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Examining the psychosocial determinants of exercise during pregnancy using the framework of the theory of planned behavior

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Examining the psychosocial determinants of exercise during pregnancy using the framework of the theory of planned behavior a prospective investigation
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Downs, Danielle Symons, 1973-
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Body mass index ( jstor )
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Motivation ( jstor )
Normativity ( jstor )
Pregnancy ( jstor )
Psychology ( jstor )
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Saliency ( jstor )
Spouses ( jstor )
Women ( jstor )
Dissertations, Academic -- Exercise and Sport Sciences -- UF ( lcsh )
Exercise and Sport Sciences thesis, Ph. D ( lcsh )
City of Gainesville ( local )
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Thesis (Ph. D.)--University of Florida, 2002.
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Includes bibliographical references (leaves 152-164).
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Printout.
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Vita.
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by Danielle Symons Downs.

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EXAMINING THE PSYCHOSOCIAL DETERMINANTS OF EXERCISE DURING
PREGNANCY USING THE FRAMEWORK OF THE THEORY OF PLANNED
BEHAVIOR: A PROSPECTIVE INVESTIGATION












By


DANIELLE SYMONS DOWNS


A DISSERTATION PRESENTED TO THE DEPARTMENT OF EXERCISE
AND SPORT SCIENCES OF THE UNIVERSITY OF FLORIDA IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY IN HEALTH AND HUMAN PERFORMANCE

UNIVERSITY OF FLORIDA


2002






























Copyright 2002

by

Danielle Symons Downs


























This dissertation is dedicated to my best friend and husband, Jon Downs.
He is my inspiration.














ACKNOWLEDGMENTS

I would like to take this opportunity to extend my deepest gratitude and

appreciation to the many people who have helped me throughout this entire dissertation

process. First, I would like to thank my advisor, Dr. Heather Hausenblas, for her

intelligence, guidance, support, and tremendous patience. This dissertation would not

have been possible without her UF Opportunity Fund grant, and her countless hours of

planning, preparation, and thrashing oopss, I mean editing!) @ Heather has been not only

my advisor and mentor, but my greatest role model. I am grateful for her many pep talks,

for pushing me to work to my potential, and for helping me become who I am today.

Most of all, I thank Heather for her friendship. I am forever grateful for her! Second, I

would like to thank my other committee members: Dr. Robert Singer, Dr. James

Shepperd, and Dr. Peter Giacobbi. Dr. Singer will always be the first person who gave

me the chance to prove myself. I thank him for his continued support, guidance, and

direction. Most of all, I thank him for his trust and for believing in me. I thank Dr.

Shepperd for sharing his knowledge, for answering many of my questions, and for

challenging me to see myself and my research, from another perspective. I thank Dr.

Giacobbi, for his time and his insightful conversations regarding my research philosophy.

Third, I would like to extend a special thanks to those individuals who assisted me

with recruiting my participants and collecting data. Without Dr. Andreoli's support, this

dissertation would not have been possible. He is an inspiration in so many ways, not to








not to mention and outstanding physician and father. I thank Dr. Connor and Katherine

Hutchison for allowing me to collect data from their office. I am grateful for Katherine's

dedication to my project and for our many talks. I would also like to thank Nini

DeBraganza and Shivani Shaw for their commitment, and their many hours of assistance

with this project. I could not have finished this dissertation without all of them!

Fourth, I would like to thank the many people in my life who have believed in

me: especially Heather Polen, the Schwartz's, the Andreoli's, and the Stafford's. I thank

them for always being there, even when I didn't have much to offer back. I thank Becky

Ellis Gardner for her support, and Derek de la Pena, Amy Hagan, Aaron Duley, Jim

Curby, Lori Gibbs, and Gary Nave for keeping me sane...they are the best!

Finally, I would like to thank my family for their unconditional love and support.

My deepest gratitude is extended to my parents, Sandra and Robert Symons, and Susan

and John Downs. Their encouragement, faith, and love will always make me strive to be

my best. I thank my sisters and brothers for putting up with me! I thank the Repka's and

the Reid's for their encouragement, trips to the airport, and for making their homes ours. I

thank my Pap for challenging and believing in me. He makes me proud! Finally, it is

without question that my husband, Jon, is the reason for this dissertation. I thank God

everyday for him. Without his motivation, inspiration, faith, love, and humor, this project

would not have been possible. I thank him for his patience, putting up with my

"meltdowns," and for understanding why I needed to spend many endless nights glued to

the computer "until it was perfect." He is my best friend (my "buddy"), and my greatest

inspiration. Lastly, I am grateful that he was able to keep himself busy on the golf course

while I wrote this dissertation. It was a tough job, but together, we can handle anything!















TABLE OF CONTENTS
page

ACKNOWLEDGMENTS..................................................................... iv

A BSTRA CT .................................................................... .... ........................... xi

CHAPTER

1 INTRODUCTION ........................................ ...................... ......................... 1

Theory of Planned Behavior Constructs ......................................................... 3
Scale Correspondence ................................................................ ..........................8
Elicitation Studies ........................................................ ...........................10
Empirical Support for the TPB and Exercise Behavior ........................................... 12
Importance of Examining Exercise and Pregnancy ........................................ ... 15
D issertation Studies............................................................ ............................. 16

2 STUDY 1: THE THEORY OF PLANNED BEHAVIOR AND ELICITATION
STUDIES: A SYSTEMATIC REVIEW OF EXERCISE BELIEFS.......................... 19

M ethod .................................................. .......................................................25
Selection and Inclusion of Studies .....................................................................25
Review Procedures .......................................... ..........................25
D ata A analysis .................................................................... ...........................26
Results ....................................................... ..................................................35
Elicitation Study Characteristics ................................. .. ................................35
Main Theory of Planned Behavior Study Characteristics ...................................35
Elicitation Study Method Characteristics .................... ...........................38
Elicitation Study Belief Characteristics .......................... ............................38
Discussion .... ........................................................... ........................44
Prelude to Chapter 3 ........................................ ............................................. 51

3 STUDY 2: THE THEORY OF PLANNED BEHAVIOR AND EXERCISING
DURING PREGNANCY AND POSTPARTUM: AN ELICITATION STUDY .......52

Method ........................................... ....................... ............................61
Participants ................................................... ..........................................61
M measures ....................................................................... ......................... 61
Procedure ........ ............................... ..............................64









D ata A analysis ..................................................................... ......................... 65
Results ..................... ..... .... ................... ..... ....................... 66
Discussion ................................. .... ..... ..........................76
Prelude to Chapter 4 ....................................... ............... ............ .............82

4 STUDY 3: EXAMINING PREGNANT WOMEN'S EXERCISE INTENTION
AND BEHAVIOR FROM THEIR SECOND TO THEIR THIRD TRIMESTER:
A PROSPECTIVE EXAMINATION OF THE THEORY OF PLANNED
BEHAVIOR ........... ............ ................................... ................... 83

M ethod ........................................ ... .................... .......................... 89
Participants .................................. ............... ...........89
M measures ....................................... ......... ....................89
Procedure ............................ .... .. .... ........... ...............96
Data Analysis ..................... ................. ....................................98
Results .................................. ....... ...... ........... .......................... 99
Discussion ... ........................................... .... ....................102

4 GENERAL DISCUSSION .................................... ....... ................. 110

Summary of the Dissertation Studies ........................... .................... 110
Study 1 ........................................ ............................................. .................. 110
Study 2 ................................................ ......... .... 112
Study 3 .................................................................. ......................... 114
Recommendations for Future Research ............................. ....................116
M oderator Variables ........................ ................................ 116
Conceptual and Measurement Issues ............................................................. 117
Practical Implications of This Dissertation ................................ ...........122
C conclusion ....................................................................... ............................... 123

APPENDIX

A THEORY OF PLANNED BEHAVIOR AND EXERCISE STUDIES
WITH SPECIAL POPULATIONS ............................... ..... ............. 125

B PERSONAL HISTORY QUESTIONNAIRE ...................................................130

C LEISURE-TIME EXERCISE QUESTIONNAIRE ............................................ 131

D ELICITATION BELIEFS QUESTIONNAIRE................. ... .... ........... 132

E IRB APPROVAL FOR STUDY 2 .................................. ......................... 135

F CONSENT FORM ........................ ..... .... .......................... 136

G PERSONAL HISTORY QUESTIONNAIRE .................................... .............. 137

H BEHAVIORAL BELIEF ITEMS ............................................. ..... 138









I NORMATIVE BELIEF ITEMS .................................................... 139

J CONTROL BELIEF ITEMS ...................................... ......................... 140

K ATTITUDE ITEM S .......................................................... ......................... 141

L SUBJECTIVE NORM ITEM ...................................................................... ......... 142

M PERCEIVED BEHAVIORAL CONTROL ITEMS ............................................... 143

N INTENTION ITEM .......................................................... ......................... 144

O EXERCISE BEHAVIOR ITEM .................................... ....................... 145

P IRB APPROVAL FOR STUDY 3 ........................................................... ............ 146

Q STUDY 3 EXPLANATION ...................................... ......................... 147

R CONSENT FORM ............................................. 148

S SECOND TRIMESTER COVER LETTER .......................................................... 149

T POSTCARD REMINDER ................... ................................................. 150

U THIRD TRIMESTER COVER LETTER ............................................................... 151

REFEREN CES .................................................................... .......................... 152

BIOGRAPHICAL SKETCH ................................... ........................ 165
























viii














LIST OF TABLES


Table page

2.1 Elicitation and Main Theory of Planned Behavior Study Sample
Characteristics and the Number and Types of Elicitation Beliefs ................ 27

2.2 The Number (N) and Percent (%) of Main Theory of Planned Behavior
and Elicitation Study Characteristics ............................................. 36

2.3 The Number (N) and Percent (%) of Elicitation Study Behavioral,
Normative, and Control Beliefs ................................ .....................39

3.1 The Number (N) and Percent (%) of Demographic Characteristics for the
Participants ....................................................... .................... 62

3.2 Type, Number (N), and Percent (%) of Beliefs Reported During Pregnancy .... 67

3.3 Type, Number (N), and Percent (%) of Beliefs Reported During Postpartum... 70

4.1 The Number (N) and Percent (%) Demographic Characteristics for the
Participants .............................. .................... ......... 90

4.2 Corresponding Demographic Characteristics for the Elicitation Study
Participants and the Main Theory of Planned Behavior Study Participants ..... 92

4.3 Hierarchical Regression Analyses for the Theory of Planned Behavior
Constructs .......................... ........... ................... 100

4.4 Correlations, Means (M), and Standard Deviations (SD) Among the
Theory of Planned Behavior Constructs ........................................ 101

4.5 Number (N), Means (M), Standard Deviations (SD), t-test Mean
Comparisons, and Eta Squared (rl) Values for the Leisure-Time Exercise
Questionnaire (LTEQ) and Body Mass Index (BMI) .......................... 102














LIST OF FIGURES


Figure page

1.1 Schematic representation of the theory of planned behavior ........................4

3.1 Mean Leisure-Time Exercise Questionnaire (LTEQ) total scores for prior
to pregnancy, during pregnancy, and during postpartum ......................... 72

3.2 Mean body mass index (BMI) prior to pregnancy and during postpartum ...... 72

3.3 Most salient behavioral advantages of exercising during pregnancy ............. 74

3.4 Most salient behavioral advantages of exercising during postpartum ............ 74

3.5 Most salient normative beliefs of exercising during pregnancy ................. 75

3.6 Most salient normative beliefs of exercising during postpartum .................. 75

3.7 Most salient obstructing control beliefs of exercising during pregnancy ......... 77

3.8 Most salient obstructing control beliefs of exercising during postpartum ....... 77

5.1 Hierarchical conceptualization of perceived behavioral control .................120














Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy in Health and Human Performance

EXAMINING THE PSYCHOSOCIAL DETERMINANTS OF EXERCISE DURING
PREGNANCY USING THE FRAMEWORK OF THE THEORY OF PLANNED
BEHAVIOR: A PROSPECTIVE INVESTIGATION

By

Danielle Symons Downs

August 2002

Chairperson: Dr. Heather Hausenblas
Major Department: Exercise and Sport Sciences

Pregnancy is associated with numerous physical and psychological demands that

may reduce women's exercise behavior; however, the research examining women's

behaviors, attitudes, and cognitions during pregnancy is scant. Consequently, there is a

need for research that theoretically examines the determinants of exercising during

pregnancy. The general objective of this dissertation was to examine the predictive utility

of the theory of planned behavior (TPB) in explaining pregnant women's exercise

intention and behavior. In an attempt to achieve this objective, and adhere to the theory

guidelines established by Ajzen and Fishbein (1980), the following three studies were

conducted:

* Study 1 was a review of 38 TPB elicitation studies with exercise behavior.

* Study 2 was a TPB elicitation study of 74 postpartum women's beliefs about
exercising during their pregnancy and postpartum.








* Study 3 was a prospective examination of the TPB and 81 pregnant women's exercise
intention and behavior from their second to their third trimester.

For Study 1, the primary findings for healthy and special populations' salient

exercise beliefs were: a) physical and psychological health (behavioral beliefs), b) friends

and family (normative beliefs), and c) physical and psychological issues (control beliefs).

For Study 2, the primary findings for women's salient beliefs about exercising during

their pregnancy were: a) overall mood (behavioral beliefs), b) husband or fiance

(normative beliefs), and c) physical limitations and restrictions (control beliefs). The

salient beliefs about exercising during postpartum were: a) weight control (behavioral

beliefs), b) husband or fiance (normative beliefs), and c) no time (control beliefs). For

Study 3, it was found that the TPB was successful in predicting pregnant women's

exercise intention and behavior. More specifically, intention was the strongest predictor

of pregnant women's exercise behavior, and perceived behavioral control was the

strongest predictor of their intention from their second to their third trimester.

Implications of the results from all three studies are discussed, as well as future research

directions and practical implications.














CHAPTER 1
INTRODUCTION

Over the past 50 years in the United States, healthcare has been dictated by the

types of diseases that dominate medical expenses and mortality. For example, the leading

causes of death in the 1950s were communicable diseases such as pneumonia and

tuberculosis. However, in the 2000s, chronic behavioral diseases such as cardiovascular

disease and cancer are responsible for the greatest medical expenses and mortality among

American adults (Centers for Disease Control [CDC], 1999; National Center for Health

Statistics [NCHS], 1997). Although advances in medicine and science enable doctors to

manage the communicable diseases of the 1950s, they have not had the same success

with today's behavioral diseases. Ailments such as atherosclerosis, cancer, diabetes, and

obesity have generated medical expenses in the United States in excess of 95 billion

dollars annually (American Heart Association [AHA], 1997; Twisk, Kemper, & Van

Mechelen, 2000). While some people may have a genetic predisposition for these

illnesses, most chronic behavioral diseases are associated with a variety of lifestyle

factors including smoking, poor diet, and sedentariness (Blair, 1994; Giovannucci et al.,

1995; Mitchell, Almasy, & Rainwater, 1999; NCHS).

People can reduce their risk of chronic diseases by making decisions to adopt

positive lifestyle patterns such as eating balanced diets, having routine physical

examinations, and maintaining healthy body weights (AHA, 1997; Taylor, 1999; Twisk

et al., 2000). Aside from these positive behaviors, engaging in regular physical activity is








another effective method for alleviating the symptoms associated with many chronic

diseases. For example, regular exercise contributes positively to physical health (e.g.,

lowering heart rate, improving lung capacity, increasing work output) and psychological

well-being (e.g., decreasing anxiety and depression and improving body image; United

States Department of Health and Human Services [USDHHS], 1996, 2000).

Despite the efforts of government sponsored programs (e.g., Healthy People

2010), that aim to increase the number of active individuals, most North Americans are

not engaging in sufficient exercise to experience its health-related benefits (CDC, 1999;

NCHS, 1997; USDHHS, 2000). That is, most people do not meet the guidelines of

engaging in 30 min of accumulated moderate to vigorous physical activity on most, if not

all, days of the week (American College of Sports Medicine [ACSM], 2000; CDC). For

example, 50% of adolescents and young adults ages 12 to 21 are inactive, approximately

60% of adults do not engage in regular physical activity, and 75% of people over the age

of 65 are sedentary (Grove & Spier, 1999; Sullum, Clark, & King, 2000; USDHHS). In

addition, nearly 50% of adults dropout of an exercise program within the first 6 months

(Dishman, 1993). Therefore, in an effort to increase exercise participation, researchers

have advocated the need for conceptually based models of physical activity participation

(Maddux & DuCharme, 1997).

Before the 1980s, studying the psychosocial determinants of exercise behavior

has been data-driven and theoretical in nature (Rejeski, 1995). In part, this is due to a

lack of theoretical models developed for exercise behavior (Maddux, 1993; Maddux &

DuCharme, 1997). Thus, exercise researchers have borrowed theoretical frameworks

from mainstream psychology to examine the psychological, social, and environmental








determinants of exercise behavior (Rimal, 2001). Although many psychological theories

have been applied to exercise behavior, the theory of planned behavior (TPB; Ajzen,

1985, 1988) has emerged as an effective structure for studying the multidimensional (e.g.,

social, cognitive, and behavioral) determinants of exercise participation. Because the

TPB includes many of the same components found in other behavioral models, it offers

researchers a comprehensive framework for understanding and predicting exercise

behavior (Maddux & DuCharme). The purpose of this introduction is to:

* Describe the TPB constructs.

* Discuss scale correspondence.

* Define and explain elicitation studies.

* Provide empirical support for the TPB and its application to exercise behavior.

* Examine the strengths of the TPB.

* Illustrate the importance of examining exercising and pregnancy.

* Briefly describe the three studies conducted for this dissertation.

Theory of Planned Behavior Constructs

The TPB was developed by Ajzen (1988, 1991) as a revision of the theory of

reasoned action (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975). It includes the

following five main constructs: behavior, intention, attitude, subjective norm, and

perceived behavioral control (see Figure 1.1). Associations among the theoretical

constructs is expressed with the following equation: B ~ I = (Aact)wt + (SN)w2 +

(PBC)w3, whereby behavior (B) is affected by intention (I), and wi, w2, and w3 represent

empirically determined weighing parameters that reflect the influence of attitude (Aact),










Aact








PBC



Figure 1.1. Schematic representation of the Theory of Planned Behavior. Stable
theoretical associations linking attitude (Aact), subjective norm (SN), and perceived
behavioral control (PBC) to intention (I) are represented by the solid arrows, and a direct
relationship linking perceived behavioral control to behavior (B) is represented by the
dashed arrow (adapted from Ajzen, 1991).

subjective norm (SN), and perceived behavioral control (PBC) on people's intentions

(Ajzen & Madden, 1986).

The primary objective of the TPB is to understand and predict human behavior

based on people's intention to perform or not perform a certain behavior (Ajzen &

Fishbein, 1980). Intention represents a person's strategy for carrying out an action. It is

assumed to resemble how much motivation and effort the individual is planning to exert

to perform a behavior (Ajzen, 1991). A consistent finding in the TPB literature is that

people's intentions strongly predict their behavior. That is, the stronger one's intention to

engage in a behavior, the more likely one will perform that behavior. The TPB posits that

people's intentions are influenced by the following three factors:

* Their attitude about the behavior (i.e., attitude).

* Their perception of the social pressures to perform the behavior (i.e., subjective
norm).








* Their beliefs about how easy or difficult it will be to engage in the behavior (i.e.,
perceived behavioral control).

Intention is expected to influence behavior to the extent that people have behavioral

control, and they are motivated to try the behavior. The more positive an individual's

attitude, subjective norm, or both, and the more salient his or her perceived behavioral

control, the stronger his or her intention is to perform the behavior (Ajzen & Fishbein).

The constructs of attitude, subjective norm, and perceived behavioral control are

described in more detail below.

Attitude is defined as a personal belief toward a behavior. It is a function of the

strength of this association and the perceived consequences of carrying out the behavior

(Ajzen, 1985; Ajzen & Fishbein, 1980). Expressed as the following formula: Aact =

E b x e, attitude (Aact) is the summed product of behavioral beliefs (b) multiplied by

one's evaluation (e), either positive or negative, of performing the behavior. Behavioral

beliefs are postulated to be the driving force behind people's attitude, and they are

represented by instrumental beliefs (i.e., benefits and costs of engaging in the behavior),

and affective beliefs (i.e., positive or negative feelings derived from the behavior; Ajzen

& Driver, 1992; Madden, Scholder, & Ajzen, 1992). People's attitude strongly predicts

their behavioral intention. That is, when people believe that engaging in a behavior will

produce positive outcomes, they are more likely to have a favorable attitude toward it

(Ajzen). People typically have between 5 and 10 readily available beliefs about engaging

in a particular behavior (Godin & Shephard, 1990). For example, the most common

behavioral beliefs about exercise held by healthy populations include both positive (e.g.,

exercising will improve physical and psychological health) and negative (e.g., exercising

will decrease time spent with family and friends) expectations (Carron, Hausenblas, &








Estabrooks, 2003). These beliefs can vary depending on the time and situation, and they

are critical in adopting and maintaining exercise behavior.

Subjective norm (SN) is defined as the perceived social pressures to behave in a

particular way. It is a function of the perceived expectations of significant others (e.g.,

family members, friends, coworkers), and one's motivation to comply with the requests

of these people (Ajzen & Fishbein, 1980). Expressed in the following formula: SN = E

NB x MC, subjective norm is the summed product of normative beliefs (NB; i.e., whether

important others think a person should or should not engage in a behavior) multiplied by

motivation to comply (MC; i.e., how much the person is compelled to conform with the

request of significant others). People are influenced by significant others to the extent that

they value the opinions of others. For example, if people believe that their spouses want

them to exercise, and they value their spouses' opinion, their subjective norm for exercise

will be higher, and it will positively influence their intentions (Culos-Reed, Gyurcsik, &

Brawley, 2001). Frequently reported normative beliefs are the expectations of important

individuals (e.g., a spouse, friend, or other family member) and groups (e.g., coworkers,

roommates, church members; Carron et al., 2003).

Perceived behavioral control (PBC) reflects how people's beliefs about their

resources, skills, and opportunities are viewed as underlying behavioral control (Ajzen,

1985, 1988). These facilitating and obstructing factors are referred to as control beliefs

(c), and they interact with a corresponding measure of perceived power (p) in the

expression: PBC = Z c x p. Most health-related activities such as smoking, weight

control, and exercise fall along a continuum from total control to complete lack of control

(Godin & Shephard, 1990). For example, people have control when they can decide to








perform or not to perform a behavior, and when there are no restrictions for behavior

adoption (Ajzen, 1991). Alternatively, when a behavior requires external resources (e.g.,

money, time, cooperation from others, opportunities, skills) that are absent, people have a

lack of control (Godin, 1994).

Perceived behavioral control has been compared to perceived barriers

(Rosenstock, 1966) and facilitating conditions (Triandis, 1977); however, it is frequently

conceptualized as self-efficacy (Bandura, 1986, 1997). According to Ajzen (1991), self-

efficacy is a belief that one can successfully perform a desired behavior, whereas

perceived behavioral control is a person's perception of the ease or difficulty in

performing a behavior at a specified time. Ajzen (in press) argued that perceived

behavioral control and self-efficacy are conceptually similar; thus, they have the same

mediating role with exercise behavior. That is, perceived behavioral control and self-

efficacy can have direct influences on behavior, and they can impact behavior indirectly

through intention (Ajzen, 1985).

The TPB proposes that behavior can be explained by the combined influences of

the model constructs. However, Ajzen and Fishbein (1980; Ajzen, 1991) argued that four

conditions must be met for the model to accurately predict behavior. First, they proposed

that measures of intention and perceived behavioral control must correspond with the

behavior. For instance, if the behavior is to participate in 30 min of leisure-time physical

activity everyday, then intentions to participate in 30 min of leisure-time physical activity

must be assessed, and perceived behavioral control should be measured accordingly.

Second, Ajzen and Fishbein suggested that the measurement of intention should be as

close in time as possible to the behavior. The longer the time interval, the greater the








likelihood that intentions will be affected by external (uncontrollable) factors and

consequently have the potential for change. Third, intentions and perceived behavioral

control must remain stable in the time between their assessment and behavioral

observation. That is, any intervening event that occurs between measuring intention and

behavior may alter people's intention to perform the behavior. For instance, a person's

intention to attend a fitness class is measured before the class onset; however, once

exposed to the intensity of the workouts, his or her intentions may change before the

exercise behavior is assessed. Finally, when people's perceived behavioral control

accurately reflects their perceptions of actual control, the likelihood of predicting

behavior improves (Ajzen). According to Ajzen, the accuracy of the TPB in predicting

and explaining behavior is compromised when researchers fail to adhere to these four

model guidelines.

Scale Correspondence

Scale correspondence is obtained when the items that measure intention and

behavior are consistent with respect to the action, target, context, and time (Ajzen &

Fishbein, 1980; Courneya & McAuley, 1994). For example, scale correspondence is

achieved if intention is assessed with the item: "I intend to exercise for at least 20

minutes per day for 3 of the next 7 days" and behavior is measured with the item: "I

exercised for at least 20 minutes per day for 3 of the past 7 days." In contrast, for

example, scale correspondence is not achieved if intention is measured with the item: "I

intend to exercise for at least 20 minutes per day for 3 of the next 7 days" and behavior is

measured with the item: "I walked more than twice last week." In this example, the items

assessing intention and behavior do not correspond with respect to their action (i.e.,








"exercise" versus "walked") and their time (i.e., "at least 20 minutes per day for 3 of the

next 7 days" versus "more than twice last week").

Scale correspondence is important to obtain when predicting behaviors such as

exercise that may vary in action, target, context, and time. For example, a person may

want to run (action) to lose weight (target), and he or she may do so in a variety of

contexts (e.g., at home, around the neighborhood, at the gym) during different parts of the

day (time). Thus, to obtain a better association between intention and behavior, and

improve the predictive utility of the TPB, it is important to specify the same conditions

for the intention and behavior items (Coumeya & McAuley, 1994; Symons Downs &

Hausenblas, 2002). To obtain scale correspondence, Courneya and McAuley (1993)

suggested that intention and behavior may be assessed with any of the following four

methods:

* Continuous-open (e.g., "I intend to exercise times during the next three weeks,"
and "I exercised times during the past three weeks").

* Continuous-closed (e.g., "I intend to exercise during the next 3 weeks the following
number of times: 0-1, 2-4, 5-7, etc.," and "I exercised during the past 3 weeks the
following number of times: 0-1, 2-4, 5-7, etc.").

* Dichotomous-yes/no (e.g., "I do do not intend to exercise at least nine times
during the next three weeks," and "I did did not exercise at least nine times
during the past three weeks").

* Dichotomous-graded (e.g., "I intend to exercise at least nine times during the next
three weeks," and "I exercised at least nine times during the past three weeks").

While Courneya and McAuley (1993) recommended that any of the previous

methods can be used to achieve scale correspondence, Coumeya and McAuley (1994)

examined the physical activity behavior of 170 undergraduate students, and they found

that the continuous-open scale produced a larger intention-behavior association than the








dichotomous-graded scale (Courneya & McAuley, 1994). Thus, for the purpose of this

dissertation, a continuous-open scale was used to measure intention and behavior (see

Study 3).

Moreover, Symons Downs and Hausenblas (2002) meta-analytically examined

scale correspondence with 87 TPB and exercise studies, and they found two important

findings. First, scale correspondence was obtained in only 17.5% of the exercise studies

that were reviewed. Second, a larger intention-behavior association was found for studies

with scale correspondence (effect size d = 1.57) compared to studies without scale

correspondence (effect size d = .90). Thus, consistent with previous researchers'

suggestions (e.g., Courneya & McAuley, 1994; Culos-Reed et al., 2001; Symons Downs

& Hausenblas), researchers applying the TPB to exercise should examine, or at least

acknowledge, scale correspondence. If not, the predictive utility of the TPB is

compromised. Therefore, to be consistent with previous researchers' recommendations,

scale correspondence was obtained in Study 3 of this dissertation (see Chapter 4).

Elicitation Studies

According to Ajzen and Fishbein (1980), an elicitation study is similar to a pilot

investigation. The purpose of an elicitation study is to determine the behavioral,

normative, and control beliefs of a population. Because the TPB posits that people's

beliefs are the underlying structure for their attitude, subjective norm, and perceived

behavioral control, Ajzen and Fishbein recommended that an elicitation study be

conducted before the main TPB study (i.e., a study that examines the utility of the TPB

constructs; see Chapter 4 for an example of a main TPB study) to establish the








participants' beliefs about a behavior. To ensure that researchers are conducting

elicitation studies properly, Ajzen and Fishbein established the following four guidelines:

* The elicitation study population and the main TPB study population should be similar
with respect to the participants' demographic characteristics (e.g., type of population,
age, sex, race/ethnicity, and socioeconomic status).

* Open-ended statements are recommended because they allow the participants to
record multiple behavioral, normative, and control beliefs about a behavior (e.g.,
"List the advantages of exercising over the next three months").

* A content analysis (i.e., a frequency count) is used to rank-order the participants'
beliefs. This can be rank-ordered into higher-order themes (e.g., improving physical
and psychological health) and raw data themes (e.g., keeping fit, maintaining health,
and exercise feels good).

* The 5 to 10 most common behavioral, normative, and control beliefs that emerge
from the participants' responses are used to develop the beliefs instrument for the
TPB main study.

To determine if elicitation studies impacted the TPB associations, Symons Downs

and Hausenblas (2002) meta-analytically examined their moderating influence with 87

TPB and exercise studies. They found a larger intention-behavior association in main

TPB studies that included an elicitation study (effect size d = 1.32) compared to main

TPB studies without an elicitation study (effect size d = .86). In addition, they found a

larger perceived behavioral control-behavior association for main TPB studies with an

elicitation study (effect size d = .78) compared to main TPB studies without an elicitation

study (effect size d = .34). However, elicitation studies were conducted in only 46.0% of

the main TPB studies examined in the meta-analysis; thus, Symons Downs and

Hausenblas suggested that researchers adhere to the TPB guidelines and conduct an

elicitation study before examining the predictive utility of the model.

In summary, elicitation studies are an important facet of the TPB's structure, and

the predictive utility of the model is compromised when they are not conducted before








the main TPB study (Symons Downs & Hausenblas, 2002). Thus, an elicitation study was

conducted for this dissertation (see Chapter 3) to determine the salient beliefs of pregnant

women, and to develop the beliefs instrument for the main TPB study (see Chapter 4).

Empirical Support for the TPB and Exercise Behavior

Researchers have found that on average, attitude, subjective norm, and perceived

behavioral control explain 40% to 60% of the variance in exercise intentions, and 20% to

40% of the variance in exercise behavior (Culos-Reed et al., 2001). The findings from

narrative (e.g., Blue, 1995; Godin, 1993) and statistical (e.g., Hagger, Chatzisarantis, &

Biddle, 2002; Hausenblas, Carron, & Mack, 1997; Symons Downs & Hausenblas, 2002)

reviews of the literature provide support for the TPB constructs with exercise behavior.

For example, Godin examined eight TPB studies applied to exercise, and he found that

perceived behavioral control significantly predicted exercise behavior. In addition, he

found that attitude and subjective norm predicted intention; with attitude being the

stronger predictor. Also, Blue reviewed seven TPB studies and she found that:

* Behavioral beliefs were positively associated with attitude in six studies.

* Normative beliefs were positively associated with subjective norm in five studies.

* Attitude predicted intentions in all seven studies.

* Most subjective norm-intention associations were nonsignificant.

* Perceived behavioral control contributed to predicting exercise intention beyond
attitude and subjective norm in five studies.

Moreover, Hausenblas and her colleagues (1997) reviewed 31 studies with over

10,000 participants applying the theories of reasoned action and planned behavior (41.9%

TPB) to exercise. They found large associations between:








* Intention and behavior (effect size d = 1.09).

* Perceived behavioral control and behavior (effect size d = 1.01).

* Perceived behavioral control and intention (effect size d = .97).

* Attitude and intention (effect size d = 1.22).

In addition, they found a moderate association between subjective norm and intention

(effect size d = .56)'. The authors concluded that intention had a larger effect on exercise

behavior than perceived behavioral control, and attitude had a larger effect on intention

than perceived behavioral control and subjective norm. Furthermore, although subjective

norm was less associated with intention than attitude and perceived behavioral control,

Hausenblas et al. argued that the influence of people's subjective norm on their intention

and behavior should not be overlooked.

While the Godin (1993), Blue (1995), and Hausenblas et al. (1997) reviews

contribute to the TPB and exercise literature, two limitations have been identified. First,

Godin and Blue used vote-counting procedures to quantify the literature. More

specifically, they sorted the results of the studies into positive, negative, and

nonsignificant categories, and then analyzed their findings. While there are benefits to

this type of review, this technique's power decreases as the number of studies included in

the review increases (Hedges & Olkin, 1980). Thus, meta-analytic procedures are

recommended to statistically review the literature because they provide for the integration

of many diverse studies using the full power of statistical methods (Glass, McGraw, &

Smith, 1981).



'The values of.20, .50, and .80 correspond to small, medium, and large effect sizes, respectively,
(Cohen, 1969, 1992).








Second, Ajzen (1991) recommended that researchers use hierarchical regression

analysis when examining the predictive utility of the model because this technique is

consistent with the TPB constructs. Because the meta-analysis by Hausenblas et al.

generated a small number of effect sizes (n = 8) examining the complete TPB, these

authors had insufficient power to examine the predictive utility of the TPB with

hierarchical regression procedures2.

Thus, Symons Downs and Hausenblas (2002) conducted an updated meta-analytic

review of the literature with the following two objectives. The first objective was to

examine the strength of the associations among the TPB constructs with exercise

behavior. The second objective was to examine the predictive utility of the TPB with

hierarchical regression analyses. Symons Downs and Hausenblas reviewed 87 studies

that included a total of 20,616 participants and yielded 164 effect sizes, and they found:

* Large associations for:
o Intention and behavior (effect size d = 1.04).
o Attitude and intention (effect size d = 1.06).
o Perceived behavioral control and intention (effect size d = .83).

* Moderate associations for:
o Perceived behavioral control and behavior (effect size d =.52).
o Subjective norm and intention (effect size d = .59).

* For predicting intention:
o Attitude, perceived behavioral control, and subjective norm explained 29% of
the variance in intention.
o Attitude and perceived behavioral control provided unique contributions,
however, subjective norm did not.
o Attitude was the strongest predictor of intention.



2Adequate power to conduct the hierarchical multiple regression for a model with 2 predictors is
determined by samples sizes based on power analysis of .80 with 481, 66, and 30 being small,
medium, and large effect sizes, respectively. A model with 3 predictors is based on analysis with
547 (small), 76 (medium), and 35 (large) effect sizes (Green, 1991).








* For predicting exercise behavior:
o Intention and perceived behavioral control explained 21% of the variance in
exercise behavior.

intention was the only significant predictor of exercise behavior. These findings support

that people's attitude is the strongest predictor of their intention, and their intention is the

strongest predictor of their exercise behavior. Symons Downs and Hausenblas concluded

that the TPB provides researchers with a strong conceptual model for explaining exercise

behavior in healthy populations, and that further research is needed examining the utility

of the TPB with populations that are at risk for sedentary behavior.

Importance of Examining Exercise and Pregnancy

Pregnancy is an important time in women's lives that may place them at greater

risk for decreased physical activity (USDHHS, 2000). For example, Zhang and Savitz

(1996) found that nearly 60% of pregnant women are sedentary. Many women find the

added physiological (e.g., increased cardiac output, body temperature, and respiration)

and psychological (e.g., increased anxiety and depression) demands of pregnancy too

stressful; thus, they decrease or stop exercising during this time (American College of

Obstetricians and Gynecologists (ACOG), 1994; Bungum, Peaslee, Jackson, & Perez,

2000; Carter, Baker, & Brownell, 2000). Despite women's concerns about exercising

during their pregnancy, it contributes positively to women's health (USDHHS). In

addition, the ACOG recommends that healthy pregnant women exercise moderately for at

least 15 min per day, 3 to 5 days per week. Thus, to promote physical activity during

pregnancy, it is necessary to examine the determinants of exercising during this time.

Moreover, it is important to study exercising and pregnancy because the literature is

scant, and it is limited by several factors, including:








* Small sample sizes (Berg, 1999).

* Few human participant studies (Koniak-Griffin, 1994).

* A lack of theoretical research explaining the determinants of exercising during
pregnancy (Walker, Cooney, & Riggs, 1999).

* Methodological concerns with using nonstandardized exercise measures (Eisen,
Rield, & Larason, 1991).

* Mostly cross-sectional studies (Koniak-Grifin).

Thus, the studies included in this dissertation aimed to improve on the previous exercise

and pregnancy literature by:

* Including pregnant women (i.e., Studies 2 and 3).

* Using a standardized measure of exercise behavior (i.e., Studies 2 and 3).

* Prospectively examining pregnant women's exercise behavior from their second to
their third trimester (i.e., Study 3)

* Using the TPB framework for understanding and explaining pregnant women's
exercise behavior (i.e., Studies 1, 2, and 3).

Dissertation Studies

The general objective of this dissertation was to examine the utility of the TPB in

understanding, predicting, and explaining pregnant women's exercise intention and

behavior. In an effort to adhere to the theory guidelines developed by Ajzen and Fishbein

(1980) and to achieve the general objective of this dissertation, three studies were

conducted. The following section provides a brief overview of each study, followed by a

general description of the final discussion chapter.

1. Study 1 (Chapter 2) is a review of 38 TPB and exercise studies that conducted

an elicitation study before the main TPB study. Elicitation studies are important for two

primary reasons: a) they determine people's exercise beliefs, and b) they are used to








develop the assessment instrument for measuring the TPB constructs in the main TPB

study (Ajzen & Fishbein, 1980). However, the research examining exercise elicitation

studies is scant. Thus, a systematic review of this literature would:

* Identify people's common behavioral, normative, and control beliefs about exercise.

* Determine researchers methods for determining these beliefs.

* Establish whether exercise beliefs of healthy populations differ from populations that
are at risk for sedentary behavior.

There were two purposes of Study 1. The first purpose was to review the salient

behavioral, normative, and control beliefs of exercise elicitation study participants. The

second purpose was to examine the elicitation study methods (i.e., participants, measures,

and procedures). A detailed list of the reviewed studies is provided describing the study

characteristics and elicited beliefs. In addition, limitations of the reviewed studies are

highlighted, followed by a discussion regarding the need for future research examining

elicitation studies with exercise behavior.

2. Study 2 (Chapter 3) is a TPB elicitation study of postpartum women's beliefs

about exercising during their pregnancy and postpartum. Because of the limited number

of studies examining the TPB and exercise with pregnant populations, the methodological

concerns regarding these studies, and the lack of elicitation studies in the literature, the

study objective was to conduct a retrospective investigation of women's beliefs about

exercising during pregnancy and postpartum (K. S. Coumeya, personal correspondence,

2002). The main study purpose was to determine the frequency of women's behavioral,

normative, and control beliefs for exercising during pregnancy and postpartum. The

findings regarding the type and number of elicited beliefs are discussed. Consistent with

the TPB guidelines (Ajzen & Fishbein, 1980), the salient beliefs emerging from Study 2








were used to form the assessment instrument that was used in the prospective study of the

TPB and exercising during pregnancy (i.e., Study 3).

3. Study 3 (Chapter 4) is a prospective study of the TPB constructs and exercising

from pregnant women's second to their third trimester. Because pregnancy can promote

decreased physical activity (e.g., Zhang & Savitz, 1996), it is important to examine the

determinants of exercising during pregnancy. In addition, because few TPB studies have

included populations that are at risk for sedentary behavior, and because no located

studies have examined the TPB constructs and exercising from pregnant women's second

to their third trimester, a prospective study was warranted. The general study purposes

were to prospectively examine the utility of the TPB in predicting pregnant women's

exercise intention and behavior from their second trimester to their third trimester, and to

examine the associations among the TPB constructs. The findings from hierarchical

multiple regressions, correlations, and dependent t-tests are discussed.

4. The general discussion (Chapter 5) includes:

* The composite findings from Studies 1, 2, and 3.

* A general overview of the strengths and limitations of these studies.

* Recommendations for future research with the TPB constructs, exercise behavior, and
pregnant populations.

* Practical implications of this dissertation.














CHAPTER 2
STUDY 1: THE THEORY OF PLANNED BEHAVIOR AND
ELICITATION STUDIES: A SYSTEMATIC REVIEW OF EXERCISE BELIEFS

An important element for promoting health-related physical activity is applying

theoretical models that can identify and explain the multidimensional (e.g., social,

cognitive, behavioral) determinants of exercise participation (Biddle & Nigg, 2000;

Rimal, 2001). Despite the number of psychological theories available, no consensus

exists regarding which is the best model for studying exercise behavior (Maddux &

DuCharme, 1997). However, one conceptual framework that has been successfully

applied to exercise behavior is the theory of planned behavior (TPB; Ajzen, 1988, 1991;

Ajzen & Fishbein, 1980). The TPB is a belief-based social cognitive theory whereby

people's expectations about engaging in a behavior (and the values attached to it) form

their behavioral, normative, and control beliefs toward the behavior. These beliefs in turn,

influence people's attitude (i.e., feelings and perceived consequences of a behavior),

subjective norm (i.e., normative influences and motivation to comply with expectations

of others), and perceived behavioral control (i.e., feelings and personal control for the

facilitating and obstructing factors of behavior adoption) toward their intention, and

ultimately, their behavior (Ajzen).

Behavioral beliefs are posited to be the driving force behind people's attitude.

They are determined by people's perceived consequences (either positive or negative) of

engaging in a behavior, and their personal evaluation of each of these consequences

(Ajzen & Fishbein, 1980). For example, people may believe that exercising will improve








their health and help them to control their weight. However, they may also feel that it is

time consuming and painful. On average, people have 5 to 10 beliefs about engaging in

exercise behavior (Ajzen & Driver, 1991; Godin & Shephard, 1990). For healthy

populations, Carron et al. (2003) reported that the most common behavioral beliefs are

that exercise:

* Improves physical and psychological health.

* Improves physical appearance.

* Is fun and enjoyable.

* Is time consuming.

* Is tiring.

Normative beliefs provide the framework for subjective norm, and they are

formulated by whether important others (e.g., friends, family) think people should or

should not engage in a behavior, and people's motivation to comply with the wishes and

desires of these significant others (Ajzen, 1985). People are influenced by significant

others to the extent that their opinions are valued. For example, if a woman believes that

her spouse wants her to exercise during pregnancy, and she values her spouse's opinion,

her subjective norm for exercise will be higher. The most frequently reported normative

beliefs regarding exercise in healthy populations are individuals (e.g., friend, spouse, or

other family member) and groups (e.g., coworkers, roommates, church members; Carron

et al., 2003).

Control beliefs provide the structure for perceived behavioral control. They are

developed from people's evaluation of how easy or difficult behavior adoption will be,

and from people's perceived power of the control beliefs facilitating or inhibiting the








behavior (Ajzen, 1991). Control beliefs represent people's personal beliefs about the

facilitating and obstructing factors of behavior adoption, and they include their personal

resources, skills, and opportunities. According to Ajzen, the more resources and

opportunities that people believe they have (e.g., I have free time on Saturday to go to the

gym), and the fewer obstacles they anticipate (e.g., I can have mom watch the kids), the

greater their perception of control is for engaging in the behavior (e.g., even if mom can't

watch the kids, I can take them to the gym and let them play in the children's area). The

most common control beliefs for exercise in healthy populations are lacking time, energy,

and motivation (Carron et al., 2003).

The TPB postulates that people's beliefs influence their attitude, subjective norm,

and perceived behavioral control, which in turn, influence their intention and behavior

(Ajzen, 1991). The findings from several narrative (e.g., Blue, 1995; Godin, 1993) and

statistical (e.g., Hagger et al., 2002; Hausenblas et al., 1997; Symons Downs &

Hausenblas, 2002) reviews of the literature provide support for the TPB constructs with

exercise behavior. For example, Symons Downs and Hausenblas meta-analytically

examined 87 TPB and exercise studies, and they found: a) large associations for intention

and behavior (effect size d = 1.04), attitude and intention (effect size d = 1.06), and

perceived behavioral control and intention (effect size d = .83); and b) moderate

associations for perceived behavioral control and behavior (effect size d = .52) and

subjective norm and intention (effect size d = .59). In addition, they reported that attitude,

perceived behavioral control, and subjective norm explained 29% of the variance in

exercise intention; with attitude and perceived behavioral control providing unique

contributions in predicting intention. Also, intention and perceived behavioral control








explained 21% of the variance in exercise behavior, with intention emerging as the only

significant predictor. These findings support that people's attitude most strongly predicts

their intention, and their intention most strongly predicts their exercise behavior.

Despite the TPB's predictive success, the utility of the model is compromised

when researchers fail to adhere to the theory guidelines developed by Ajzen and Fishbein

(1980; Fishbein & Ajzen, 1975). As a result, several conceptual and methodological

issues have emerged with the TPB and exercise literature (Culos-Reed et aL, 2001). A

main methodological concern is the limited use of elicitation studies (Symons Downs &

Hausenblas, 2002). According to Ajzen and Fishbein, the purpose of an elicitation study

is to determine the behavioral, normative, and control beliefs of a population. For

example, if researchers want to study the TPB constructs for cancer patients, they should

first conduct an elicitation study with a subsample of the population to determine cancer

patients' behavioral, normative, and control beliefs about exercise (e.g., Courneya &

Friedenreich, 1997, 1999). To determine a population's salient beliefs, Ajzen and

Fishbein recommended that researchers adhere to the following three steps:

* Conduct an elicitation study with open-ended questions assessing a population's
behavioral, normative, and control beliefs.

* Perform a content analysis (i.e., a frequency count) on the results from the elicitation
study to rank-order the beliefs of the population.

* Determine the 5 to 10 most salient beliefs of the population.

Once these beliefs are established, researchers can then conduct a follow-up study (i.e.,

the main TPB study) to measure the TPB constructs (i.e., behavioral, normative, and

control beliefs, attitude, subjective norm, perceived behavioral control), and to determine

which of these theoretical tenets predict the sample's exercise intention and behavior.








While Ajzen and Fishbein (1980) suggested that researchers perform elicitation

studies before the main TPB study, most TPB and exercise studies are conducted without

them. For instance, Symons Downs and Hausenblas (2002) found that less than half of

the studies reviewed in their meta-analysis conducted an elicitation study before the main

TPB study. In addition, the authors found that the main TPB studies without elicitation

studies had smaller intention-behavior (effect size d = .86) and perceived behavioral

control-behavior (effect size d = .34) associations compared to the main TPB studies with

elicitation studies (effect sizes d = 1.32 and .78, respectively). Also, there was a

nonsignificant trend for smaller subjective norm-intention and perceived behavioral

control-intention associations in studies without elicitation studies. These findings

illustrate two limitations of the TPB and exercise literature. First, researchers

are not properly adhering to the TPB guidelines. Second, the utility of the TPB is

compromised when elicitation studies are not performed.

Thus, research examining elicitation studies is warranted for at least two reasons.

First, it is important to identify the salient exercise beliefs of a variety of populations

because not all people share the same thoughts, feelings, and ideas about exercise. For

example, researchers have reported the most common exercise beliefs of healthy

populations (Carron et al., 2003), however, it is unclear whether those beliefs represent

the salient exercise beliefs of special populations (e.g., elderly, pregnant women, obese).

Because these populations are at risk for sedentary behavior, it is necessary to examine

their behavioral, normative, and control beliefs about physical activity to identify the

factors that may assist researchers with increasing their exercise behavior.








Second, it is important to examine the methods (i.e., participants, measures, and

procedures) of elicitation studies that have been conducted with exercise behavior

because the utility of the TPB can be compromised by inadequate methods (e.g., lack of

correspondence between the elicitation sample and the main TPB sample, not following

the TPB guidelines for elicitation studies). More specifically, if the elicitation study

sample and the main TPB sample do not correspond with respect to their demographic

characteristics (e.g., type of population, M age or age range, sex, race/ethnicity, socio-

economic status), then the beliefs that emerge from the elicitation study participants may

not represent the main TPB participants. For example, if researchers examining the TPB

and exercise behavior conduct an elicitation study with a sample of Caucasian, middle-

class, pregnant women, then the main TPB study participants should also be Caucasian,

middle-class, pregnant women. Alternatively, if the elicitation study was conducted with

Caucasian, middle-class, pregnant women, and the main TPB study was conducted with

African American, lower-class pregnant women, the salient exercise beliefs of these

populations are likely to be different (USDHHS, 2000). Then, researchers are assessing

the beliefs of one population, and measuring the attitude, subjective norm, and perceived

behavioral control of another population. Thus, there is a lack of correspondence between

the elicitation and main TPB study participants, and the utility of the TPB is

compromised (Ajzen).

In addition, because inadequate measures and procedures can compromise the

utility of the TPB, it is also important to examine these components of exercise elicitation

studies. As previously stated, Ajzen and Fishbein (1980) established guidelines for

conducting elicitation studies, and they have suggested that the predictive utility of the








TPB is improved when researchers follow these procedures (e.g., using open-ended

statements to elicit the beliefs, performing a content analysis, rank-ordering the beliefs).

However, because there is a paucity of information regarding exercise elicitation study

methods, more research is warranted that examines these characteristics.

The primary study purpose was to review the salient behavioral, normative, and

control beliefs of exercise elicitation study participants. The secondary study purpose was

to examine the elicitation and main TPB studies' methods (i.e., participants, measures,

and procedures) in an attempt to determine if there was correspondence between the

elicitation and main TPB study participants, and to determine how the elicited beliefs

were obtained. Correspondence was defined as when the same participant characteristics

(i.e., population type, sex, M age or age range, race/ethnicity, and socioeconomic status)

were reported for both the elicitation and main TPB studies (Ajzen, 1991).

Method

Selection and Inclusion of the Studies

Eighty-seven TPB and exercise studies from the Symons Downs and Hausenblas

(2002) meta-analysis were reviewed to see if they met the inclusion criteria of having an

elicitation study conducted before the main TPB study. Based on this inclusion criterion,

38 main TPB studies with elicitation studies were selected for this review. The main TPB

studies reviewed had 11,936 total participants (N range = 30 to 3,719 participants), and

the elicitation studies had 1,488 total participants (N range = 8 to 245 participants).

Review Procedures

The elicitation study characteristics reviewed were participant characteristics

(i.e., the number of participants, type of population, M age or age range, sex,








race/ethnicity, and socioeconomic status), and the number and type of elicited behavioral,

normative, and control beliefs. The main study characteristics reviewed were year,

publication format, participant characteristics (i.e., the number of participants, type of

population, M age or age range, sex, race/ethnicity, and socioeconomic status), and type

of behavior (i.e., exercise, running, walking).

Data Analysis

Following the procedures of previous researchers (i.e., Creswell, 1994; Jackson,

1992; Patton, 1980; Tesch, 1990), a five-step procedure was used to examine the type of

exercise beliefs. First, behavioral, normative, and control belief categories were

established. Second, raw data themes were identified from the reviewed studies. Third,

the raw data themes were organized into higher-order themes based on inductive and

deductive procedures. Specifically, the inductive procedure was used to identify the

higher-order belief themes from the compiled list of raw data themes. The deductive

procedure was used to re-examine the themes to ensure that they made intuitive sense,

and to make certain that all of the raw data themes had been placed into the appropriate

higher-order themes. Fourth, a reliability check of the raw data and higher-order themes

was performed by a TPB expert. Finally, the most salient exercise beliefs were identified

(e.g., the 5 to 10 most common beliefs; Ajzen & Fishbein, 1980; Godin & Shephard,

1990). In addition, I coded the following information: a) frequency of beliefs; b) studies

that examined exercise beliefs but failed to describe them in detail; and c) studies that did

not examine behavioral, normative, or control beliefs. A detailed list of the studies

included in this review are located in Table 2.1.









Table 2.1
Elicitation and Main Theory of Planned Behavior Study Sample Characteristics. and Number and Types of Elicitation Beliefs

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Ajzen & Driver N= 27 undergraduate
(1991) male and female
students (M age=
N.A.), SES =N.A.,
race/ethnicity = N.A.

Backman N = 25 male and female
(1999)' adolescents (age range
= 14-19 years, M age=
N.A.), SES=N.A.,
race/ethnicity =
Hispanic, Caucasian,
and African American


Bergen N= 14 male and 11
(1996)' female chronic pain
patients (M age= 41.6
years), SES = lower to
middle class,
race/ethnicity=
Caucasian, African
American, and Hispanic

Blissmer N = 40 male and female
(1997)' undergraduate students
(M age= N.A.), SES=
N.A., race/ethnicity=
Caucasian


N = 43 male and 103 female
undergraduate students (M
age= 20.1 years), SES=
middle to upper class.
race/ethnicity = N.A.

N= 338 male and 426
female adolescents (age
range= 14-19 years, M age
=N.A), SES= N.A.,
race/ethnicity = Hispanic
(35.7%6), Caucasian (28.6%),
and African American
(14.2%)

N = 51 male and 39 female
chronic pain patients (M age
= 45.6 years), SES = lower
to middle class,
race/ethnicity = Caucasian
(68.9%) and African
American (27.8%)


N N.A. = N.A.
BB were elicited but not described NB were elicited but not
described


N=8
Stay in shape, feel healthy and good
about self, controls weight and diet,
increases energy, athletic
performance, experience pain and
soreness, tired


N=6
Parents, siblings, friends,
coach, teacher


N=7 N=5
BB were elicited but not described NB were elicited but not
described


N = 81 male and 92 female not elicited
undergraduate students (age
range= 18-24 years, M age
= 19.8), SES= N.A.,
racelethnicity= Caucasian
(88%)


not elicited


N =N.A.
CB were elicited but not
described



N=6
Lacking time, money,
motivation, support
encouragement, exercise
knowledge, and access to
exercise equipment or school
physical activity programs


N=8
CB were elicited but not
described


N=7
Perceived barriers = lacking
time, motivation, and energy,
facility too far away and too
crowded, no exercise partner,
other commitments, poor
weather









Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Blue (1996)' N= 21 male and female
worksite employees (M
age = N.A.), SES=
N.A., race/ethnicity=
Caucasian




Bozionelos & N = 20 undergraduate
Bennett (1999) male and female
students (M age =
N.A.), SES=N.A.,
race/ethnicity = N.A.

Brenes, Strube, N= 35 male and female
& Storandt older adults (M age =
(1998) 71.2 years), SES=
N.A., race/ethnicity =
Caucasian (86.0%) and
African American
(3.0%)

Courneya N = 30 male and female
(1995) older adults (age range
= 60 years and older, M
age =N.A.), SES=
lower-middle class,
race/ethnicity= N.A.


Courneya & N= 24 male and female
Friedenreich cancer patients (M age
(1997) =N.A.), SES = middle
class, race/ethnicity=
N.A.


N= 344 male and 109
female worksite employees
(M age = 43.2 years), SES =
N.A.. race/ethnicity
Caucasian (94.5%)




N = 58 male and 56 female
undergraduate students (M
age = 22.0 years), SES =
N.A., race/ethnicity = N.A.


N = 12 male and 93 female
older adults (M age = 68.3
years), SES=N.A.,
race/ethnicity = Caucasian
(66.0%) and African
American (31.1%)


N = 288 male and female
older adults (63% female, M
age = 71.5 years), SES
lower-middle class,
race/ethnicity = N.A.



N = 69 male and 41 female
cancer patients (M age =
60.9 years), SES = middle
class, race/ethnicity= N.A.


N=12
Improves health, feel better, controls
weight, improves muscle tone,
increases energy, promotes
relaxation, increases risk of injury,
illness, and sore muscles, too tired,
too time consuming, interferes with
family and other commitments

N= N.A.
BB were elicited but not described




N=7
Controls weight, feel better,
increases flexibility, improves
muscle tone, energy, health, and
cardiovascular system



N=7
Improves muscular strength and
tone, improves mental health, feel
better, increases energy level,
muscle strength, and tone, lose
weight, provides opportunity to
socialize

N=8
Get mind off cancer treatment, feel
better, improves well-being,
maintain normal lifestyle, cope with
stress, gain control over life. recover
from surgery, controls weight


N=7
Spouse or girl/boyfriend,
other family members,
coworkers, boss, friends,
physician, nurse




N= N.A.
NB were elicited but not
described



N=4
cp.-u-c ..r q.jl h...fnT .'.J
..h.lI e. tl.n J.]
physician


Not elicited


N=5
Spouse or girl/boyfriend,
other family members,
friends, physician, other
people with cancer


N=7
Having an exercise partner.
fun and enjoyable,
convenient, had a reminder,
nice weather, inexpensive,
lacking time



N = N.A.
CB were elicited but not
described



N=4
Experiencing illness or
health problems, lacking
time, energy, and motivation




N=7
Experiencing pain or health
problems, other
commitments, feeling lazy or
unmotivated, bad weather,
too expensive, lacking access
to facilities

N=6
Experiencing illness, nausea,
fatigue, tiredness, pain, and
soreness, no counseling for
exercise, no time and support










Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Coureya & N= 24 female breast
Friedenreich cancer patients (age range
(1999) = less than 70 years, M
age = N.A.), SES =
middle -upper class,
race/ethnicity = N.A.

Cowell N = 26 female
(1996)' undergraduate students
(age range = 20-43 years,
M age= 30.9 years), SES
= N.A., race/ethnicity=
Caucasian only

Daltroy & N= 28 male and female
Godin spouses of cardiac
(1989a) patients (M age = N.A.),
SES = N.A.,
race/ethnicity = N.A.


Dawson,
Brawley,
& Maddux
(2000)


N = N.A. male and
female community adults
(M age = NA.), SES =
N.A., race/ethnicity=
N.A.


Deyo (1984) N = N.A. fitness class
participants (sex = N.A.,
M age = N.A.), SES
N.A., race/ethnicity=
N.A.


N = 164 female breast cancer
patients (M age = 53.0
years), SES = middle- upper
class, race/ethnicity = N.A.



N =199 female
undergraduate students (age
range= 20-45 years, M age
= 29.9 years), SES = N.A.,
race/ethnicity= Caucasian
only

N= 13 male and 121 female
spouses of cardiac patients
(M age = 53.5 years), SES =
N.A., race/ethnicity = N.A.


N = 20 male and 96 female
community adults (M age =
27.0 years), SES = N.A.,
race/ethnicity = N.A.


N = 187 fitness class
participants (68.4% female,
M age = 34.8 years); SES =
middle class; race/ethnicity =
N.A.


N=8
Get mind off cancer treatment, feel
better, improves well-being,
maintain normal lifestyle, cope with
stress, gain control over life, recover
from surgery, weight loss

N=3
Improve muscle tone and strength,
control weight, improves
cardiovascular fitness



N=5
hI r uise,- C..rT .,.o Y r h.. l.;,
.,ulj><,k ..r. Ilc ..T,- r,-,\,: r ,L.-lrt.
inconvenient for spouse, changes
mealtime

Not elicited





N N.A.
BB were elicited but not described


N=5
Spouse or girl/boyfriend,
other family members,
friends, physician, other
people with cancer


N=4
Spouse or girl/boyfriend,
other family members,
physician, athletes


Not elicited





Not elicited


N=N.A.
NB were elicited but not
described


N=7
Experiencing illness, nausea,
fatigue, tiredness, pain, and
soreness, had to work, no
counseling for exercise, no
time and support

N=3
Experiencing injury, not
enough time, feeling lazy


Not elicited


N=N.A.
CB were elicited but not
fully described


Not elicited









Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Doyle-Baker N= 10 patients with
(2000)' fibromyalgia (sex =
N.A., M age = N.A.).
SES N.A.,
race/ethnicity= N.A.


Dzewaltowski N= 55 male and female
(1989) undergraduate students
(M age = N.A.), SES=
N.A., race/ethnicity=
N.A.

Godin, Cox, & N = 55 male and female
Shephard adults (M age = N.A.);
(1983) SES = N.A.;
race/ethnicity = N.A.


Godin,
Deshamais.
Valois, Lepage,
Jobin, & Bradet
(1994)
(Sample I)

Godin,
Desharnais,
Valois, Lepage,
Jobin, & Bradet
(1994)
(Sample 2)


N =51 male and female
community adults, SES
= N.A., race/ethnicity=
N.A.



N = 45 male and female
cardiovascular disease
patients, SES= N.A.,
race/ethnicity= N.A.


N= 4 male and 137 female
patients with fibromyalgia
(M age = 48.6 years); SES =
N.A.; Race/Ethnicity =
Anglo Canadian (57.4%),
European (16.3%), and
Caucasian (12.8%)
N= 136 male and 192
female undergraduate
students (M age = N.A.),
SES = N.A., race/ethnicity=
N.A.

N = 172 male and female
adults (M age = 31.1 years),
SES =N.A.. race/ethnicity
N.A.

N = 130 male and 219
female community adults (M
age = 38.1 years), SES =
N.A., race/ethnicity= N.A.


N= 10
Reduces disease symptoms, more
positive life outlook, improves self-
confidence, body image, and sleep,
perform routine tasks more easily,
increases energy for family, return
to work, decreases stress, too tired
N=13
BB were elicited but not described




N=11
BB were elicited but not described


Not elicited


N= 137 male and 25 female Not elicited
cardiovascular disease
patients (M age= 56.6
years), SES= N.A.,
race/ethnicity = N.A.


N=7
Spouse or girl/boyfriend,
other family members,
physician, physical
therapist, other health care
workers, boss, minister or
church official
N =N.A.
NB were elicited but not
described



N=3
NB were elicited but not
described


Not elicited


Not elicited


N=7
Lacking time, money, fitness
counseling, transportation,
and exercise knowledge,
having previous exercise
experience

Not elicited


Not elicited


N=5
Perceived barriers = lacking
access to facilities, money,
time, and an exercise partner,
health problems


N= 10
Perceived barriers = lacking
time, access to facility, and
an exercise partner, age,
experiencing heart pain, fear
of another heart attack,
psychological difficulties
adapting to life after heart
problems, physician's
counter-indication, laziness










Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Godin,
Deshamais,
Valois, Lepage,
Jobin, & Bradet
(1994)
(Sample 3)


N = 47 postpartum
females (M age=
N.A.), SES= N.A.,
race/ethnicity = N.A.


Hagger, Cale, N= N.A. male and
& Almond female primary school
(1997) children (age range = 9-
11 years, M age =
N.A.), SES= middle
class, race/ethnicity=
N.A.

Helm (1987)' N = 18 male and female
older adults (age range
= 60-94, M age= N.A.),
SES= retired,
race/ethnicity =
Caucasian


Kerner & N = N.A. fitness center
Grossman personnel (sex = N.A.,
(1998) age range= 20-67
years, M age= N.A.),
SES = middle-upper
class, race/ethnicity=
N.A.


N = 139 pregnant females Not elicited
(M age = 27.3 years); SES =
N.A., race/ethnicity =N.A.


N= 25 male and 19 female
primary school children (age
range =9-11 years, M age =
N.A), SES = middle class,
race/ethnicity= N.A.



N= 89 male and 165 female
older adults (age range= 60-
94, M age = 74 years), SES
= retired, race/ethnicity=
Caucasian



N = 50 male and 23 female
fitness center personnel (age
range = 20-67 years, M age
= 44.7 years), SES = middle-
upper class, race/ethnicity=
N.A.


N=6
Feel healthy and better, fun and
enjoyment, make friends, increases
risk of injury, too much effort




N=10
Increases flexibility, feel better and
more healthy, improves circulation,
alertness, and mental health,
controls weight, aggravates physical
condition, overexertion, time
consuming, messy

N =N.A.
BB were elicited but not described


Not elicited








N=5
Parents, grandparents,
other family members,
friends, teachers




N=9
Spouse or girl/boyfriend,
other family members
(i.e., sister, brother,
daughter, son, grandchild,
spouse of child), friends,
physician

N= N.A.
NB were elicited but not
described


N=6
Perceived barriers = lactation
constraints, lacking time and
support from husband,
experiencing physical health
problems after birth, baby's
physical health problems.
psychological problems
adapting to life after birth
Not elicited


Not elicited







Not elicited









Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Kimiecik N = 30 worksite
(1992) employees (sex = N.A.,
1 .,C, = N\ SIS=A
T..lJJlL-.^p; I .I
race/ethnicity= N.A.

Legg (1987) N = 73 male and 63
female undergraduate
students (age range =
18-54 years, M age =
N.A.), SES= N.A.,
race/ethnicity = N.A.

Michels & N= N.A. male and
Kugler (1998) female older adults (age
range = 65-70 years, M
age= NA.), SES=
upper middle class,
race/ethnicity = N.A.

Mummery, N= N.A. children (sex
Spence, & = N.A., age range = 8-
Hudec (2000) 16 years, M age=
N.A.), SES =N.A.,
race/ethnicity= N.A.





Norman & N = 18 male and female
Smith (1995) undergraduate students
(M age= N.A.), SES=
N.A., race/ethnicity=
N.A.


N= 176 male and 154
female worksite employees
(M age =39.1 years), SES=
middle-upper class,
race/ethnicity = N.A.

N = 15 male and 15 female
undergraduate students (age
range = 18-54 years, M age
= N.A.), SES= N.A..
race/ethnicity= N.A.


N = N.A. male and female
older adults (age range = 65-
70 years, M age = N.A.),
SES = upper middle class.
race/ethnicity = Caucasian
(90.8%)

N = 746 male and female
adolescents: N = 63 3d
graders (M age = 8.2 years),
N = 139 5 graders (M age=
10.3 years), N= 191 8
graders (M age = 13.9
years), N= 184 11h graders
(M age =16.4 years), SES
N.A., race/ethnicity= N.A.

N = 83 male and female
undergraduate students (M
age= N.A.), SES =N.A..
race/ethnicity = N.A.


N=6
BB were elicited but not described




N=15
rr-,~ rg.-.cil;k .,n e ,,il r'.i .ei
cardiovascular fitness, meet new
people, increases energy, controls
weight, time, relieves stress, tired,
sore muscles, expensive
N=4
Improves health, increases energy
level, controls weight, decreases
joint stiffness, causes pain



N =N.A.
BB were elicited but not described








N=7
BB were elicited but not fully
described (e.g., improves agility and
suppleness)


N=3 N=7
NB were elicited but not CB were elicited but not
described described


N=4
Spouse or girl/boyfriend,
parents, physician, friends




N=4
Spouse or girl/boyfriend,
friends, physician, media




N=N.A.
NB were elicited but not
described







N=4
Other family members,
friends, media, people
who exercise regularly


Not elicited






N=N.A.
CB were elicited but not
described




N= N.A.
CB were elicited but not
described







N=7
Lacking time, other
commitments, feeling tired
and lazy, too much effort,
too far from facilities,
experiencing pain and
soreness








Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Pender & N= 100 community
Pender(1986) adults (sex = N.A.. age
range = 18 years and
older, M age = N.A.),
SES = N.A.,
race/ethnicity = N.A.

Rahilly (1994)' N= I1 females (age
range = 21-50 years, M
age= N.A.), SES =
N.A., race/ethnicity=
N.A.

Riddle (1980) N = 40 male and female
exercisers (age range =
30 years and older, M
age =N.A.), SES =
N.A. race/ethnicity=
N.A.

Schlapman N= 22 male and 44
(1994)' female older adults (M
age = 44.6 years), SES
= N.A., race/ethnicity=
N.A.





Schmelling N= 40 male and female
(1985) university faculty and
staff(age range = 30-55
years, M age = NA.),
SES= N.A.,
race/ethnicity = N.A.


N= 377 male and female
community adults; 60%
female (M age = 38.0 years),
SES = middle class,
race/ethnicity = Caucasian


N = 88 females (age range =
21-50 years, M age = 34.7
years), SES= N.A.,
race/ethnicity = N.A.


N = 198 male and 98 female
exercisers (age range = 30
years and older, M age
N.A.), SES = N.A.,
race/ethnicity = N.A.


N= 135 male and 296
female older adults (M age =
62.0 years), SES = retired,
race/ethnicity = Caucasian






N= 135 male and female
university faculty and staff
(58.5% male, age range =
30-55 years, M age = N.A.),
SES =N.A., race/ethnicity=
N.A.


N= N.A.
BB were elicited but not fully
described (e.g., controls weight,
cope with stress)



N= N.A.
BB were elicited but not described




N=19
BB were elicited but not described





N=9
Improves physical and mental
health/fitness, feels good, lowers
blood pressure, controls weight,
socializing, good exercise, wears on
bones and joints




N=17
Increases energy, stronger heart and
lungs, improves health, strength,
body appearance, appetite, and
alertness, feel better about self, more
relaxed and structured day, controls
weight, time consuming, aggravates
health condition, muscle aches, and
injuries, too tired, daily interference


N=6
Spouse or girl/boyfriend,
children, parents or close
older relative, friends,
coworkers, physician


N= N.A.
NB were elicited but not
described



N=7
NB were elicited but not
described




N=6
Spouse or girl/boyfriend,
children, parents, friends,
physician, coworkers






N=4
Spouse or girl/boyfriend,
other family members,
friends, boss, coworkers


Not elicited






Not elicited





Not elicited


N=9
Having a walking partner,
mall meetings and programs,
contests and incentives,
lacking time, motivation, and
access to a facility to walk
indoors, experiencing illness
and injury, other
commitments

Not elicited









Table 2.1 Continued

Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics


Sheeran & N =N.A. undergraduate
Orbell (2000) students (sex = N.A., M
age= N.A), SES=
N.A., race/ethnicity=
N.A.
Smith & Biddle N= 7 male and 7
(1999) Study 1 female health club
members (age range=
18 years and older, M
age = N.A.), SES =
N.A., race/ethnicity=
N.A

Smith & Biddle N=4 male and 4
(1999) Study 2 female worksite
employees (M age =
N.A.), SES =N.A.,
race/ethnicity = N.A.

Terry& N= 25 male and 31
O'Leary (1995) female undergraduate
students (M age = 20.3
years), SES N.A.,
race/ethnicity = N.A.

Theodorakis N= 120 female fitness
(1994) class participants (age
range = 18-45 years, M
age= N.A.), SES =
N.A., race/ethnicity=
N.A.


N = 163 undergraduate
students (sex = N.A., M age
= N.A.), SES= N.A.,
race/ethnicity = N.A.

N= 44 male and 51 female
health club members (M age
= 34.0 years), SES = middle
class, race/ethnicity=
Caucasian



N = 74 male and 67 female
worksite employees (M age
= 36.0 years), SES = middle
class, race/ethnicity=
Caucasian

N= 73 male and 73 female
undergraduate students (M
age = 20.2 years), SES =
N.A., race/ethnicity= N.A.


N= 395 female fitness class
participants (age range =18-
45 years, M age = 29.3
years), SES = N.A,
race/ethnicity = N.A.


N =N.A.
BB were elicited but not described



N= N.A.
BB were elicited but not described


N= N.A.
BB were elicited but not described




N=12
BB were elicited but not fully
described (e.g., tired, improves
physical fitness)


N=13
BB were elicited but not described


N =N.A.
NB were elicited but not
described


N=N.A.
NB were elicited but not
described


N=N.A.
NB were elicited but not
described



N=3
Spouse or girl/boyfriend,
parents, friends



N=5
Spouse or boyfriend, other
family members, friends,
exercise leader


N=N.A.
CB were elicited but not
described


Not elicited


Not elicited


N= N.A.
CB were elicited but not
described



N=9
CB were elicited but not
described


Note. = thesis or dissertation; N = number; M = mean; SES = socioeconomic status; N.A. = not available.








Results

Elicitation Study Characteristics

Table 2.2 displays a summary of the elicitation and main study characteristics.

The elicitation study participants ranged in age from 20.1 to 71.2 years (M age = 39.1

years, SD = 16.7). Most of the studies examined males and females (71.1%). The

participants were undergraduates (23.7%), worksite employees (13.2%), older adults

(13.2%), community adults (10.5%), children (10.5%), exercise class attendants (10.5%),

and patients (e.g., cardiac, pain, cancer, 10.5%). The majority of the studies did not report

the participant's race/ethnicity (81.6%) or socioeconomic status (68.4%); however, in the

studies that did report these characteristics, the majority were Caucasian middle-to-upper

class adults.

Main TPB Study Characteristics

Most of the studies were published (71.1%) and were conducted in the 1990's

(65.8%), followed by the 1980's (23.7%), and the 2000's (10.5%). The majority of the

studies included male and female participants (86.8%). The participants were

undergraduates (23.7%), worksite employees (13.2%), older adults (13.2%), community

adults (10.5%), children (10.5%), exercise class attendants (10.5%), and patients (e.g.,

cardiac, pain, cancer, 10.5%). Most of the studies did not report the participant's

race/ethnicity (65.8%) or socioeconomic status (60.5%); however, in the studies that did

report these characteristics, Caucasian middle-to-upper class adults were the most

frequently studied.








Table 2.2
The Number (N) and Percent (%) of Main Theory of Planned Behavior (TPB) and
Elicitation Study Characteristics

Characteristic N %

Main TPB Study Characteristics
Publication year
1980's 9 23.7
1990's 25 65.8
2000's 4 10.5
Publication format
Published 27 71.1
Unpublished 11 28.9
Dissertation 9 81.8
Thesis 2 18.2
Participants
Sex
Male and female 33 86.8
Female only 4 10.5
Not available 1 2.6
Race/Ethnicity
Caucasian 9 23.7
Caucasian and African American 2 5.3
Caucasian, Hispanic, and African American 1 2.6
Caucasian, Anglo-Canadian, and European 1 2.6
Not available 25 65.8
Population
Undergraduates 9 23.7
Worksite employees 5 13.2
Older adults 5 13.2
Community adults 4 10.5
Children 4 10.5
Exercise class attendants 4 10.5
Patients (e.g., cardiac, pain, cancer) 4 10.5
Spouses of cardiac patients 1 2.6
Combination (cardiac patients, community adults 1 2.6
pregnant women)
Not available 1 2.6
Socioeconomic status
Middle class 6 15.8
Middle class-upper class 5 13.2
Lower class-middle class 4 10.5
Not available 23 60.5








Table 2.2 Continued

Characteristic N %

Type of behavior
Exercise 26 68.4
Physical or leisure activities 8 21.1
Walking 2 5.3
Tonercise 1 2.6
Habit 1 2.6
Elicitation study characteristics
Participants
Sex
Male and female 27 71.1
Female only 4 10.5
Not available 7 18.4
Race/Ethnicity
Caucasian 4 10.5
Caucasian, Hispanic, and African American 2 5.3
Caucasian and African American 1 2.6
Not available 31 81.6
Population
Undergraduates 9 23.7
Worksite employees 5 13.2
Older adults 5 13.2
Community adults 4 10.5
Children 4 10.5
Exercise class attendants 4 10.5
Patients (e.g., cardiac, pain, cancer) 4 10.5
Spouses of cardiac patients 1 2.6
Combination (cardiac patients, community adults, 1 2.6
pregnant women)
Not available 1 2.6
Socioeconomic status
Middle class to upper class 5 13.2
Middle class 4 10.5
Lower class to middle class 2 5.3
Not available 27 71.1

Note. aMay not add up to 100% because more than one construct was measured per
study.








Elicitation Study Method Characteristics

Correspondence between the elicitation and main TPB study participant

characteristics could not be determined for the majority of studies (94.7%, n = 36)

because not enough information was provided regarding the elicitation studies. For

example, Doyle-Baker (2000) provided information on the main TPB study participants'

sex, M age, and race/ethnicity; however, these characteristics were not provided for the

elicitation study participants. Similarly, the majority of elicitation studies (60.5%, n = 23)

did not provide enough information to determine the measures and procedures used to

elicit the behavioral, normative, and control beliefs. For example, Mummery, Spence, &

Hudec (2000) stated that they elicited participants' behavioral, normative, and control

beliefs; however, no information was provided as to what these salient beliefs were or

how they were obtained.

Elicitation Study Belief Characteristics

Behavioral beliefs. The majority of the elicitation studies (92.1%) examined

behavioral beliefs, and the average number of beliefs reported per study was 10 (see

Table 2.3). The most salient behavioral advantages of exercise were: a) feeling healthy,

better, or good about self (93.3%); b) controls weight and diet (86.7%); c) increases

physical fitness (80.0%); d) improves daily functioning (73.3%); e) increases energy

(66.7%); f) improves mental health (60.0%); g) relieves stress and promotes relaxation

(53.3%); and h) improves cardiovascular system (53.3%). The most common behavioral

disadvantages were: a) experiencing pain, injury, and soreness; 53.3%); b) tired (40%); c)

inconvenience (40.0%); and d) lacking time (33.3%)'.


'Percents add up to greater than 100% because some people reported several beliefs about
exercise behavior.








Table 2.3
The Number (N) and Percent (%) of Elicitation Study Behavioral, Normative, and
Control Beliefs

Beliefs Higher-order Theme Raw Data Theme N %'

Behavioral Improves physical Feeling healthy, better, 14 93.3
Beliefs and psychological or good about self
(Advantages) health
Controls weight and diet 13 86.7

Increases physical 12 80.0
fitness (e.g., muscular
strength, physical fitness,
toning, flexibility,
and reflexes)

Improves daily 11 73.3
functioning (e.g., get
mind off of cancer
treatment, maintain a
normal lifestyle, gain
control over life,
recover from surgery,
return to work, perform
tasks with more ease,
more daily structure)

Increases energy 10 66.7

Improves mental health 9 60.0
(e.g., better outlook on
life, increases confidence,
concentration, and
alertness)

Relieves stress and 8 53.3
promotes relaxation
(e.g., relieves tension
and joint stiffness, coping
with stress, relax)

Improves cardiovascular 8 53.3
system (e.g., increases
circulation, agility, stronger
heart and lungs, suppleness
decreases blood pressure)








Table 2.3 Continue

Beliefs


Behavioral
Beliefs
(Disadvantages)


Higher-order Theme Raw Data Theme

Improves health
and well-being

Improves self and
body image

Stay in shape

Improves sleep

Increases appetite

Decreases disease
symptoms

Socialize Make friends

Meet new people

Opportunity to socialize

Physical activity Athletic performance

Good exercise

Fun Fun and enjoyment

Physical and Experiencing pain,
psychological soreness, or injury
health issues
Tired

Aggravates physical
Condition

Wears on bones
and joints


N %a

5 33.3


3 20.0


2 13.3

1 6.7

1 6.7

1 6.7


2 13.3

1 6.7

1 6.7

1 6.7

1 6.7

1 6.7

8 53.3


6 40.0

2 13.3


1 6.7


ed








Table 2.3 Continue

Beliefs


Higher-order Theme Raw Data Theme

Inconvenience Daily inconveniences
(e.g., other commitments,
interferes with daily
routine and family, messy,
inconvenient for spouse
Lacking time Lacking time, no time


Expensive


Expensive, no money


Normative
Beliefs


Friends 16 88.9

Spouse or girl/boyfriend 15 83.3

Family members 11 61.1
not specified

Parents 7 46.7

Children 6 33.3

Siblings 2 11.1

Grandparents 1 5.6

Physician 12 66.7

Nurse 1 5.6

Physical therapist 1 5.6

Heathcare workers 1 5.6
not specified

Boss 4 22.2

Coworkers 4 22.2

Teacher 2 11.1

Coach 1 5.6


,d


Family and
friends














Healthcare
professionals







School and
worksite
personnel


~


N %"

6 40.0




5 33.3

1 6.7








Table 2.3 Continue

Beliefs


Control
Beliefsd
(Facilitating
Factors)


d


Higher-order Theme Raw Data Theme N

Miscellaneous Other exercisers 3

Other people with cancer 2

Media 2

Minister or church official 1

Social support Having an exercise partner 2


Getting encouragement 2
and motivation

Getting a written reminder 1

Meetings and programs 1

Contests and incentives 1

Previous exercise 1
experience

Fun and enjoyment 1

Convenience 1

Good weather 1

Inexpensive 1

Experiencing pain, injury, 13
and illness

Lacking motivation 6
or feeling lazy

Tiredness and fatigue 5

Fear (e.g., having another 1
heart attack)


Miscellaneous











Control Physical and
Beliefs psychological
(Obstructing health issues
Factors)


1 6.7


%"

16.7

11.1

11.1

5.6

13.3

13.3


6.7

6.7

6.7

6.7


6.7

6.7

6.7

6.7

86.7


40.0


33.3

6.7








Table 2.3 Continued

Beliefs Higher-order Theme Raw Data Theme N %a

Time Lacking time, no time 13 86.7

Inconvenience Lacking access to exercise 5 33.3
facilities and equipment

Other commitments 5 33.3

Bad weather 2 13.3

Facility too crowded 1 6.7

Facility too far away 1 6.7

Lacking transportation 1 6.7

Baby's health problems 1 6.7

Lactation constraints 1 6.7

Miscellaneous No exercise partner 6 40.0

Lacking exercise 5 33.3
knowledge or exercise
counseling

Lacking money or 4 26.7
too expensive

Note. N = 38 studies reviewed; aPercent may not add up to 100% because multiple beliefs
were reported per study; bn = 15 studies elicited and described behavioral beliefs, n = 20
studies elicited behavioral beliefs but did not describe in detail, = 3 studies did not elicit
behavioral beliefs; en = 18 studies elicited and described normative beliefs, n = 15 studies
elicited normative beliefs but did not describe in detail, n = 5 studies did not elicit
normative beliefs; dn = 12 studies elicited and described control beliefs (Godin et al.,
1994 elicited control beliefs separately for three different populations; these beliefs were
coded as separately, and the percent were calculated by dividing the belief n by 15 rather
than 12), n = 10 studies elicited control beliefs but did not describe in detail, n = 16
studies did not elicit control beliefs.








Normative beliefs. The majority of the elicitation studies examined normative

beliefs (86.8%), and the average number of beliefs reported per study was 5. The

normative beliefs were: a) friends (88.9%), b) spouse or girl/boyfriend (83.3%), c)

physician (66.7%), d) family members not specified (61.1%), e) parents (46.7%), f)

children (33.3%), g) boss (22.2%), and h) coworkers (22.2%).

Control beliefs. Slightly more than half (57.9%) of the studies examined control

beliefs, and the average number of beliefs per study reported was 7. The most frequently

reported control belief facilitating exercise was social support (e.g., having an exercise

partner, getting encouragement and motivation; 46.7%). The most common control

beliefs obstructing exercise were: a) experiencing pain, injury, and illness (86.7%); b)

lacking time (86.7%); c) lacking motivation or feeling lazy (40.0%); d) no exercise

partner (40.0%0); e) tiredness and fatigue (33.3%); f) lacking access to exercise facilities

and equipment (33.3%); and g) lacking exercise knowledge or exercise counseling

(33.3%).

Discussion

The primary purpose of this study was to identify the salient beliefs reported in

elicitation studies. The secondary purpose of this study was to compare the characteristics

of the elicitation and main TPB studies to determine if there was correspondence between

the participants, methods, and procedures. Several findings warrant discussion. First,

consistent with previous researchers' conclusions (e.g., Carron et al., 2003), the most

salient behavioral advantage of exercise was that it improves people's physical and

psychological health (e.g., improves physical fitness, feeling better about self). In

addition, the most common behavioral disadvantages of exercise were:








* Physical and psychological health issues (e.g., experiencing pain, soreness, and
injury, and invoking tiredness).

* Inconvenience (e.g., interferes with daily routine, inconvenient for spouse).

* Lacking time.

These findings indicate that people have a variety of positive and negative behavioral

beliefs regarding exercise, and elicitation studies help researchers determine which of

these beliefs are the most salient for their population of interest.

Moreover, because researchers have found that people's attitude most strongly

predict their exercise intentions (i.e., Symons Downs & Hausenblas, 2002), it is

important to consider a population's behavioral advantages and disadvantages for

exercise. For example, while healthy populations may believe that exercising will

improve their health, some special populations (e.g., cardiovascular disease and chronic

pain patients) may believe that exercising will debilitate their health. Thus, identifying

how people feel about exercise is an important step in determining the factors that may

facilitate or inhibit their exercise behavior. In addition, understanding people's salient

behavioral advantages and disadvantages of exercise can assist researchers with tailoring

their exercise interventions to meet the specific thoughts, needs, and beliefs of

populations that are at risk for sedentary behavior (e.g., elderly, overweight, pregnant;

Carron et al., 2003).

Second, consistent with the findings of Carron et al. (2003), the most frequently

reported normative influences were friends and family. Specifically, it was found that for

exercise behavior, people value the opinions and wishes of their friends and spouse or

girl/boyfriend the most, followed by the expectations of their parents, children, and

siblings. In some studies, however, the normative influence of family members was not








completely described (e.g., Blue, 1996; Courneya & Friedenreich, 1997, 1999). That is, a

"family member" was reported as a normative influence, however, the researchers did not

identify who this family member was (e.g., a parent, spouse, brother). Moreover,

identifying which important others have the strongest impact can be helpful for

researchers who are designing and implementing exercise interventions. For example,

social support plays an important role in exercise adherence, and knowing who provides a

person with the most social support may help to increase his or her exercise participation

and adherence (Courneya & McAuley, 1995; Courneya, Plotnikoff, Hotz, & Birkett,

2000). Thus, researchers are encouraged to be more specific when reporting the influence

of significant others on people's exercise intention and behavior.

Third, consistent with previous researchers' conclusions (Carron et al., 2003),

another frequently reported normative influence was a person's physician. That is, people

consider their physician to be an important authority regarding their exercise behavior.

Thus, physicians and other healthcare workers may play a valuable role in promoting

exercise behavior and adherence with their patients. In addition, it is important to note

that while 70% of adults are seen by a healthcare provider at least one time per year,

some special populations (e.g., cancer patients, the elderly, pregnant women) are in more

frequent contact with their primary caretaker (Logsdon, Lazaro, & Meier, 1989). Thus,

because there is a need for research examining populations that are at risk for sedentary

behavior (e.g., cancer, patients, the elderly, pregnant women; USDHHS, 2000) and

because access to these populations can be challenging (e.g., getting diseased, elderly,

and pregnant populations to volunteer for studies), researchers studying the determinants








of exercise behavior in special populations may consider collaborating with physicians

and other healthcare professionals when conducting their studies (Koniak-Griffin, 1994).

Fourth, while Carron et al. (2003) stated that the most common control beliefs

inhibiting exercise participation were a lack of time, energy, and motivation, I found that

the most common control beliefs obstructing exercise were:

* Physical and psychological issues (e.g., experiencing pain, injury, and illness, lacking
motivation, tiredness and fatigue).

* Lacking time.

* Inconvenience (e.g., lacking access to exercise facilities or equipment, other
commitments).

* No exercise partner.

One explanation for this discrepancy is that I reviewed studies that included special

populations, while Carron et al.'s conclusions were based on healthy populations. For

example, in this review, different salient beliefs emerged for healthy populations (i.e.,

lacking time and motivation) compared to special populations such as cancer patients

(i.e., recovering from surgery, experiencing nausea; Courneya & Friedenreich, 1997,

1999), older adults (i.e., experiencing illness, injury, or health problems; Brenes et al.,

1998), and postpartum women (i.e., experiencing physical health problems after birth;

Godin et al., 1994). These findings demonstrate the importance of conducting elicitation

studies, and they emphasize the need to examine the determinants of exercise in special

populations. That is, what obstructs exercise participation for a person during cancer

treatment may be different than what inhibits exercise participation for a mother with a

newborn baby.








In addition, the most salient control belief facilitating exercise behavior was

receiving social support from other people, including having an exercise partner and

receiving encouragement and motivation. Consistent with the findings for normative

beliefs, these findings indicate that people's exercise behavior can be positively

influenced by other people, and they illustrate that significant others may assist

researchers with increasing exercise behavior in populations that are at risk for

sedentariness. Moreover, identifying what people perceive as facilitating and obstructing

factors of exercise participation may help researchers to emphasize the advantages of

exercise (e.g., improves self-esteem and increases energy), as well as assist people with

overcoming their perceived barriers (e.g., exercise may cause injury). These are

important facets of increasing people's exercise motivation, and ultimately, their exercise

adherence (Lynch et al., 2000). Thus, the findings from this review may aid researchers

in: understanding the determinants of exercise behavior, developing exercise

interventions to increase exercise participation, and promoting exercise adherence.

Fifth, because of the lack of information provided for elicitation studies, I was

unable to examine the elicitation study methods (i.e., participants, measures, and

procedures). More specifically, 95% of the studies did not report sufficient information

for the participant characteristics, and 61% of the studies did not report adequate details

to determine the measures and procedures used to elicit the beliefs. For example, only

two of the studies reviewed (i.e., Bergen, 1996; Helm, 1987) provided enough detail

regarding the elicitation and main TPB study participants (i.e., population type, number

of participants, sex, M age or age range, race/ethnicity, and socioeconomic status) for

correspondence to be determined. Similarly, a limited number of studies (e.g., Ajzen &








Driver, 1991; Courneya & Friedenreich, 1997, 1999; Smith & Biddle, 1999) described

the elicitation study measures and procedures with sufficient detail. This is problematic

for two reasons. First, it is not clear whether the elicitation study participants were similar

to the main TPB study participants. When correspondence cannot be determined, it is

possible that the elicitation study may have been conducted with people who have

different beliefs about exercise than the main TPB study. Second, when the measures and

procedures of an elicitation study are not properly described, researchers are not able to

determine how the beliefs were obtained, and they cannot replicate the measures and

procedures in future studies. Both of these problems can jeopardize the utility of the TPB

in predicting exercise intention and behavior (Ajzen, 1991).

Two limitations of the studies included in this review must be noted. First, when

interpreting the findings regarding the salient behavioral, normative, and control beliefs,

researchers should consider that some of the elicitation studies were conducted with

nonrandom samples (e.g., Brenes et al., 1998; Godin et al., 1994), and samples with a

small number of participants (e.g., n = 8 participants; Smith & Biddle, 1999). Second,

because there was limited information provided for the majority of the elicitation studies,

the salient behavioral, normative, and control beliefs that emerged from this review are

based on the small number of studies that elicited and described these beliefs. Thus, these

findings have limited generalizability.

Moreover, it is important that elicitation study methods are reported with more

detail for researchers to generalize their findings to a variety of populations and replicate

these studies. For example, researchers must present the elicitation study methods and

specify the participants, measures, and procedures for the study to be replicated. Thus,








researchers are encouraged to report more details regarding elicitation studies in an

attempt to improve the predictive utility of the TPB (Ajzen, 1991).

In summary, Ajzen and Fishbein (1980) developed theoretical guidelines for

researchers to direct their studies and improve the predictive utility of the TPB by using

elicitation studies. When researchers adhere to these guidelines, the TPB is more

powerful in predicting exercise intentions and behavior (Symons Downs & Hausenblas,

2002). Thus, it is important for researchers examining the TPB to use the recommended

theoretical guidelines to effectively increase people's physical activity behavior (Carron

et al., 2003; Maddux & DuCharme, 1997). In short, because elicitation studies determine

a population's salient behavioral, normative, and control beliefs which provide the

necessary framework for examining people's attitude, subjective norm, and perceived

behavioral control, researchers are encouraged to:

* Adhere to the TPB guidelines and conduct elicitation studies.

* Obtain correspondence between the elicitation and main TPB study participants.

* Report more details regarding the elicitation study participants (i.e., population type,
M age or age range, sex, race/ethnicity, and socioeconomic status), measures, and
procedures.

This information may assist researchers with planning and implementing programs

designed to increase exercise involvement and improve exercise adherence across all

types of populations (e.g., children, diseased, elderly, economically disadvantaged).

Moreover, this is important considering that the majority of North Americans are low

active or sedentary, which increases their risk for a variety of physical and psychological

diseases (USDHHS, 2000). Thus, understanding people's beliefs about exercising can








assist researchers with strategies that may increase their exercise behavior, change their

lifestyle, and ultimately, improve their physical and psychological health.

Prelude to Chapter 3

This review of TPB and exercise elicitation studies was necessary for two

reasons. First, because few TPB and exercise studies have conducted elicitation studies, it

was important that I could identify the type of behavioral, normative, and control beliefs

that people have reported about exercise. Thus, the best method for me to obtain a more

comprehensive understanding about people's exercise beliefs was to conduct this review

study. Second, the findings from this review provided the framework for the next chapter.

Specifically, understanding the methods that previous researchers have used to obtain

people's exercise beliefs allowed me to effectively design and implement an elicitation

study with a sample of postpartum women. The next chapter (Chapter 3) will:

* Provide the rationale and purpose for conducting an exercise elicitation study with
postpartum women.

* Describe in detail the study methods and results.

* Highlight the important study findings for discussion.














CHAPTER 3
STUDY 2: THE THEORY OF PLANNED BEHAVIOR
AND EXERCISING DURING PREGNANCY AND POSTPARTUM:
AN ELICITATION STUDY

In the past 50 years, many scientific and medical innovations have increased

people's lifespan, including artificial organ transplants, microscopic surgery, and gene

therapy (Eaton, Cordain, & Lindeberg, 2002; Eaton et al., 2002). Despite these advances,

chronic behavioral ailments such as cardiovascular disease, cancer, diabetes, and liver

disease are currently responsible for the greatest mortality among American adults (AHA,

1997; CDC, 1999; NCHS, 1997). While genetics may predispose people to certain

conditions, most chronic diseases are associated with negative behaviors such as

smoking, poor diet, and sedentariness (Mitchell et al., 1999). Thus, people can reduce

their risk of chronic disease by adopting positive lifestyle patterns such as eating a

balanced diet, maintaining a healthy weight, and engaging in regular physical activity

(AHA; CDC; Taylor, 1999; Twisk et al., 2000).

In regard to physical activity, regular exercise contributes positively to

physiological heath and psychological well-being (USDHHS, 1996, 2000). Most U.S.

adults, however, are physically inactive because they are not participating in 30 min of

accumulated moderate to vigorous physical activity on most, if not all, days of the week

(ACSM, 1999, 2000). The people most at risk for a low active or sedentary lifestyle

include special populations such as ethnic minorities, the elderly, women, and people of

low socioeconomic status and education (USDHHS). Promoting physical activity in these








special populations is difficult due to the unique barriers obstructing their participation

that are not found in nonrisk populations. For example, women are faced with several

physical and psychological challenges that can reduce their exercise behavior. For

example, life events unique to women (e.g., menstruation, pregnancy, and menopause)

may place them at greater risk for decreased physical activity compared to men

(USDHHS). Specifically for pregnancy, Zhang and Savitz (1996) conducted a prevalence

study on 9,953 U.S. women and they found that:

* 45% were sedentary before and during pregnancy.

* 13% exercised before pregnancy but stopped after they found out they were pregnant.

* 7% did not exercise before pregnancy but exercised during pregnancy.

* 35% exercised before and during pregnancy.

These findings illustrate that 58% of pregnant women are sedentary, placing them above

the national average (i.e., 30% of U.S. adults are sedentary; USDHHS). Thus, pregnancy

is an important event in women's lives that may promote decreased physical activity.

For many women, exercising during pregnancy is compromised by the

physiological and psychological demands of this time. For instance, pregnancy is

associated with increases in maternal cardiac output, ventilation, oxygen constraints, and

body mass index (Bungum et al., 2000; Carter et al., 2000). In addition, symptoms of

depression, stress, and anxiety can occur during pregnancy (Monk et al., 2000;

Zuckerman, Amaro, Bauchner, & Cabral, 1989). For example, approximately one-third of

women experience depressive symptoms during their pregnancy (Zuckerman et al.).

Moreover, exercising during pregnancy can elevate maternal core temperature, decrease

blood flow to the fetus, and increase a woman's risk of exercise-related injuries (e.g.,








physical changes from gaining weight; Wallace & Engstrom, 1987). Consequently, many

women find these added physical and psychological demands stressful, and thus, they

either decrease or stop exercising during their pregnancy.

Regardless of these concerns, there is a general consensus that most previously

active women can continue to exercise during their pregnancy without risk to either

themselves or their fetus (Bungum et al., 2000; Clapp, 1990; Jackson, Gott, Lye, Knox-

Ritchie, & Clapp, 1995; Lokey, Tran, Wells, Myers, & Tran, 1991; Rice & Fort, 1991).

For example, Lokey et al. meta-analytically reviewed 18 exercise and pregnancy studies,

and they found that exercising during pregnancy was not associated with harmful

physical effects for either the mother or the fetus. Moreover, the ACOG (1994)

recommended that women without obstetric or medical problems exercise moderately

during their pregnancy. Their specific guidelines are that pregnant women should:

* Warm-up before exercise.

* Avoid overexertion (e.g., heart rate should not exceed 140 beats per min, strenuous
exercise not to exceed 15 min).

* Drink plenty of fluids.

* Consume calories in addition to the 300 extra kilocalories required by pregnancy.

* Avoid activities that may cause abdominal trauma.

* Modify or stop activity if uncomfortable.

In addition, some researchers have concluded that exercising during pregnancy is

associated with decreased depression, and improved self-esteem, mood, and body image

(Bungum et al., 2000; Koniak-Griffin, 1994; Walker et al, 1999). For example, Koniak-

Griffin examined the effects of exercise on pregnant women's psychological health, and








she found that women's self-esteem increased and depressive symptoms decreased over a

6-week aerobic exercise program. Moreover, exercising during pregnancy can assist

women with controlling their weight by reducing excessive weight gain (Bungum et al.;

Carter et al., 2000). Considering that weight gain during pregnancy is associated with

negative affective symptoms (e.g., anxiety, depression) during both pregnancy and

postpartum, it is important to examine the effects of exercise as a way to control

excessive weight gain (Carter et al.).

While there is an abundance of studies examining exercise in nonrisk populations,

the research examining physical activity during pregnancy is scant and limited by several

factors. First, the majority of the researchers have focused on the physiological effects of

exercise during pregnancy (i.e., risk to the fetus), and few studies have examined its

psychosocial effects on the mother (e.g., Koniak-Griffin, 1994; Zhang & Savitz, 1996).

Second, due to the difficulty associated with recruiting pregnant participants, many

studies have been conducted with animal versus human subjects (Koniak-Griffin). Third,

many studies including pregnant women have had small samples sizes or inadequate

control groups (Berg, 1999).

Fourth, while physical activity is a valuable treatment for alleviating

psychological symptoms such as anxiety and depression in clinical and nonclinical

populations (e.g., USDHHS, 1996), there are a limited number of studies that have

examined the effects of exercise as a treatment for the psychological changes (i.e., mood

disturbances) experienced during pregnancy. It is important to examine if exercise

improves women's mood during pregnancy because of the higher likelihood for women

to experience negative affect during this time (Carter et al., 2000). Fifth, researchers have








found that exercise behavior decreases during pregnancy and postpartum, however, most

of this research is based on author-developed measures of exercise (Eisen et al., 1991).

Thus, there is a need to examine exercise behavior during pregnancy and postpartum with

standardized measures (Eisen et al.). Sixth, the research examining women's thoughts,

feelings, and beliefs about the facilitating and obstructing factors of exercising during

pregnancy is scant. It is important to examine what women feel about exercising during

their pregnancy to determine how to prevent decreased physical activity during this time.

Finally, while researchers have stated the need for theoretically examining exercise

determinants, most of the research with pregnant populations is theoretical (Maddux &

DuCharme, 1997; Walker et al., 1999).

One conceptual framework that may provide researchers with a better

understanding of women's beliefs about exercising during pregnancy and postpartum is

the theory of planned behavior (TPB; Ajzen, 1988, 1991; Ajzen & Fishbein, 1980). The

TPB is a belief-based model that includes the following eight constructs:

* Behavioral beliefs (i.e., perceived consequences, either positive or negative of
engaging in a behavior, and one's personal evaluation of these consequences).

* Normative beliefs (i.e., whether people believe that significant others such as family
and friends think that they should engage in a behavior).

* Control beliefs (i.e., factors that facilitate and obstruct behavior adoption such as
personal skills, resources, and opportunities).

* Attitude (i.e., people's beliefs about a behavior, the strength of this association, and
the perceived consequences of performing the behavior).

* Subjective norm (i.e., people's normative beliefs about a behavior and their
motivation to comply with the expectations of significant others).

* Perceived behavioral control (i.e., how people feel about the facilitating and
obstructing factors of behavioral adoption and how much control they think they have
over engaging in a behavior).








Intention (ie., a person's plan, and their level of motivation for behavior adoption).

Behavior (i.e., any activity that people wish to engage in such as exercise, smoking
cessation, and eating a balanced diet).

According to Ajzen and Fishbein, people's behavioral, normative, and control beliefs

about a behavior formulate their attitude, subjective norm, and perceived behavioral

control. These factors then influence people's intentions, and ultimately their behavior.

Ajzen and Fishbein (1980) developed guidelines for the TPB. One of their

recommendations is that an elicitation study be performed to establish the salient

behavioral, normative, and control beliefs of a population. An elicitation study should be

conducted with the following three procedures. First, open-ended questions are used to

retrospectively elicit the beliefs (e.g., retrospective accounts are recommended because

they provide a more accurate assessment of people's beliefs since there has been time for

their beliefs to form; K. S. Courneya, personal communication, 2002). Second, a content

analysis (i.e., frequency count) is performed to rank-order the beliefs. Third, structured

TPB items are developed from the most salient beliefs to measure people's attitude,

subjective norm, perceived behavioral control, intention, and behavior.

Researchers have identified the most frequently reported beliefs of exercise

participants (Carron et al., 2003; Symons Downs, Chapter 2). For healthy populations,

Carron and his colleagues have suggested that the most salient behavioral beliefs include

both positive (e.g., exercise improves health) and negative (e.g., exercise reduces time

with family and friends) evaluations regarding exercise. Carron et al. suggested that the

most frequently reported normative beliefs include the influences of significant

individuals (e.g., spouse, mother, brother) and groups (e.g., friends, coworkers). In








addition, the authors concluded that the most common control beliefs are a lack of time,

energy, and motivation.

Recently, Symons Downs (Chapter 2) reviewed 38 studies that elicited exercise

beliefs in healthy and special populations, and she found that:

The most salient behavioral advantage of exercise was that it improves physical and
psychological health.

The most important normative influences were friends, spouses, physicians, and
family members.

The most common control beliefs obstructing exercise behavior were physical and
psychological health issues, a lack of time, and inconvenience.

The findings of Carron et al. (2003) and Symons Downs illustrate the importance of

assessing people's beliefs, and they demonstrate that exercise beliefs can vary from one

population to another.

Moreover, the findings from several narrative (e.g., Blue, 1995; Godin, 1993) and

statistical (e.g., Hagger et al., 2002; Hausenblas et al., 1997; Symons Downs &

Hausenblas, 2002) reviews of the literature have determined that the TPB has been

successfully applied to exercise behavior. The constructs of attitude, subjective norm, and

perceived behavioral control have explained 40% to 60% of the variance in intentions,

and 20% to 40% of the variance in exercise behavior (Culos-Reed et aL, 2001). In

addition, Symons Downs and Hausenblas meta-analytically examined 87 studies, and

they found that attitude was a stronger predictor of intention than perceived behavioral

control, and intention was the strongest predictor of exercise behavior. In addition, less

than half of the reviewed studies included an elicitation study, and smaller intention-

behavior and perceived behavioral control-behavior associations were found when an

elicitation study was not conducted. These findings demonstrate that most researchers








are not adhering to the theory guidelines, and that the utility of the TPB is compromised

when elicitation studies are not conducted.

Furthermore, Symons Downs and Hausenblas (2002) found that the number of

TPB studies examining exercise with at-risk populations is scant. That is, only 22.9% of

the studies they reviewed included special populations (see Appendix A for a detailed list

of these studies). For example, only three located studies have examined the TPB for

exercise behavior with pregnant or postpartum populations (i.e., Godin, Valois, &

Lepage, 1993; Godin, Vezin, & Leclerc, 1989; Godin et al., 1994). Godin et al. (1989)

examined the TPB constructs and habit in predicting 98 pregnant women's intentions to

exercise after giving birth, and they found that perceived barriers emerged as the

strongest predictor. Godin et al. (1993) examined the TPB constructs and habit in

predicting 136 pregnant women's exercise intentions and behavior, and they found that

habit was the only predictor of exercise behavior, and attitude, habit, and perceived

behavioral control predicted intention. Finally, Godin et al. (1994) examined the control

beliefs and perceived barriers to exercise of 139 pregnant women, and they found that

perceived barriers (e.g., baby's health and time management problems) were negatively

associated with intention.

These studies, however, are limited by two methodological concerns. First, Godin

et al. (1989) and Godin et al. (1993) did not conform to the TPB guidelines with respect

to the model constructs (Ajzen, 1991; Ajzen & Fishbein, 1980). That is, in one study (i.e.,

Godin et al., 1989), perceived barriers were substituted for perceived behavioral control,

and in both studies, habit was added to the model to predict intention and behavior.

According to Ajzen, when researchers substitute or add variables to the TPB, the utility








of the model in predicting exercise intentions and behavior is compromised. Second, only

one study (i.e., Godin et al., 1994) conducted an elicitation study to ascertain the salient

beliefs of postpartum women. However, this study only assessed women's control

beliefs. Participants in this study reported that the most important control beliefs

obstructing their exercise were:

Lactation constraints.

Lacking time.

Physical health problems following delivery.

Psychological problems adapting to life after being pregnant.

The baby's health problems.

Thus, no located elicitation studies have examined women's salient behavioral and

control beliefs regarding exercising during pregnancy and postpartum.

Therefore, due to the limited number of studies examining the TPB and exercise

during pregnancy and postpartum, the methodological concerns regarding these studies

(i.e., nonstandardized exercise measures, substituting and adding variables to the TPB),

and the lack of elicitation studies in the literature, the objective of this study was to

examine postpartum women's beliefs about exercising during pregnancy and postpartum

using the theoretical framework of the TPB. The first study purpose was to examine the

frequency of women's behavioral, normative, and control beliefs for exercising during

their pregnancy and postpartum, and to determine their most salient beliefs. Because the

aim of elicitation studies is to generate people's beliefs, and because beliefs are expected

to vary across time and situation (e.g., Ajzen, 1991; Carron et al., 2003), no apriori

hypotheses were established for pregnant women's beliefs. The second study purpose








was to examine participant's physical activity during three periods (i.e., before

pregnancy, during pregnancy, and in postpartum) with a standardized self-report measure

of exercise behavior. Consistent with the conclusions of Zhang and Savitz (1996), it was

hypothesized that the participant's exercise behavior would be greater before pregnancy

compared to during and after pregnancy (i.e., postpartum). The third study purpose was

to examine the participant's body mass index before pregnancy and during in postpartum.

Based on the findings of Carter et al. (2000), it was hypothesized that the participant's

body mass index would be lower before pregnancy compared to postpartum.

Method

Participants

Participants were 74 postpartum women (M age = 31.30 years, SD = 4.37, age

range = 19-40 years). Postpartum was operationalized as being within 1-year of the

child's birth (Anderson, Anderson, & Glanze, 1994). The majority of participants were

Caucasian (81.1%), married (86.5%), college graduates (44.6%), business employees

(39.2%), and earning a family income of $40,000 to $100,000 (62.2%; see Table 3.1).

Measures

Personal History Questionnaire. The Personal History Questionnaire was

developed for this study, and it assessed age, height, weight, date of birth of most recent

child, race/ethnicity, marital status, highest level of education achieved, employment, and

family income (see Appendix B).

Body Mass Index (BMI). BMI was measured with self-reported height and

weight, and it was calculated by converting weight from pounds to kilograms, and

changing height from inches to meters (kg/m2). BMI is a reliable estimate of obesity,








Table 3.1
The Number (N) and Percent (%) of the Demographic Characteristics for the Participants

Characteristic N %a

Race/Ethnicity
Caucasian 60 81.1
Hispanic American 5 6.8
African American 1 1.4
Other 4 5.4
Marital Status
Married 64 86.5
Single 5 6.8
Divorced 3 4.1
Common Law 1 1.4
Widow 1 1.4
Employment
Business 29 39.2
Teacher 8 10.8
Secretary or Administrative Assistant 8 10.8
Housewife 7 9.5
Cashier or Waitress 7 9.5
Nurse 5 6.8
Doctor 4 5.4
Lawyer 2 2.7
Not Employed 1 1.4
Education
High School 16 21.6
College 33 44.6
Graduate 17 23.0
Grade School 1 1.4
Trade 5 6.8
Other 1 1.4
Family Income
Less than $10,000 2 2.7
$10,000 to $20,000 4 5.4
$20,000 to $40,000 9 12.2
$40,000 to $100,000 46 62.2
Greater than $100,000 12 16.2

Note. "May not add up to 100% due to missing data.








however, there is a 5% standard error when using BMI to estimate body fat percentage

(ACSM, 2000; Garrow & Webster, 1985).

Leisure-Time Exercise Questionnaire (LTEO). The LTEQ (Godin, Jobin, &

Bouillon, 1986) assesses the frequency of strenuous, moderate, and mild leisure-time

exercise done for at least 20 min during a typical week (see Appendix C). A total exercise

index (in weekly metabolic equivalents, METS) was calculated for participant's exercise

behavior before, during, and after pregnancy by weighing the frequency of each intensity

and summing them for a total score with the following formula: 3(mild) + 5(moderate) +

9(strenuous). The LTEQ is a reliable and valid measure of exercise behavior (Jacobs,

Ainsworth, Hartman, & Leon, 1993).

Exercise Beliefs Questionnaire. Adhering to the TPB guidelines, the participants

reported their beliefs about exercising during their pregnancy and postpartum (Ajzen &

Fishbein, 1980). Following each question were five double-spaced blank lines for

participants to record as many beliefs that applied to them (see Appendix D). Behavioral

beliefs were measured by the following four questions: "List the main advantages of

exercising during your pregnancy," "List the main disadvantages of exercising during

your pregnancy," "List the main advantages of exercising following the birth of your

child," and "List the main disadvantages of exercising following the birth of your child."

Normative beliefs were measured by the following two questions: "List the individuals or

groups who were most important to you when you thought about exercising during your

pregnancy," and "List the individuals or groups who were most important to you when

you thought about exercising following the birth of your child." Control beliefs were

assessed by the following four questions: "List the main factors that helped you to








exercise during your pregnancy," "List the main factors that prevented you from

exercising during your pregnancy," "List the main factors that helped you exercise

following the birth of your child," and "List the main factors that prevented you from

exercising following the birth of your child." Content validity of the Exercise Beliefs

Questionnaire was established by having two TPB and exercise experts examine the

items (i.e., the experts obtained 100% content validity agreement).

Procedures

Approval was obtained from the University's Institutional Review Board to

conduct this study (see Appendix E). Consent was obtained from a private practice

physician specializing in obstetrics and gynecology, who agreed to assist with the data

collection. The consent form (see Appendix F) and the questionnaire packets (i.e.,

Personal History Questionnaire, the LTEQ, and the Exercise Beliefs Questionnaire) were

mailed to the doctor's office in New Britain, CT at the end of October, 2000, and the data

were collected from November, 2000 to April, 2001.

The participants volunteering for this study were given a questionnaire packet

while they waited for their doctor's appointment. They completed the questionnaire

packets in a medium-sized furnished waiting room, and the measures took approximately

15 min to finish. Upon completing the packet, each participant was instructed to place

their consent form and questionnaires in a sealed envelope and return it to the

receptionist's desk. From a total of 74 questionnaires that were distributed to the

participants in the doctor's office, 74 women completed and returned their

questionnaires; thus, representing a 100% response rate. All participants were treated in








accordance with the guidelines for human participants as specified by the American

Psychological Association (1992). The completed questionnaire packets were mailed

back to the Principal Investigator at the end of April, 2001.

Data Analysis

Paired t-tests were undertaken with Bonferonni correction (.05/4, p = .01) to

compare participant's: a) BMI before and after pregnancy, and b) total LTEQ scores

before pregnancy and during postpartum, c) total LTEQ scores before pregnancy and

during pregnancy, and c) total LTEQ scores during postpartum and pregnancy. To

determine the meaningfulness of these results, eta squared (12) was calculated with .20,

.50 and .80 representing small, medium, and large effects, respectively (Cohen, 1969,

1992).

To assess the salient beliefs, I followed the recommendations of Ajzen and

Fishbein (1980) and used a 5-step procedure. First, the raw data themes (i.e., open-ended

responses) were tabulated and categorized by belief type (i.e., behavioral, normative,

control) and time (i.e., during pregnancy or postpartum). Second, the raw data themes

were organized into higher-order themes based on the procedures of Patton (1990). Third,

a content analysis was conducted to determine the most salient beliefs. Consistent with

previous researchers, the most salient beliefs were identified (i.e., the most frequent 5 to

10 beliefs; Ajzen, 1991; Carron et al., 2003). The content analysis was conducted by: a)

sorting participant's responses into sets of statements which involved the same

underlying belief b) obtaining a frequency count for each set of beliefs to determine the

most salient beliefs, and c) double-checking the belief sets to ensure that all of the beliefs

were appropriately sorted (Patton). Fourth, to determine consistency in the classifications,








the belief sets were reviewed by four experts (i.e., two experts on the TPB and two

doctoral students specializing in exercise psychology). Fifth, the beliefs were rank-

ordered from the most to the least salient. A detailed list of the exercise beliefs for

pregnancy and postpartum are located in Table 3.2 and Table 3.3, respectively.

Results

Exercise behavior and BMI. The LTEQ total scores were significantly higher

before pregnancy (M = 33.08, SD = 27.20) compared to during pregnancy (M = 18.25,

SD= 17.89) [t (50) = 5.81, p <.001, 12= .40], and compared to postpartum (M= 16.56,

SD = 15.18) [t (51) = 4.38, p < .001, i2 = .27]. No significant differences were observed

in participant's LTEQ total scores during pregnancy compared to postpartum, [t (50) =

.65, p > .05, i2= .01]. Participant's BMI was significantly higher in postpartum (M =

28.26, SD = 6.07) compared to before pregnancy (M = 26.71, SD =6.32), [t (62) = 4.85,

p < .001, r2= .28]. Figure 3.1 presents the LTEQ total scores before, during, and after

pregnancy. Figure 3.2 displays the participant's BMI before and after pregnancy.

Behavioral beliefs. The behavioral advantages of exercising during pregnancy

were that exercise: a) improves overall mood (33.8%), b) increases energy and stamina

(29.7%), c) assists with staying fit (21.6%), d) controls weight (18.9%), e) assists with

labor and delivery (14.9%), and f) provides stress relief (8.1%). The behavioral

disadvantages were: a) causes physical discomfort (24.3%), b) tiredness and fatigue

(24.3%), and c) time limits (10.8%). For exercising during postpartum the advantages

were that exercise: a) controls weight (37.8%), b) assists with staying fit (36.5%), c)

improves overall mood (31.1%), d) increases energy and stamina (10.8%), e) decreases








Table 3.2
Type. Number (N), and Percent (%) of Beliefs Reported During Pregnancy


Belief Type Higher-order Theme Raw Data Theme(s) No %


Behavioral
Beliefs
(Advantages)


Improves overall mood Feel good, better about
self, more comfortable,
mental health, improve
mood and overall
well-being


25 33.8


Increases energy
and stamina



Stay fit



Controls weight


Assist in labor and
and delivery

Provides stress relief


Causes physical
discomfort


Tiredness and
fatigue

Time limits


Husband or fiance


More energy, maintain
current level of energy,
less tired, improve
stamina and endurance

Fitness and flexibility,
stay in shape, keep muscle
tone, to walk

Keeps weight in check,
help weight

Make delivery easier
and faster

Stress reduction,
relaxation

Swelling, soreness,
cramping, nausea, too
big, shortness of breath

Too much effort, need
to conserve energy

Time limits in schedule,
no time, lacking time


Children


22 29.7




16 21.6



14 18.9


11 14.9


6 8.1


18 24.3



18 24.3


8 10.8


27 36.5

13 17.6


Behavioral
Beliefs
(Disadvantages)


Normative
Beliefs








Table 3.2 Continu

Belief Type


Control
Beliefs
(Obstructing
Factors)


Control
Beliefs
(Facilitating
Factors)


led

Higher-order Theme

Family members
other than husband
and children

Friends

Doctors

Gym instructors

Physical therapist

Physical limitations
and restrictions


Tiredness and
fatigue

No time


Gaining weight


Other children


Fear


Bad weather


No motivation


Improves overall
mood


Raw Data Theme(s)


Vomiting, nausea,
cramps, swelling,
uncomfortable

Tired, fatigued,
no energy

Lacking time,
time restrictions

Weight gain, size,
too big

Taking care of
children, being a mom

Afraid to harm unborn
baby or self

Bad weather, rain,
too cold

No motivation or
ambition, feel lazy

Feel good, healthy,
mental health


N" %

11 14.9



9 12.2

2 2.7

2 2.7

1 1.4

42 56.8



20 27.0


19 25.7


10 13.5


7 9.5


7 9.5


6 8.1


6 8.1


11 14.9





69


Table 3.2 Continued

Belief Type Higher-order Theme Raw Data Theme(s) N' %

Controls weight Keeps weight in 11 14.9
in check, controls
weight and feeling fat

Motivation Motivation from 8 10.8
from others husband, encouraging
friends

Stay healthy Wanting to stay healthy 6 8.1
for good delivery and
a healthy baby

Other children Son, daughter, children 6 8.1

Stay fit To stay fit, stay in shape 6 8.1

Note. = May not add up to 100% because some participants reported multiple beliefs.








Table 3.3
Type, Number (N), and Percent (%) of Beliefs Reported During Postpartum


Belief Type Higher-order Theme Raw Data Theme(s) N" %


Controls weight


Stay fit


Improves overall
mood




Increases energy
and stamina



Decreases physical
discomfort

Provides stress
relief

Causes physical
discomfort


Time limits


Tiredness and
fatigue

Difficulty with
exercises

Husband or fiance

Family members


Behavioral
Beliefs
(Advantages)


Keep weight in check,
helps weight

Fitness and flexibility,
stay in shape, keep
muscle tone, to walk

Feel good, better about
self, more comfortable,
mental health, improves
mood and overall
well-being

More energy, maintain
current level of energy,
less tired, improve
stamina and endurance

Relieves leg cramps,
soreness, swelling

Stress reduction,
relaxation

Swelling, soreness,
cramping, nausea, too
big, shortness of breath

Time limits in schedule,
no time, lacking time

Too much effort, need
to conserve energy

Difficulty doing some
exercises


Behavioral
Beliefs
(Disadvantages)


Normative
Beliefs


28 37.8


27 36.5



23 31.1





22 29.7




3 4.1


2 2.7


17 23.0



16 21.6


13 17.6


2 2.7


28 37.8

11 14.9








Table 3.3 Continued

Belief Type Higher-order Theme Raw Data Theme(s) N" %

Family members 14 18.9
other than husband
and children

Friends 9 12.2

Children 7 9.5

Doctors 3 4.1

Gym instructor 1 1.4

Physical therapist 1 1.4

Control No time Lacking time, 36 48.6
Beliefs time restrictions
(Obstructing
Factors) Physical limitations Vomiting, nausea, 16 21.6
and restrictions cramps, swelling,
uncomfortable

Tiredness and Tired, fatigued, 10 13.5
fatigue no energy

Fear Afraid to harm self 8 10.8

No motivation No motivation or 6 8.1
ambition, feel lazy

Control Controls weight Keeps weight in 16 21.6
Beliefs check, controls
(Facilitating weight and feeling fat
Factors)
Improves overall Feel good, healthy, 11 14.9
mood mental health

Motivation Motivation from 9 12.2
from others husband and friends

Stay fit To stay fit, stay in shape 9 12.2

Note. = May not add up to 100% because some participants reported multiple beliefs.



























10 1 --- I
Prior to Pregnancy During Pregnancy During Postpartum

Figure 3.1. Mean Leisure-Time Exercise Questionnaire (LTEQ) total scores for before
pregnancy, during pregnancy, and during postpartum. Women had significantly higher
LTEQ total scores before pregnancy compared to during pregnancy (p < .001) and during
postpartum (1 <.001). No significant differences in LTEQ total scores were observed for
during pregnancy compared to during postpartum.


Prior to Pregnancy During Postpartum


Figure 3.2. Mean Body Mass Index (BMI) before pregnancy and during postpartum.
Women had significantly higher BMI during postpartum compared to before pregnancy
( <.001).


in








physical discomfort (4.1%), and f) provides stress relief (2.7%). The disadvantages were:

a) causes physical discomfort (23.0%), b) time limits (21.6%), c) tiredness and fatigue

(17.6%), and d) difficulty with some exercises (2.7%). Figure 3.3 presents the salient

advantages of exercising during pregnancy and Figure 3.4 displays the advantages of

exercising during postpartum.

Normative beliefs. For exercising during pregnancy, the normative beliefs were:

a) husband or fiance (36.5%), b) children (17.6%), c) family members other than husband

or children (14.9%), d) friends (12.2%), e) doctors (2.7%), f) gym instructors (2.7%), and

g) physical therapist (1.4%). For exercising during postpartum, the normative beliefs

were: a) husband or fiance (37.8%), b) family members other than husband or children

(18.9%), c) friends (14.9%), d) children (9.5%), e) doctors (4.1%), f) gym instructor

(1.4%), and g) physical therapist (1.4%). Figure 3.5 presents the salient normative beliefs

for exercising during pregnancy. Figure 3.6 displays the salient normative beliefs for

exercising during postpartum.

Control beliefs For exercising during pregnancy, the reported control beliefs that

obstructed exercise were: a) physical limitations and restrictions (56.8%), b) tiredness

and fatigue (27.0%), c) no time (25.7%), d) gaining weight (13.5%), e) other children

(9.5%), i) fear of harming self or the baby (9.5%), g) bad weather (8.1%), and h) no

motivation (8.1%). The control beliefs that facilitated exercise were: a) improves overall

mood (14.9%), b) controls weight (14.90/), c) motivation from others (10.8%), d) stay

healthy, e) other children (8.1%), and f) assist with staying fit (8.1%). For exercising

during postpartum, the obstructing control beliefs were: a) no time (48.6%), b) physical

limitations and restrictions (21.6%), c) tiredness and fatigue (13.5%), d) fear of harming








O Improves overall mood
* Increases energy & stamina
* Stay fit
D Controls weight


Figure 3.3. The most salient behavioral advantages of exercising during pregnancy were:
a) improves overall mood (34%), b) increases energy and stamina (30%), c) stay fit
(22%), and d) controls weight (19%).




Improves overall mood
SIncreases energy & stamina
Stay fit
0 Controls weight




Figure 3.4. The most salient behavioral advantages of exercising during postpartum were:
a) controls weight (38%), b) stay fit (37%), c) improves overall mood (31%), and d)
increases energy and stamina (30%).


ii)











Husband or fiance

Children

Other family members

O Friends









Figure 3.5. The most salient normative beliefs for exercising during pregnancy were: a)
husband or fiance (37%), b) children (18%), c) family members other than husband or
children (15%), and friends (12%).







Husband or fiance

Children

Other family members

O Friends








Figure 3.6. The most salient normative beliefs for exercising during postpartum were: a)
husband or fiance (38%), b) family members other than husband or children (19%), c)
friends (15%), and d) children (10%).








self (10.8%), and e) no motivation (8.1%). The facilitating control beliefs were: a)

controls weight (21.6%), b) improves overall mood (14.9%), c) motivation from others

(12.2%), and assists with staying fit (12.2%). Figure 3.7 presents the salient control

beliefs obstructing exercising during pregnancy. Figure 3.8 displays the salient control

beliefs obstructing exercising during postpartum.

Discussion

The purpose of this study was three-fold. The first purpose was to use the

theoretical framework of the TPB to examine the frequency of behavioral, normative, and

control beliefs of women regarding exercising during their pregnancy and postpartum,

and to determine which of their beliefs were most salient. The second purpose was to

assess the participant's physical activity before pregnancy, during pregnancy, and during

postpartum with a standardized measure of exercise behavior. The third purpose was to

examine the participant's BMI before pregnancy and during postpartum. Several findings

warrant discussion.

First, the frequency of behavioral beliefs varied from pregnancy to postpartum.

These findings are consistent with the conclusions of researchers who have suggested that

people's beliefs can vary depending on the time and situation (Ajzen, 1991; Carron et al.,

2003). For example, the most common behavioral advantage during pregnancy was that

exercise helped to improve women's overall mood; whereas in postpartum, the most

common behavioral advantage was that exercise helped to control women's weight.

Researchers aiming to increase exercise during pregnancy and postpartum should

consider the differences in women's salient behavioral beliefs during these times.












0 Physical limitations &
restrictions
Tiredness & fatigue

No time











Figure 3.7. The most salient control beliefs obstructing exercising during pregnancy
were: a) physical limitations and restrictions (57%), b) tiredness and fatigue (27%), and
c) no time (26%).







0 Physical limitations &
restrictions
Tiredness & fatigue

SNo time











Figure 3.8. The most salient control beliefs obstructing exercising during pregnancy
were: a) no time (49%), b) physical limitations and restrictions (22%), and c) tiredness
and fatigue (14%).








Specifically, researchers conducting exercise interventions during pregnancy may want to

focus on methods that help to improve women's overall mood (e.g., muscle relaxing and

imagery techniques). Alternatively, researchers conducting interventions during

postpartum may want to concentrate on methods that assist women in weight control

(e.g., calorie expending activities such as aerobics and running, and proper dieting).

Second, the most common normative influence during pregnancy and postpartum

was from a woman's husband or fiance. These findings are consistent with the

conclusions of Symons Downs (Chapter 2). Specifically, I reviewed 38 TPB and exercise

elicitation studies, and I found that the most salient normative influences for healthy and

special populations were people's friends, spouses, physicians, and other family

members. The current findings indicate that women's spouses have an important

influence on their exercise behavior during pregnancy and postpartum. Future researchers

are encouraged to examine other factors that may influence women's exercise behavior

such as marital satisfaction and the type of feedback (i.e., positive versus negative) that

women receive from their spouses regarding exercising during pregnancy and

postpartum.

In addition, it is important to note that the women in this study did not indicate

that their physicians were an important normative influence for exercising during

pregnancy or postpartum. Considering that 70% of adults are examined by a healthcare

provider at least one time per year, it has been suggested that physicians may play a

valuable role in promoting exercise behavior with their patients (Logsdon et al., 1989).

However, more research is needed that examines the normative influence of physicians








before any conclusions can be made regarding their impact on women's exercise

behavior during pregnancy and postpartum.

Third, the frequency of control beliefs varied from pregnancy to postpartum. The

most common control beliefs obstructing exercising during pregnancy were physical

limitations and restrictions; whereas during postpartum, the most frequently reported

obstructing control belief was having no time. Thus, researchers aiming to promote

physical activity during pregnancy may consider methods that make women feel more

comfortable (e.g., home-based exercise programs tailored to women's specific needs and

limitations, water calisthenics). In comparison, researchers promoting physical activity

during postpartum may focus on methods that provide women with useful skills for

scheduling exercise into their daily routines (e.g., time management, organizing,

preparing, planning, goal-setting). For example, Symons Downs and Singer (2002) found

that exercise goals formed with implementation intentions (i.e., specifying where, when,

and at what time exercise would occur) assisted college students with increasing their

exercise performance over eight weeks. These same techniques may assist researchers

with promoting exercising during pregnancy and postpartum.

Fourth, consistent with the hypothesis, participant's LTEQ total scores were

higher before pregnancy compared to during pregnancy and postpartum. That is, the

participants were engaging in more exercise before they were pregnant compared to

during their pregnancy and postpartum. These findings are consistent with previous

researchers conclusions that pregnancy can promote decreases in exercise behavior

during pregnancy and postpartum (USDHHS, 1996, 2000; Zhang & Savitz, 1996). While

the temporary decrease in exercise during pregnancy and postpartum may not be harmful;








over time, lower levels of exercise behavior are associated with increasing people's risk

of disease, gaining weight, and decreasing longevity (USDHHS). Thus, more research is

warranted that promotes exercising during pregnancy and postpartum, and that examines

physical activity prospectively and longitudinally to determine when and if women return

to their prepregnancy exercise behavior.

Fifth, as predicted, women's BMI was greater during postpartum compared to

before pregnancy. It is important to note that the participant's BMI was greater than 25

before pregnancy and during postpartum; thus, classifying these women as overweight

during both of these periods (ACSM, 1999, 2000). These findings are concerning because

higher BMI is associated with an increased risk for cardiovascular disease, type II

diabetes, and obesity (USDHHS, 2000). In addition, some researchers have suggested

that higher BMI before and during pregnancy may predict the onset of depressive

symptoms occurring in postpartum (Carter et al., 2000). For example, Carter and her

colleagues found that higher BMI was not associated with anxiety and depression during

pregnancy, however, it was associated with these affective symptoms during postpartum.

Moreover, according to Ross's (1994) Self-Reflected Appraisal Theory, when

increased weight is perceived as accepted (e.g., women may feel that gaining weight is

justified during pregnancy because they are nurturing their growing infant), higher BMI

will be less likely to influence depression. However, higher BMI during pregnancy may

exacerbate affective symptoms during postpartum (e.g., women may feel that being

overweight during postpartum can no longer be justified; Carter et al., 2000).

Furthermore, the fact that BMI had not returned to baseline values after pregnancy

illustrates the need for longitudinal studies that assess if and when women return to their








prepregnancy weights. This is important to examine because postpartum may be a critical

event that promotes increased weight gain, and interventions that include exercise may

assist women in controlling and maintaining their weight during postpartum (Bungum et

al., 2000; Carter et al.).

There are three limitations of this study that should be noted. First, my original

intention was to examine exercise behaviors across ethnically diverse women. However,

difficulties in recruiting participants from African American and Hispanic American

populations narrowed the participant pool to mostly middle to upper class Caucasian

Americans; and thus, there is limited generalizability in the findings to low

socioeconomic status and ethnic minority populations. Second, while BMI was measured

before and after pregnancy, it was not assessed during pregnancy. While it is assumed

that the participants' BMI was higher during pregnancy due to the baby, it is important to

assess BMI before, during, and after pregnancy to examine how much it fluctuates

throughout the pregnancy. In addition, this information may be a helpful intervention tool

for researchers. That is, BMI can be used as a benchmark for improving women's weight

during postpartum (e.g., women can use their BMI to keep track of their progress with

losing weight). Thus, future researchers are encouraged to measure BMI before, during,

and after pregnancy.

Third, the postpartum period was operationalized as "within one year of the

child's birth." However, because participants were not asked to report when they filled-

out the questionnaire packet, the time that they completed the surveys during postpartum

(e.g., 6-weeks postpartum or 6 months postpartum) could not be determined. Researchers

examining exercise beliefs during pregnancy are encouraged to record when the








participants complete their surveys because women's beliefs may vary across trimesters.

For example, what women identify as obstructing factors early in pregnancy (e.g.,

nausea, vomiting) may not be the same factors that limit their exercise later on in

pregnancy (e.g., physical size, too uncomfortable). Similarly, women's beliefs can vary

from early postpartum (e.g., exercising helps to control weight) to later in postpartum

(e.g., exercising takes away from other family and work commitments).

Prelude to Chapter 4

Pregnancy places a tremendous amount of physiological and psychological stress

on a woman's body including changes in weight, posture, diet, and cardiovascular and

gastrointestinal functioning (Bungum et al., 2000; Wallace & Engstrom, 1987). Despite

these demands, exercise during pregnancy and postpartum is a recommended and

beneficial activity for alleviating affective symptoms (e.g., anxiety, depression) and

controlling weight gain during this time (ACOG, 1994). The findings from this study

indicated that women's beliefs about exercising varied from pregnancy to postpartum,

and researchers aiming to understand the determinants of exercising during pregnancy

and postpartum should consider those differences when planning and implementing their

exercise interventions. In addition, following the recommendations of Ajzen and Fishbein

(1980), the salient behavioral, normative, and beliefs elicited from this study provided the

framework for the belief measures used in Study 3. The next chapter (i.e., Chapter 4) is a

prospective study of the TPB and exercising from pregnant women's second to their third

trimester (i.e., Study 3).














CHAPTER 4
STUDY 3: EXAMINING PREGNANT WOMEN'S EXERCISE INTENTION AND
BEHAVIOR FROM THEIR SECOND TO THEIR THIRD TRIMESTER: A
PROSPECTIVE EXAMINATION OF THE THEORY OF PLANNED BEHAVIOR

Regular physical activity contributes positively to physical health (e.g.,

decreasing risk of atherosclerosis, diabetes, and obesity) and psychological well-being

(e.g., decreasing anxiety and depression; USDHHS, 1996, 2000). Despite these benefits,

approximately 58% of pregnant women are sedentary, which is almost twice the national

average for sedentary adults (i.e., 30% of U.S. adults are sedentary; USDHHS; Zhang &

Savitz, 1996). This is alarming because low physically active and sedentary lifestyles are

associated with a greater risk of disease, poorer mental health, and increased weight

(USDHHS). Thus, it is important to understand the facilitating and obstructing factors of

exercising during pregnancy to increase women's physical activity during this time.

Pregnancy is associated with a variety of physical (e.g., increased cardiac output,

ventilation, and weight) and psychological (e.g., symptoms of anxiety, stress, and

depression) demands; and thus, many women either decrease or stop exercising during

this time (Bungum et al., 2000; Monk et al., 2000; Zuckerman et al., 1989). Despite the

challenges of pregnancy, exercise is a safe and beneficial activity for most women

(Lokey et al., 1991). For example, Lokey and his colleagues meta-analytically examined

the physical effects of exercising during pregnancy, and they concluded that regular

physical activity is not associated with harming either the mother or the fetus. Exercising

during pregnancy also has psychological benefits such as decreasing anxiety and








depression, and improving self-esteem, mood, and body image (Bungum et al., 2000;

Koniak-Griffin, 1994; Walker et al., 1999). In addition, exercising during pregnancy

controls excessive weight gain, which is important considering that 30% of normal

weight and 60% of overweight women gain more weight during their pregnancy than is

recommended (i.e., normal weight gain is 20 to 30 Ibs; Polley, 2001). Researchers have

found that greater weight gain during pregnancy is associated with negative affective

symptoms (e.g., anxiety and depression), and greater postpartum weight retention in both

pregnancy and postpartum (Carter et al., 2000; Polley). Thus, exercise is a valuable

method for managing the physical and psychological challenges of pregnancy (Bungum

et al.).

Although exercising during pregnancy contributes to women's health (ACOG,

1994; USDHHS, 2000), the research examining women's attitude, behavior, and

cognition about exercising during their pregnancy is scant and limited by several

conceptual and methodological factors (see Chapter 3 for a detailed list). A main

conceptual concern is the lack of theoretical research that examines exercise behavior

during pregnancy. For example, while the theory of planned behavior (TPB; Ajzen &

Fishbein, 1980; Ajzen, 1991) has been successfully applied to exercise behavior in

healthy populations (see Symons Downs & Hausenblas, 2002 for a statistical review), its

application to exercise behavior during pregnancy is scant. Moreover, Symons Downs

(Chapter 3) found that only three studies from a recent meta-analysis of the TPB and

exercise (i.e., Symons Downs & Hausenblas) included pregnant populations, and these

studies were limited by methodological issues (Godin et al., 1994; Godin et al., 1993;

Godin et al., 1989).








For instance, Godin et al. (1989) examined 98 pregnant women's attitude,

subjective norm, perceived barriers, and habit in predicting their intention to exercise

after giving birth. Godin and his colleagues found that perceived barriers was the

strongest predictor of intention. However, the predictive utility of the TPB was

compromised when the authors substituted perceived barriers for perceived behavioral

control and added habit to the model. That is, according to Ajzen and Fishbein, when

constructs other than the theoretical tenets of the TPB are substituted or added to the

model the predictive utility of the TPB is jeopardized.

In addition, Godin et al. (1993) examined 136 pregnant women's attitude,

perceived behavioral control, and habit in predicting their exercise intention and

behavior. The authors found that all three constructs predicted intention; however, only

habit predicted exercise behavior. While Godin and his colleagues concluded that

perceived behavioral control contributed to the understanding of intention but not

behavior, this assumption was compromised by not including subjective norm in the

model, and by adding habit to the model (Ajzen & Fishbein, 1980).

Moreover, only Godin et aL (1994) followed Ajzen and Fishbein's (1980)

recommendations and conducted an elicitation study to establish the participants' salient

beliefs about exercising during their pregnancy. Godin and his colleagues assessed

postpartum women's control beliefs for exercising during pregnancy, and they found that

the most important beliefs were lactation constraints, lack of time, physical health

problems for the mother and baby, and difficulties adapting to life after pregnancy.

However, the authors did not obtain the salient behavioral and normative beliefs of these

women. Thus, because women's exercise behavior can decrease during pregnancy, and








because there are few studies assessing the TPB constructs and exercise with pregnant

populations, more research is needed that examines pregnant women's behavioral,

normative, and control beliefs for exercising during pregnancy. In addition, research is

needed that examines the utility of the TPB constructs (i.e., attitude, subjective norm,

perceived behavioral control) in predicting pregnant women's exercise intention and

behavior.

A second limitation with the exercise and pregnancy literature is that most of the

research is cross-sectional (e.g., Koniak-Griffin, 1994), and few studies have

prospectively examined pregnant women's exercise behavior. Thus, there is a need for

research that prospectively examines the determinants of exercising during pregnancy.

While the framework of the TPB allows researchers to prospectively examine the

constructs, the literature examining the TPB and exercising during pregnancy is scant.

More specifically, no studies have been found examining the TPB and exercising from

pregnant women's second to their third trimester. Moreover, prospective investigations of

the TPB and exercising during pregnancy are needed to determine which of the TPB

constructs most strongly predict exercise intention and behavior from pregnant women's

second to their third trimester. This information can assist researchers with developing

exercise and pregnancy interventions that are specific to the needs of women during these

trimesters.

A third limitation of the exercise and pregnancy literature is the lack of research

examining exercise behavior during pregnancy with standardized exercise measures

(Eisen et al., 1991). That is, most of the studies examining exercising during pregnancy

are based on dichotomous (yes/no) self-report items (e.g., "Do you participate in regular








physical activity during pregnancy?"), nonstandardized author-developed questionnaires,

and frequency or duration of exercise behavior (Stemfeld, 1997). For example, Kulpa,

White, and Visscher (1987) classified pregnant women as exercisers if they participated

in aerobic exercise more than once per week for at least 15 min. This type of

classification is problematic because women are being categorized as exercisers when

they may only be exercising twice a week, which is less than the prescribed exercise

guidelines (i.e., ACOG, 1994; ACSM, 2000). In addition, because the ACOG

recommends that women do not exceed 144 bpm when exercising during their

pregnancy, it is necessary to examine exercise intensity with a standardized measure of

exercise. For example, the Leisure-Time Exercise Questionnaire (Godin et al., 1986)

assesses the frequency of strenuous, moderate, and mild leisure-time exercise, which can

assist researchers in determining women's exercise intensity during their pregnancy, and

if women are meeting the ACOG guidelines for exercising during their pregnancy. In

short, research is needed that examines exercising during pregnancy with standardized

self-report measures such as the Leisure-Time Exercise Questionnaire.

Finally, researchers have found that pregnancy is associated with increased

negative mood and body image disturbance (Bungum et al., 2000; Koniak-Griffin, 1994).

This is important considering that weight gain during pregnancy is associated with

negative affective symptoms (e.g., anxiety, stress, depression) during pregnancy and

postpartum (Cameron et al., 1996). For example, researchers have found that 8% of

women are concerned about their weight during pregnancy, and 75% of women are

unhappy with their weight during the first few weeks of postpartum (Baker, Carter,

Cohen, & Brownell, 1999; Hisner, 1986). However, the research prospectively examining








body mass index and exercise behavior during pregnancy is scant. In one of the few

located prospective studies, Carter and her colleagues (2000) found that higher body

mass index was not associated with negative affect (i.e., anxiety and depression) during

pregnancy, whereas it was associated with these symptoms during the first four weeks of

postpartum. These findings illustrate that higher body mass index can place women more

at risk for experiencing mood disturbances during postpartum. Thus, there is a need to

prospectively examine body mass index during pregnancy. In summary, the absence of

studies prospectively examining the TPB, body mass index, and exercise behavior during

pregnancy demonstrates that more research examining these constructs is warranted.

There were four purposes of this study. The first purpose was to prospectively

examine the utility of the TPB in predicting pregnant women's exercise intention and

behavior from their second to their third trimester. Consistent with the findings of

previous researchers (i.e., Symons Downs & Hausenblas, 2002) for exercise behavior, it

was hypothesized that intention and perceived behavioral control would predict exercise

behavior, with intention being the strongest predictor of exercise behavior. For intention,

it was hypothesized that attitude, perceived behavioral control, and subjective norm

would predict intention, with attitude being the strongest predictor of intention.

The second purpose was to examine the associations among the TPB constructs.

Based on theoretical assumptions of Ajzen and Fishbein (1980; Ajzen, 1991), it was

hypothesized that during the second pregnancy trimester women's behavioral beliefs

would be positively associated with their attitude, their normative beliefs would be

positively associated with their subjective norm, and their control beliefs would be

positively associated with their perceived behavioral control.




Full Text
EXAMINING THE PSYCHOSOCIAL DETERMINANTS OF EXERCISE DURING
PREGNANCY USING THE FRAMEWORK OF THE THEORY OF PLANNED
BEHAVIOR: A PROSPECTIVE INVESTIGATION
By
DANIELLE SYMONS DOWNS
A DISSERTATION PRESENTED TO THE DEPARTMENT OF EXERCISE
AND SPORT SCIENCES OF THE UNIVERSITY OF FLORIDA IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY IN HEALTH AND HUMAN PERFORMANCE
UNIVERSITY OF FLORIDA
2002

Copyright © 2002
by
Danielle Symons Downs

This dissertation is dedicated to my best friend and husband, Jon Downs.
He is my inspiration.

ACKNOWLEDGMENTS
I would like to take this opportunity to extend my deepest gratitude and
appreciation to the many people who have helped me throughout this entire dissertation
process. First, I would like to thank my advisor, Dr. Heather Hausenblas, for her
intelligence, guidance, support, and tremendous patience. This dissertation would not
have been possible without her UF Opportunity Fund grant, and her countless hours of
planning, preparation, and thrashing (oops, I mean editing!) © Heather has been not only
my advisor and mentor, but my greatest role model. I am grateful for her many pep talks,
for pushing me to work to my potential, and for helping me become who I am today.
Most of all, I thank Heather for her friendship. 1 am forever grateful for her! Second, I
would like to thank my other committee members: Dr. Robert Singer, Dr. James
Shepperd, and Dr. Peter Giacobbi. Dr. Singer will always be the first person who gave
me the chance to prove myself. I thank him for his continued support, guidance, and
direction. Most of all, I thank him for his trust and for believing in me. I thank Dr.
Shepperd for sharing his knowledge, for answering many of my questions, and for
challenging me to see myself, and my research, from another perspective. I thank Dr.
Giacobbi, for his time and his insightful conversations regarding my research philosophy.
Third, I would like to extend a special thanks to those individuals who assisted me
with recruiting my participants and collecting data. Without Dr. Andreoli’s support, this
dissertation would not have been possible. He is an inspiration in so many ways, not to
IV

not to mention and outstanding physician and father. I thank Dr. Connor and Katherine
Hutchison for allowing me to collect data from their office. I am grateful for Katherine’s
dedication to my project and for our many talks. 1 would also like to thank Nini
DeBraganza and Shivani Shaw for their commitment, and their many hours of assistance
with this project. I could not have finished this dissertation without all of them!
Fourth, I would like to thank the many people in my life who have believed in
me: especially Heather Polen, the Schwartz’s, the Andreoli’s, and the Stafford’s. I thank
them for always being there, even when I didn’t have much to offer back. 1 thank Becky
Filis Gardner for her support, and Derek de la Pena, Amy Hagan, Aaron Duley, Jim
Curby, Lori Gibbs, and Gary Nave for keeping me sane...they are the best!
Finally, I would like to thank my family for their unconditional love and support.
My deepest gratitude is extended to my parents, Sandra and Robert Symons, and Susan
and John Downs. Their encouragement, faith, and love will always make me strive to be
my best. I thank my sisters and brothers for putting up with me! I thank the Repka’s and
the Reid’s for their encouragement, trips to the airport, and for making their homes ours. I
thank my Pap for challenging and believing in me. He makes me proud! Finally, it is
without question that my husband, Jon, is the reason for this dissertation. 1 thank God
everyday for him. Without his motivation, inspiration, faith, love, and humor, this project
would not have been possible. I thank him for his patience, putting up with my
“meltdowns,” and for understanding why 1 needed to spend many endless nights glued to
the computer “until it was perfect.” He is my best friend (my “buddy”), and my greatest
inspiration. Lastly, 1 am grateful that he was able to keep himself busy on the golf course
while I wrote this dissertation, ft was a tough job, but together, we can handle anything!
v

TABLE OF CONTENTS
page
ACKNOWLEDGMENTS iv
ABSTRACT »
CHAPTER
1 INTRODUCTION 1
Theory of Planned Behavior Constructs 3
Scale Correspondence 8
Elicitation Studies 10
Empirical Support for the TPB and Exercise Behavior 12
Importance of Examining Exercise and Pregnancy 15
Dissertation Studies 16
2 STUDY 1: THE THEORY OF PLANNED BEHAVIOR AND ELICITATION
STUDIES: A SYSTEMATIC REVIEW OF EXERCISE BELIEFS 19
Method 25
Selection and Inclusion of Studies 25
Review Procedures 25
Data Analysis 26
Results 35
Elicitation Study Characteristics 35
Main Theory of Planned Behavior Study Characteristics 35
Elicitation Study Method Characteristics 38
Elicitation Study Belief Characteristics 38
Discussion 44
Prelude to Chapter 3 51
3 STUDY 2: THE THEORY OF PLANNED BEHAVIOR AND EXERCISING
DURING PREGNANCY AND POSTPARTUM: AN ELICITATION STUDY 52
Method 61
Participants 61
Measures 61
Procedure 64
vi

Data Analysis 65
Results 66
Discussion 76
Prelude to Chapter 4 82
4 STUDY 3: EXAMINING PREGNANT WOMEN'S EXERCISE INTENTION
AND BEHAVIOR FROM THEIR SECOND TO THEIR THIRD TRIMESTER:
A PROSPECTIVE EXAMINATION OF THE THEORY OF PLANNED
BEHAVIOR 83
Method 89
Participants 89
Measures 89
Procedure 96
Data Analysis 98
Results 99
Discussion 102
4 GENERAL DISCUSSION 110
Summary of the Dissertation Studies 110
Study 1 110
Study 2 112
Study 3 114
Recommendations for Future Research 116
Moderator Variables 116
Conceptual and Measurement Issues 117
Practical Implications of This Dissertation 122
Conclusion 123
APPENDIX
A THEORY OF PLANNED BEHAVIOR AND EXERCISE STUDIES
WITH SPECIAL POPULATIONS 125
B PERSONAL HISTORY QUESTIONNAIRE 130
C LEISURE-TIME EXERCISE QUESTIONNAIRE 131
D ELICITATION BELIEFS QUESTIONNAIRE 132
E IRB APPROVAL FOR STUDY 2 135
F CONSENT FORM 136
G PERSONAL HISTORY QUESTIONNAIRE 137
H BEHAVIORAL BELIEF ITEMS 138
vii

I NORMATIVE BELIEF ITEMS
139
J CONTROL BELIEF ITEMS 140
K ATTITUDE ITEMS 141
L SUBJECTIVE NORM ITEM 142
M PERCEIVED BEHAVIORAL CONTROL ITEMS 143
N INTENTION ITEM 144
O EXERCISE BEHAVIOR ITEM 145
P IRB APPROVAL FOR STUDY 3 146
Q STUDY 3 EXPLANATION 147
R CONSENT FORM 148
S SECOND TRIMESTER COVER LETTER 149
T POSTCARD REMINDER 150
U THIRD TRIMESTER COVER LETTER 151
REFERENCES 152
BIOGRAPHICAL SKETCH 165
viii

LIST OF TABLES
Table page
2.1 Elicitation and Main Theory of Planned Behavior Study Sample
Characteristics and the Number and Types of Elicitation Beliefs 27
2.2 The Number (N) and Percent (%) of Main Theory of Planned Behavior
and Elicitation Study Characteristics 36
2.3 The Number (N) and Percent (%) of Elicitation Study Behavioral,
Normative, and Control Beliefs 39
3.1 The Number (N) and Percent (%) of Demographic Characteristics for the
Participants 62
3.2 Type, Number (N), and Percent (%) of Beliefs Reported During Pregnancy .... 67
3.3 Type, Number (N), and Percent (%) of Beliefs Reported During Postpartum... 70
4.1 The Number (N) and Percent (%) Demographic Characteristics for the
Participants 90
4.2 Corresponding Demographic Characteristics for the Elicitation Study
Participants and the Main Theory of Planned Behavior Study Participants 92
4.3 Hierarchical Regression Analyses for the Theory of Planned Behavior
Constructs 100
4.4 Correlations, Means (M), and Standard Deviations (SD) Among the
Theory of Planned Behavior Constructs 101
4.5 Number (N), Means (M), Standard Deviations (SD), t-test Mean
Comparisons, and Eta Squared (ri) Values for the Leisure-Time Exercise
Questionnaire (LTEQ) and Body Mass Index (BMI) 102
IX

LIST OF FIGURES
Figure page
1.1 Schematic representation of the theory of planned behavior 4
3.1 Mean Leisure-Time Exercise Questionnaire (LTEQ) total scores for prior
to pregnancy, during pregnancy, and during postpartum 72
3.2 Mean body mass index (BMI) prior to pregnancy and during postpartum 72
3.3 Most salient behavioral advantages of exercising during pregnancy 74
3.4 Most salient behavioral advantages of exercising during postpartum 74
3.5 Most salient normative beliefs of exercising during pregnancy 75
3.6 Most salient normative beliefs of exercising during postpartum 75
3.7 Most salient obstructing control beliefs of exercising during pregnancy 77
3.8 Most salient obstructing control beliefs of exercising during postpartum 77
5.1 Flierarchical conceptualization of perceived behavioral control 120
x

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy in Health and Human Performance
EXAMINING THE PSYCHOSOCIAL DETERMINANTS OF EXERCISE DURING
PREGNANCY USING THE FRAMEWORK OF THE THEORY OF PLANNED
BEHAVIOR: A PROSPECTIVE INVESTIGATION
By
Danielle Symons Downs
August 2002
Chairperson: Dr. Heather Hausenblas
Major Department: Exercise and Sport Sciences
Pregnancy is associated with numerous physical and psychological demands that
may reduce women’s exercise behavior; however, the research examining women’s
behaviors, attitudes, and cognitions during pregnancy is scant. Consequently, there is a
need for research that theoretically examines the determinants of exercising during
pregnancy. The general objective of this dissertation was to examine the predictive utility
of the theory of planned behavior (TPB) in explaining pregnant women’s exercise
intention and behavior. In an attempt to achieve this objective, and adhere to the theory
guidelines established by Ajzen and Fishbein (1980), the following three studies were
conducted:
• Study 1 was a review of 38 TPB elicitation studies with exercise behavior.
• Study 2 was a TPB elicitation study of 74 postpartum women’s beliefs about
exercising during their pregnancy and postpartum.
xi

• Study 3 was a prospective examination of the TPB and 81 pregnant women’s exercise
intention and behavior from their second to their third trimester.
For Study 1, the primary findings for healthy and special populations’ salient
exercise beliefs were: a) physical and psychological health (behavioral beliefs), b) friends
and family (normative beliefs), and c) physical and psychological issues (control beliefs).
For Study 2, the primary findings for women’s salient beliefs about exercising during
their pregnancy were: a) overall mood (behavioral beliefs), b) husband or flaneé
(normative beliefs), and c) physical limitations and restrictions (control beliefs). The
salient beliefs about exercising during postpartum were: a) weight control (behavioral
beliefs), b) husband or fiancé (normative beliefs), and c) no time (control beliefs). For
Study 3, it was found that the TPB was successful in predicting pregnant women’s
exercise intention and behavior. More specifically, intention was the strongest predictor
of pregnant women’s exercise behavior, and perceived behavioral control was the
strongest predictor of their intention from their second to their third trimester.
Implications of the results from all three studies are discussed, as well as future research
directions and practical implications.
xii

CHAPTER 1
INTRODUCTION
Over the past 50 years in the United States, healthcare has been dictated by the
types of diseases that dominate medical expenses and mortality. For example, the leading
causes of death in the 1950s were communicable diseases such as pneumonia and
tuberculosis. However, in the 2000s, chronic behavioral diseases such as cardiovascular
disease and cancer are responsible for the greatest medical expenses and mortality among
American adults (Centers for Disease Control [CDC], 1999; National Center for Health
Statistics [NCHS], 1997). Although advances in medicine and science enable doctors to
manage the communicable diseases of the 1950s, they have not had the same success
with today’s behavioral diseases. Ailments such as atherosclerosis, cancer, diabetes, and
obesity have generated medical expenses in the United States in excess of 95 billion
dollars annually (American Heart Association [AHA], 1997; Twisk, Kemper, & Van
Mechelen, 2000). While some people may have a genetic predisposition for these
illnesses, most chronic behavioral diseases are associated with a variety of lifestyle
factors including smoking, poor diet, and sedentariness (Blair, 1994; Giovannucci et al.,
1995; Mitchell, Almasy, & Rainwater, 1999; NCHS).
People can reduce their risk of chronic diseases by making decisions to adopt
positive lifestyle patterns such as eating balanced diets, having routine physical
examinations, and maintaining healthy body weights (AHA, 1997; Taylor, 1999; Twisk
et al., 2000). Aside from these positive behaviors, engaging in regular physical activity is
1

2
another effective method for alleviating the symptoms associated with many chronic
diseases. For example, regular exercise contributes positively to physical health (e.g.,
lowering heart rate, improving lung capacity, increasing work output) and psychological
well-being (e.g., decreasing anxiety and depression and improving body image; United
States Department of Health and Human Services [USDHHS], 1996, 2000).
Despite the efforts of government sponsored programs (e.g., Healthy People
2010), that aim to increase the number of active individuals, most North Americans are
not engaging in sufficient exercise to experience its health-related benefits (CDC, 1999;
NCHS, 1997; USDHHS, 2000). That is, most people do not meet the guidelines of
engaging in 30 min of accumulated moderate to vigorous physical activity on most, if not
all, days of the week (American College of Sports Medicine [ACSM], 2000; CDC). For
example, 50% of adolescents and young adults ages 12 to 21 are inactive, approximately
60% of adults do not engage in regular physical activity, and 75% of people over the age
of 65 are sedentary (Grove & Spier, 1999; Sullum, Clark, & King, 2000; USDHHS). In
addition, nearly 50% of adults dropout of an exercise program within the first 6 months
(Dishman, 1993). Therefore, in an effort to increase exercise participation, researchers
have advocated the need for conceptually based models of physical activity participation
(Maddux & DuCharme, 1997).
Before the 1980s, studying the psychosocial determinants of exercise behavior
has been data-driven and atheoretical in nature (Rejeski, 1995). In part, this is due to a
lack of theoretical models developed for exercise behavior (Maddux, 1993; Maddux &
DuCharme, 1997). Thus, exercise researchers have borrowed theoretical frameworks
from mainstream psychology to examine the psychological, social, and environmental

3
determinants of exercise behavior (Rimal, 2001). Although many psychological theories
have been applied to exercise behavior, the theory of planned behavior (TPB; Ajzen,
1985, 1988) has emerged as an effective structure for studying the multidimensional (e.g.,
social, cognitive, and behavioral) determinants of exercise participation. Because the
TPB includes many of the same components found in other behavioral models, it offers
researchers a comprehensive framework for understanding and predicting exercise
behavior (Maddux & DuCharme). The purpose of this introduction is to:
• Describe the TPB constructs.
• Discuss scale correspondence.
• Define and explain elicitation studies.
• Provide empirical support for the TPB and its application to exercise behavior.
• Examine the strengths of the TPB.
• Illustrate the importance of examining exercising and pregnancy.
• Briefly describe the three studies conducted for this dissertation.
Theory of Planned Behavior Constructs
The TPB was developed by Ajzen (1988, 1991) as a revision of the theory of
reasoned action (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975). It includes the
following five main constructs: behavior, intention, attitude, subjective norm, and
perceived behavioral control (see Figure 1.1). Associations among the theoretical
constructs is expressed with the following equation: B ~ I = (Aact)wi + (SN)W2 +
(PBC)w3, whereby behavior (B) is affected by intention (I), and Wi, W2, and W3 represent
empirically determined weighing parameters that reflect the influence of attitude (Aact),

4
Figure 1.1. Schematic representation of the Theory of Planned Behavior. Stable
theoretical associations linking attitude (Aact), subjective norm (SN), and perceived
behavioral control (PBC) to intention (I) are represented by the solid arrows, and a direct
relationship linking perceived behavioral control to behavior (B) is represented by the
dashed arrow (adapted from Ajzen, 1991).
subjective norm (SN), and perceived behavioral control (PBC) on people’s intentions
(Ajzen & Madden, 1986).
The primary objective of the TPB is to understand and predict human behavior
based on people's intention to perform or not perform a certain behavior (Ajzen &
Fishbein, 1980). Intention represents a person's strategy for carrying out an action. It is
assumed to resemble how much motivation and effort the individual is planning to exert
to perform a behavior (Ajzen, 1991). A consistent finding in the TPB literature is that
people’s intentions strongly predict their behavior. That is, the stronger one’s intention to
engage in a behavior, the more likely one will perform that behavior. The TPB posits that
people’s intentions are influenced by the following three factors:
• Their attitude about the behavior (i.e., attitude).
• Their perception of the social pressures to perform the behavior (i.e., subjective
norm).

5
• Their beliefs about how easy or difficult it will be to engage in the behavior (i.e.,
perceived behavioral control).
Intention is expected to influence behavior to the extent that people have behavioral
control, and they are motivated to try the behavior. The more positive an individual’s
attitude, subjective norm, or both, and the more salient his or her perceived behavioral
control, the stronger his or her intention is to perform the behavior (Ajzen & Fishbein).
The constructs of attitude, subjective norm, and perceived behavioral control are
described in more detail below.
Attitude is defined as a personal belief toward a behavior. It is a function of the
strength of this association and the perceived consequences of carrying out the behavior
(Ajzen, 1985; Ajzen & Fishbein, 1980). Expressed as the following formula: Aact =
X b x e, attitude (Aact) is the summed product of behavioral beliefs (b) multiplied by
one’s evaluation (e), either positive or negative, of performing the behavior. Behavioral
beliefs are postulated to be the driving force behind people’s attitude, and they are
represented by instrumental beliefs (i.e., benefits and costs of engaging in the behavior),
and affective beliefs (i.e., positive or negative feelings derived from the behavior; Ajzen
& Driver, 1992; Madden, Scholder, & Ajzen, 1992). People’s attitude strongly predicts
their behavioral intention. That is, when people believe that engaging in a behavior will
produce positive outcomes, they are more likely to have a favorable attitude toward it
(Ajzen). People typically have between 5 and 10 readily available beliefs about engaging
in a particular behavior (Godin & Shephard, 1990). For example, the most common
behavioral beliefs about exercise held by healthy populations include both positive (e.g.,
exercising will improve physical and psychological health) and negative (e.g., exercising
will decrease time spent with family and friends) expectations (Carrón, Hausenblas, &

6
Estabrooks, 2003). These beliefs can vary depending on the time and situation, and they
are critical in adopting and maintaining exercise behavior.
Subjective norm (SN) is defined as the perceived social pressures to behave in a
particular way. It is a function of the perceived expectations of significant others (e.g.,
family members, friends, coworkers), and one’s motivation to comply with the requests
of these people (Ajzen & Fishbein, 1980). Expressed in the following formula: SN = I
NB x MC, subjective norm is the summed product of normative beliefs (NB; i.e., whether
important others think a person should or should not engage in a behavior) multiplied by
motivation to comply (MC; i.e., how much the person is compelled to conform with the
request of significant others). People are influenced by significant others to the extent that
they value the opinions of others. For example, if people believe that their spouses want
them to exercise, and they value their spouses’ opinion, their subjective norm for exercise
will be higher, and it will positively influence their intentions (Culos-Reed, Gyurcsik, &
Brawley, 2001). Frequently reported normative beliefs are the expectations of important
individuals (e.g., a spouse, friend, or other family member) and groups (e.g., coworkers,
roommates, church members; Carrón et aL, 2003).
Perceived behavioral control (PBC) reflects how people’s beliefs about their
resources, skills, and opportunities are viewed as underlying behavioral control (Ajzen,
1985, 1988). These facilitating and obstructing factors are referred to as control beliefs
(c), and they interact with a corresponding measure of perceived power (p) in the
expression: PBC = X c x p. Most health-related activities such as smoking, weight
control, and exercise fall along a continuum from total control to complete lack of control
(Godin & Shephard, 1990). For example, people have control when they can decide to

7
perform or not to perform a behavior, and when there are no restrictions for behavior
adoption (Ajzen, 1991). Alternatively, when a behavior requires external resources (e.g.,
money, time, cooperation from others, opportunities, skills) that are absent, people have a
lack of control (Godin, 1994).
Perceived behavioral control has been compared to perceived barriers
(Rosenstock, 1966) and facilitating conditions (Triandis, 1977); however, it is frequently
conceptualized as self-efficacy (Bandura, 1986, 1997). According to Ajzen (1991), self-
efficacy is a belief that one can successfirlly perform a desired behavior, whereas
perceived behavioral control is a person’s perception of the ease or difficulty in
performing a behavior at a specified time. Ajzen (in press) argued that perceived
behavioral control and self-efficacy are conceptually similar; thus, they have the same
mediating role with exercise behavior. That is, perceived behavioral control and self-
efficacy can have direct influences on behavior, and they can impact behavior indirectly
through intention (Ajzen, 1985).
The TPB proposes that behavior can be explained by the combined influences of
the model constructs. However, Ajzen and Fishbein (1980; Ajzen, 1991) argued that four
conditions must be met for the model to accurately predict behavior. First, they proposed
that measures of intention and perceived behavioral control must correspond with the
behavior. For instance, if the behavior is to participate in 30 min of leisure-time physical
activity everyday, then intentions to participate in 30 min of leisure-time physical activity
must be assessed, and perceived behavioral control should be measured accordingly.
Second, Ajzen and Fishbein suggested that the measurement of intention should be as
close in time as possible to the behavior. The longer the time interval, the greater the

8
likelihood that intentions will be affected by external (uncontrollable) factors and
consequently have the potential for change. Third, intentions and perceived behavioral
control must remain stable in the time between their assessment and behavioral
observation. That is, any intervening event that occurs between measuring intention and
behavior may alter people’s intention to perform the behavior. For instance, a person’s
intention to attend a fitness class is measured before the class onset; however, once
exposed to the intensity of the workouts, his or her intentions may change before the
exercise behavior is assessed. Finally, when people’s perceived behavioral control
accurately reflects their perceptions of actual control, the likelihood of predicting
behavior improves (Ajzen). According to Ajzen, the accuracy of the TPB in predicting
and explaining behavior is compromised when researchers fail to adhere to these four
model guidelines.
Scale Correspondence
Scale correspondence is obtained when the items that measure intention and
behavior are consistent with respect to the action, target, context, and time (Ajzen &
Fishbein, 1980; Coumeya & McAuley, 1994). For example, scale correspondence is
achieved if intention is assessed with the item: “I intend to exercise for at least 20
minutes per day for 3 of the next 7 days” and behavior is measured with the item: “I
exercised for at least 20 minutes per day for 3 of the past 7 days.” In contrast, for
example, scale correspondence is not achieved if intention is measured with the item: “I
intend to exercise for at least 20 minutes per day for 3 of the next 7 days” and behavior is
measured with the item: “1 walked more than twice last week.” In this example, the items
assessing intention and behavior do not correspond with respect to their action (i.e.,

9
“exercise” versus “walked”) and their time (i.e., “at least 20 minutes per day for 3 of the
next 7 days” versus “more than twice last week”).
Scale correspondence is important to obtain when predicting behaviors such as
exercise that may vary in action, target, context, and time. For example, a person may
want to run (action) to lose weight (target), and he or she may do so in a variety of
contexts (e.g., at home, around the neighborhood, at the gym) during different parts of the
day (time). Thus, to obtain a better association between intention and behavior, and
improve the predictive utility of the TPB, it is important to specify the same conditions
for the intention and behavior items (Coumeya & McAuley, 1994; Symons Downs &
Hausenblas, 2002). To obtain scale correspondence, Coumeya and McAuley (1993)
suggested that intention and behavior may be assessed with any of the following four
methods:
• Continuous-open (e.g., “1 intend to exercise times during the next three weeks,”
and “I exercised times during the past three weeks”).
• Continuous-closed (e.g., “I intend to exercise during the next 3 weeks the following
number of times: 0-1, 2-4, 5-7, etc.,” and “I exercised during the past 3 weeks the
following number of times: 0-1, 2-4, 5-7, etc.”).
• Dichotomous-ves/no (e.g., “I do do not intend to exercise at least nine times
during the next three weeks,” and “I did did not exercise at least nine times
during the past three weeks”).
• Dichotomous-eraded (e.g., “I intend to exercise at least nine times during the next
three weeks,” and “I exercised at least nine times during the past three weeks”).
While Coumeya and McAuley (1993) recommended that any of the previous
methods can be used to achieve scale correspondence, Coumeya and McAuley (1994)
examined the physical activity behavior of 170 undergraduate students, and they found
that the continuous-open scale produced a larger intention-behavior association than the

10
dichotomous-graded scale (Coumeya & McAuley, 1994). Thus, for the purpose of this
dissertation, a continuous-open scale was used to measure intention and behavior (see
Study 3).
Moreover, Symons Downs and Hausenblas (2002) meta-analytically examined
scale correspondence with 87 TPB and exercise studies, and they found two important
findings. First, scale correspondence was obtained in only 17.5% of the exercise studies
that were reviewed. Second, a larger intention-behavior association was found for studies
with scale correspondence (effect size d = 1.57) compared to studies without scale
correspondence (effect size d = .90). Thus, consistent with previous researchers’
suggestions (e.g., Coumeya & McAuley, 1994; Culos-Reed et al., 2001; Symons Downs
& Hausenblas), researchers applying the TPB to exercise should examine, or at least
acknowledge, scale correspondence. If not, the predictive utility of the TPB is
compromised. Therefore, to be consistent with previous researchers’ recommendations,
scale correspondence was obtained in Study 3 of this dissertation (see Chapter 4).
Elicitation Studies
According to Ajzen and Fishbein (1980), an elicitation study is similar to a pilot
investigation. The purpose of an elicitation study is to determine the behavioral,
normative, and control beliefs of a population. Because the TPB posits that people’s
beliefs are the underlying structure for their attitude, subjective norm, and perceived
behavioral control, Ajzen and Fishbein recommended that an elicitation study be
conducted before the main TPB study (i.e., a study that examines the utility of the TPB
constructs; see Chapter 4 for an example of a main TPB study) to establish the

11
participants’ beliefs about a behavior. To ensure that researchers are conducting
elicitation studies properly, Ajzen and Fishbein established the following four guidelines:
• The elicitation study population and the main TPB study population should be similar
with respect to the participants' demographic characteristics (e.g., type of population,
age, sex, race/ethnicity, and socioeconomic status).
• Open-ended statements are recommended because they allow the participants to
record multiple behavioral, normative, and control beliefs about a behavior (e.g.,
“List the advantages of exercising over the next three months”).
• A content analysis (i.e., a frequency count) is used to rank-order the participants’
beliefs. This can be rank-ordered into higher-order themes (e.g., improving physical
and psychological health) and raw data themes (e.g., keeping fit, maintaining health,
and exercise feels good).
• The 5 to 10 most common behavioral, normative, and control beliefs that emerge
from the participants’ responses are used to develop the beliefs instrument for the
TPB main study.
To determine if elicitation studies impacted the TPB associations, Symons Downs
and Hausenblas (2002) meta-analytically examined their moderating influence with 87
TPB and exercise studies. They found a larger intention-behavior association in main
TPB studies that included an elicitation study (effect size d = 1.32) compared to main
TPB studies without an elicitation study (effect size d = .86). In addition, they found a
larger perceived behavioral control-behavior association for main TPB studies with an
elicitation study (effect size d = .78) compared to main TPB studies without an elicitation
study (effect size d = .34). However, elicitation studies were conducted in only 46.0% of
the main TPB studies examined in the meta-analysis; thus, Symons Downs and
Hausenblas suggested that researchers adhere to the TPB guidelines and conduct an
elicitation study before examining the predictive utility of the model.
In summary, elicitation studies are an important facet of the TPB’s structure, and
the predictive utility of the model is compromised when they are not conducted before

12
the main TPB study (Symons Downs & Hausenblas, 2002). Thus, an elicitation study was
conducted for this dissertation (see Chapter 3) to determine the salient beliefs of pregnant
women, and to develop the beliefs instrument for the main TPB study (see Chapter 4).
Empirical Support for the TPB and Exercise Behavior
Researchers have found that on average, attitude, subjective norm, and perceived
behavioral control explain 40% to 60% of the variance in exercise intentions, and 20% to
40% of the variance in exercise behavior (Culos-Reed et al., 2001). The findings from
narrative (e.g., Blue, 1995; Godin, 1993) and statistical (e.g., Hagger, Chatzisarantis, &
Biddle, 2002; Hausenblas, Carrón, & Mack, 1997; Symons Downs & Hausenblas, 2002)
reviews of the literature provide support for the TPB constructs with exercise behavior.
For example, Godin examined eight TPB studies applied to exercise, and he found that
perceived behavioral control significantly predicted exercise behavior. In addition, he
found that attitude and subjective norm predicted intention; with attitude being the
stronger predictor. Also, Blue reviewed seven TPB studies and she found that:
• Behavioral beliefs were positively associated with attitude in six studies.
• Normative beliefs were positively associated with subjective norm in five studies.
• Attitude predicted intentions in all seven studies.
• Most subjective norm-intention associations were nonsignificant.
• Perceived behavioral control contributed to predicting exercise intention beyond
attitude and subjective norm in five studies.
Moreover, Hausenblas and her colleagues (1997) reviewed 31 studies with over
10,000 participants applying the theories of reasoned action and planned behavior (41.9%
TPB) to exercise. They found large associations between:

13
• Intention and behavior (effect size d = 1.09).
• Perceived behavioral control and behavior (effect size d = 1.01).
• Perceived behavioral control and intention (effect size d = .97).
• Attitude and intention (effect size d = 1.22).
In addition, they found a moderate association between subjective norm and intention
(effect size d = .56)1. The authors concluded that intention had a larger effect on exercise
behavior than perceived behavioral control, and attitude had a larger effect on intention
than perceived behavioral control and subjective norm. Furthermore, although subjective
norm was less associated with intention than attitude and perceived behavioral control,
Hausenblas et al. argued that the influence of people’s subjective norm on their intention
and behavior should not be overlooked.
While the Godin (1993), Blue (1995), and Hausenblas et al. (1997) reviews
contribute to the TPB and exercise literature, two limitations have been identified. First,
Godin and Blue used vote-counting procedures to quantify the literature. More
specifically, they sorted the results of the studies into positive, negative, and
nonsignificant categories, and then analyzed their findings. While there are benefits to
this type of review, this technique’s power decreases as the number of studies included in
the review increases (Hedges & Olkin, 1980). Thus, meta-analytic procedures are
recommended to statistically review the literature because they provide for the integration
of many diverse studies using the full power of statistical methods (Glass, McGraw, &
Smith, 1981).
'The values of .20, .50, and .80 correspond to small, medium, and large effect sizes, respectively,
(Cohen, 1969, 1992).

14
Second, Ajzen (1991) recommended that researchers use hierarchical regression
analysis when examining the predictive utility of the model because this technique is
consistent with the TPB constructs. Because the meta-analysis by Hausenblas et al.
generated a small number of effect sizes (n = 8) examining the complete TPB, these
authors had insufficient power to examine the predictive utility of the TPB with
hierarchical regression procedures2.
Thus, Symons Downs and Hausenblas (2002) conducted an updated meta-analytic
review of the literature with the following two objectives. The first objective was to
examine the strength of the associations among the TPB constructs with exercise
behavior. The second objective was to examine the predictive utility of the TPB with
hierarchical regression analyses. Symons Downs and Hausenblas reviewed 87 studies
that included a total of 20,616 participants and yielded 164 effect sizes, and they found:
• Large associations for:
o Intention and behavior (effect size d = 1.04).
o Attitude and intention (effect size d = 1.06).
o Perceived behavioral control and intention (effect size d = .83).
• Moderate associations for:
o Perceived behavioral control and behavior (effect size d = .52).
o Subjective norm and intention (effect size d = .59).
• For predicting intention:
o Attitude, perceived behavioral control, and subjective norm explained 29% of
the variance in intention.
o Attitude and perceived behavioral control provided unique contributions,
however, subjective norm did not.
o Attitude was the strongest predictor of intention.
Adequate power to conduct the hierarchical multiple regression for a model with 2 predictors is
determined by samples sizes based on power analysis of .80 with 481, 66, and 30 being small,
medium, and large effect sizes, respectively. A model with 3 predictors is based on analysis with
547 (small), 76 (medium), and 35 (large) effect sizes (Green, 1991).

15
• For predicting exercise behavior:
o Intention and perceived behavioral control explained 21% of the variance in
exercise behavior.
intention was the only significant predictor of exercise behavior. These findings support
that people’s attitude is the strongest predictor of their intention, and their intention is the
strongest predictor of their exercise behavior. Symons Downs and Hausenblas concluded
that the TPB provides researchers with a strong conceptual model for explaining exercise
behavior in healthy populations, and that fiirther research is needed examining the utility
of the TPB with populations that are at risk for sedentary behavior.
Importance of Examining Exercise and Pregnancy
Pregnancy is an important time in women’s lives that may place them at greater
risk for decreased physical activity (USDHHS, 2000). For example, Zhang and Savitz
(1996) found that nearly 60% of pregnant women are sedentary. Many women find the
added physiological (e.g., increased cardiac output, body temperature, and respiration)
and psychological (e.g., increased anxiety and depression) demands of pregnancy too
stressful; thus, they decrease or stop exercising during this time (American College of
Obstetricians and Gynecologists (ACOG), 1994; Bungum, Peaslee, Jackson, & Perez,
2000; Carter, Baker, & Brownell, 2000). Despite women’s concerns about exercising
during their pregnancy, it contributes positively to women’s health (USDHHS). In
addition, the ACOG recommends that healthy pregnant women exercise moderately for at
least 15 min per day, 3 to 5 days per week. Thus, to promote physical activity during
pregnancy, it is necessary to examine the determinants of exercising during this time.
Moreover, it is important to study exercising and pregnancy because the literature is
scant, and it is limited by several factors, including:

16
• Small sample sizes (Berg, 1999).
• Few human participant studies (Koniak-Griffin, 1994).
• A lack of theoretical research explaining the determinants of exercising during
pregnancy (Walker, Cooney, & Riggs, 1999).
• Methodological concerns with using nonstandardized exercise measures (Eisen,
Rield, & Larason, 1991).
• Mostly cross-sectional studies (Koniak-Griffin).
Thus, the studies included in this dissertation aimed to improve on the previous exercise
and pregnancy literature by:
• Including pregnant women (i.e., Studies 2 and 3).
• Using a standardized measure of exercise behavior (i.e., Studies 2 and 3).
• Prospectively examining pregnant women’s exercise behavior from their second to
their third trimester (i.e., Study 3)
• Using the TPB framework for understanding and explaining pregnant women’s
exercise behavior (i.e., Studies 1, 2, and 3).
Dissertation Studies
The general objective of this dissertation was to examine the utility of the TPB in
understanding, predicting, and explaining pregnant women’s exercise intention and
behavior. In an effort to adhere to the theory guidelines developed by Ajzen and Fishbein
(1980) and to achieve the general objective of this dissertation, three studies were
conducted. The following section provides a brief overview of each study, followed by a
general description of the final discussion chapter.
1. Study 1 (Chapter 2) is a review of 38 TPB and exercise studies that conducted
an elicitation study before the main TPB study. Elicitation studies are important for two
primary reasons: a) they determine people’s exercise beliefs, and b) they are used to

17
develop the assessment instrument for measuring the TPB constructs in the main TPB
study (Ajzen & Fishbein, 1980). However, the research examining exercise elicitation
studies is scant. Thus, a systematic review of this literature would:
• Identify people’s common behavioral, normative, and control beliefs about exercise.
• Determine researchers methods for determining these beliefs.
• Establish whether exercise beliefs of healthy populations differ from populations that
are at risk for sedentary behavior.
There were two purposes of Study 1. The first purpose was to review the salient
behavioral, normative, and control beliefs of exercise elicitation study participants. The
second purpose was to examine the elicitation study methods (i.e., participants, measures,
and procedures). A detailed list of the reviewed studies is provided describing the study
characteristics and elicited beliefs. In addition, limitations of the reviewed studies are
highlighted, followed by a discussion regarding the need for future research examining
elicitation studies with exercise behavior.
2. Study 2 (Chapter 3) is a TPB elicitation study of postpartum women’s beliefs
about exercising during their pregnancy and postpartum. Because of the limited number
of studies examining the TPB and exercise with pregnant populations, the methodological
concerns regarding these studies, and the lack of elicitation studies in the literature, the
study objective was to conduct a retrospective investigation of women’s beliefs about
exercising during pregnancy and postpartum (K. S. Coumeya, personal correspondence,
2002). The main study purpose was to determine the frequency of women’s behavioral,
normative, and control beliefs for exercising during pregnancy and postpartum. The
findings regarding the type and number of elicited beliefs are discussed. Consistent with
the TPB guidelines (Ajzen & Fishbein, 1980), the salient beliefs emerging from Study 2

18
were used to form the assessment instrument that was used in the prospective study of the
TPB and exercising during pregnancy (i.e., Study 3).
3. Study 3 (Chapter 4) is a prospective study of the TPB constructs and exercising
from pregnant women’s second to their third trimester. Because pregnancy can promote
decreased physical activity (e.g., Zhang & Savitz, 1996), it is important to examine the
determinants of exercising during pregnancy. In addition, because few TPB studies have
included populations that are at risk for sedentary behavior, and because no located
studies have examined the TPB constructs and exercising from pregnant women’s second
to their third trimester, a prospective study was warranted. The general study purposes
were to prospectively examine the utility of the TPB in predicting pregnant women’s
exercise intention and behavior from their second trimester to their third trimester, and to
examine the associations among the TPB constructs. The findings from hierarchical
multiple regressions, correlations, and dependent t-tests are discussed.
4. The general discussion (Chapter 5) includes:
• The composite findings from Studies 1, 2, and 3.
• A general overview of the strengths and limitations of these studies.
• Recommendations for future research with the TPB constructs, exercise behavior, and
pregnant populations.
• Practical implications of this dissertation.

CHAPTER 2
STUDY 1: THE THEORY OF PLANNED BEHAVIOR AND
ELICITATION STUDIES: A SYSTEMATIC REVIEW OF EXERCISE BELIEFS
An important element for promoting health-related physical activity is applying
theoretical models that can identify and explain the multidimensional (e.g., social,
cognitive, behavioral) determinants of exercise participation (Biddle & Nigg, 2000;
Rimal, 2001). Despite the number of psychological theories available, no consensus
exists regarding which is the best model for studying exercise behavior (Maddux &
DuCharme, 1997). However, one conceptual framework that has been successfully
applied to exercise behavior is the theory of planned behavior (TPB; Ajzen, 1988, 1991;
Ajzen & Fishbein, 1980). The TPB is a belief-based social cognitive theory whereby
people’s expectations about engaging in a behavior (and the values attached to it) form
their behavioral, normative, and control beliefs toward the behavior. These beliefs in turn,
influence people’s attitude (i.e., feelings and perceived consequences of a behavior),
subjective norm (i.e., normative influences and motivation to comply with expectations
of others), and perceived behavioral control (i.e., feelings and personal control for the
facilitating and obstructing factors of behavior adoption) toward their intention, and
ultimately, their behavior (Ajzen).
Behavioral beliefs are posited to be the driving force behind people’s attitude.
They are determined by people’s perceived consequences (either positive or negative) of
engaging in a behavior, and their personal evaluation of each of these consequences
(Ajzen & Fishbein, 1980). For example, people may believe that exercising will improve
19

20
their health and help them to control their weight. However, they may also feel that it is
time consuming and painful. On average, people have 5 to 10 beliefs about engaging in
exercise behavior (Ajzen & Driver, 1991; Godin & Shephard, 1990). For healthy
populations, Carrón et al. (2003) reported that the most common behavioral beliefs are
that exercise:
• Improves physical and psychological health.
• Improves physical appearance.
• Is fun and enjoyable.
• Is time consuming.
• Is tiring.
Normative beliefs provide the framework for subjective norm, and they are
formulated by whether important others (e.g., friends, family) think people should or
should not engage in a behavior, and people’s motivation to comply with the wishes and
desires of these significant others (Ajzen, 1985). People are influenced by significant
others to the extent that their opinions are valued. For example, if a woman believes that
her spouse wants her to exercise during pregnancy, and she values her spouse’s opinion,
her subjective norm for exercise will be higher. The most frequently reported normative
beliefs regarding exercise in healthy populations are individuals (e.g., friend, spouse, or
other family member) and groups (e.g., coworkers, roommates, church members; Carrón
et al., 2003).
Control beliefs provide the structure for perceived behavioral control. They are
developed from people’s evaluation of how easy or difficult behavior adoption will be,
and from people’s perceived power of the control beliefs facilitating or inhibiting the

21
behavior (Ajzen, 1991). Control beliefs represent people’s personal beliefs about the
facilitating and obstructing factors of behavior adoption, and they include their personal
resources, skills, and opportunities. According to Ajzen, the more resources and
opportunities that people believe they have (e.g., I have free time on Saturday to go to the
gym), and the fewer obstacles they anticipate (e.g., I can have mom watch the kids), the
greater their perception of control is for engaging in the behavior (e.g., even if mom can’t
watch the kids, 1 can take them to the gym and let them play in the children’s area). The
most common control beliefs for exercise in healthy populations are lacking time, energy,
and motivation (Carrón et al., 2003).
The TPB postulates that people’s beliefs influence their attitude, subjective norm,
and perceived behavioral control, which in turn, influence their intention and behavior
(Ajzen, 1991). The findings from several narrative (e.g., Blue, 1995; Godin, 1993) and
statistical (e.g., Hagger et al., 2002; Hausenblas et al., 1997; Symons Downs &
Hausenblas, 2002) reviews of the literature provide support for the TPB constructs with
exercise behavior. For example, Symons Downs and Hausenblas meta-analytically
examined 87 TPB and exercise studies, and they found: a) large associations for intention
and behavior (effect size d = 1.04), attitude and intention (effect size d = 1.06), and
perceived behavioral control and intention (effect size d = .83); and b) moderate
associations for perceived behavioral control and behavior (effect size d = .52) and
subjective norm and intention (effect size d = .59). In addition, they reported that attitude,
perceived behavioral control, and subjective norm explained 29% of the variance in
exercise intention; with attitude and perceived behavioral control providing unique
contributions in predicting intention. Also, intention and perceived behavioral control

22
explained 21% of the variance in exercise behavior, with intention emerging as the only
significant predictor. These findings support that people’s attitude most strongly predicts
their intention, and their intention most strongly predicts their exercise behavior.
Despite the TPB’s predictive success, the utility of the model is compromised
when researchers fail to adhere to the theory guidelines developed by Ajzen and Fishbein
(1980; Fishbein & Ajzen, 1975). As a result, several conceptual and methodological
issues have emerged with the TPB and exercise literature (Culos-Reed et al., 2001). A
main methodological concern is the limited use of elicitation studies (Symons Downs &
Hausenblas, 2002). According to Ajzen and Fishbein, the purpose of an elicitation study
is to determine the behavioral, normative, and control beliefs of a population. For
example, if researchers want to study the TPB constructs for cancer patients, they should
first conduct an elicitation study with a subsample of the population to determine cancer
patients’ behavioral, normative, and control beliefs about exercise (e.g., Coumeya &
Friedenreich, 1997, 1999). To determine a population’s salient beliefs, Ajzen and
Fishbein recommended that researchers adhere to the following three steps:
• Conduct an elicitation study with open-ended questions assessing a population’s
behavioral, normative, and control beliefs.
• Perform a content analysis (i.e., a frequency count) on the results from the elicitation
study to rank-order the beliefs of the population.
• Determine the 5 to 10 most salient beliefs of the population.
Once these beliefs are established, researchers can then conduct a follow-up study (i.e.,
the main TPB study) to measure the TPB constructs (i.e., behavioral, normative, and
control beliefs, attitude, subjective norm, perceived behavioral control), and to determine
which of these theoretical tenets predict the sample’s exercise intention and behavior.

23
While Ajzen and Fishbein (1980) suggested that researchers perform elicitation
studies before the main TPB study, most TPB and exercise studies are conducted without
them. For instance, Symons Downs and Hausenblas (2002) found that less than half of
the studies reviewed in their meta-analysis conducted an elicitation study before the main
TPB study. In addition, the authors found that the main TPB studies without elicitation
studies had smaller intention-behavior (effect size d = .86) and perceived behavioral
control-behavior (effect size d = .34) associations compared to the main TPB studies with
elicitation studies (effect sizes d = 1.32 and .78, respectively). Also, there was a
nonsignificant trend for smaller subjective norm-intention and perceived behavioral
control-intention associations in studies without elicitation studies. These findings
illustrate two limitations of the TPB and exercise literature. First, researchers
are not properly adhering to the TPB guidelines. Second, the utility of the TPB is
compromised when elicitation studies are not performed.
Thus, research examining elicitation studies is warranted for at least two reasons.
First, it is important to identify the salient exercise beliefs of a variety of populations
because not all people share the same thoughts, feelings, and ideas about exercise. For
example, researchers have reported the most common exercise beliefs of healthy
populations (Carrón et al., 2003), however, it is unclear whether those beliefs represent
the salient exercise beliefs of special populations (e.g., elderly, pregnant women, obese).
Because these populations are at risk for sedentary behavior, it is necessary to examine
their behavioral, normative, and control beliefs about physical activity to identify the
factors that may assist researchers with increasing their exercise behavior.

24
Second, it is important to examine the methods (i.e., participants, measures, and
procedures) of elicitation studies that have been conducted with exercise behavior
because the utility of the TPB can be compromised by inadequate methods (e.g., lack of
correspondence between the elicitation sample and the main TPB sample, not following
the TPB guidelines for elicitation studies). More specifically, if the elicitation study
sample and the main TPB sample do not correspond with respect to their demographic
characteristics (e.g., type of population, M age or age range, sex, race/ethnicity, socio¬
economic status), then the beliefs that emerge from the elicitation study participants may
not represent the main TPB participants. For example, if researchers examining the TPB
and exercise behavior conduct an elicitation study with a sample of Caucasian, middle-
class, pregnant women, then the main TPB study participants should also be Caucasian,
middle-class, pregnant women. Alternatively, if the elicitation study was conducted with
Caucasian, middle-class, pregnant women, and the main TPB study was conducted with
African American, lower-class pregnant women, the salient exercise beliefs of these
populations are likely to be different (USDHHS, 2000). Then, researchers are assessing
the beliefs of one population, and measuring the attitude, subjective norm, and perceived
behavioral control of another population. Thus, there is a lack of correspondence between
the elicitation and main TPB study participants, and the utility of the TPB is
compromised (Ajzen).
In addition, because inadequate measures and procedures can compromise the
utility of the TPB, it is also important to examine these components of exercise elicitation
studies. As previously stated, Ajzen and Fishbein (1980) established guidelines for
conducting elicitation studies, and they have suggested that the predictive utility of the

25
TPB is improved when researchers follow these procedures (e.g., using open-ended
statements to elicit the beliefs, performing a content analysis, rank-ordering the beliefs).
However, because there is a paucity of information regarding exercise elicitation study
methods, more research is warranted that examines these characteristics.
The primary study purpose was to review the salient behavioral, normative, and
control beliefs of exercise elicitation study participants. The secondary study purpose was
to examine the elicitation and main TPB studies’ methods (i.e., participants, measures,
and procedures) in an attempt to determine if there was correspondence between the
elicitation and main TPB study participants, and to determine how the elicited beliefs
were obtained. Correspondence was defined as when the same participant characteristics
(i.e., population type, sex, M age or age range, race/ethnicity, and socioeconomic status)
were reported for both the elicitation and main TPB studies (Ajzen, 1991).
Method
Selection and Inclusion of the Studies
Eighty-seven TPB and exercise studies from the Symons Downs and Hausenblas
(2002) meta-analysis were reviewed to see if they met the inclusion criteria of having an
elicitation study conducted before the main TPB study. Based on this inclusion criterion,
38 main TPB studies with elicitation studies were selected for this review. The main TPB
studies reviewed had 11,936 total participants (N range = 30 to 3,719 participants), and
the elicitation studies had 1,488 total participants (N range = 8 to 245 participants).
Review Procedures
The elicitation study characteristics reviewed were participant characteristics
(i.e., the number of participants, type of population, M age or age range, sex,

26
race/ethnicity, and socioeconomic status), and the number and type of elicited behavioral,
normative, and control beliefs. The main study characteristics reviewed were year,
publication format, participant characteristics (i.e., the number of participants, type of
population, M age or age range, sex, race/ethnicity, and socioeconomic status), and type
of behavior (i.e., exercise, running, walking).
Data Analysis
Following the procedures of previous researchers (i.e., Creswell, 1994; Jackson,
1992; Patton, 1980; Tesch, 1990), a five-step procedure was used to examine the type of
exercise beliefs. First, behavioral, normative, and control belief categories were
established. Second, raw data themes were identified from the reviewed studies. Third,
the raw data themes were organized into higher-order themes based on inductive and
deductive procedures. Specifically, the inductive procedure was used to identify the
higher-order belief themes from the compiled list of raw data themes. The deductive
procedure was used to re-examine the themes to ensure that they made intuitive sense,
and to make certain that all of the raw data themes had been placed into the appropriate
higher-order themes. Fourth, a reliability check of the raw data and higher-order themes
was performed by a TPB expert. Finally, the most salient exercise beliefs were identified
(e.g., the 5 to 10 most common beliefs; Ajzen & Fishbein, 1980; Godin & Shephard,
1990). In addition, I coded the following information: a) frequency of beliefs; b) studies
that examined exercise beliefs but failed to describe them in detail; and c) studies that did
not examine behavioral, normative, or control beliefs. A detailed list of the studies
included in this review are located in Table 2.1.

Table 2.1
Elicitation and Main Theory of Planned Behavior Study Sample Characteristics, and Number and Types of Elicitation Beliefs
Author (Year)
Elicitation Study
Sample Characteristics
Main Study Sample
Characteristics
Behavioral Beliefs (BB)
Normative Beliefs (NB)
Control Beliefs (CB)
Ajzen & Driver
(1991)
N = 27 undergraduate
male and female
students (M age =
N.A.), SES = N.A.,
race/ethnicity = N. A.
N = 43 male and 103 female
undergraduate students (M
age = 20.1 years), SES =
middle to upper class,
race/ethnicity = N.A.
N = N.A.
BB were elicited but not described
N = N.A.
NB were elicited but not
described
N = N.A.
CB were elicited but not
described
Backman
(1999)*
N = 25 male and female
adolescents (age range
= 14-19 years, M age =
N.A.), SES = N.A.,
race/ethnicity =
Hispanic, Caucasian,
and African American
N = 338 male and 426
female adolescents (age
range = 14-19 years, M age
= N.A), SES = N.A.,
race/ethnicity = Hispanic
(35.7%), Caucasian (28.6%),
and African American
(14.2%)
N = 8
Stay in shape, feel healthy and good
about self, controls weight and diet,
increases energy, athletic
performance, experience pain and
soreness, tired
N = 6
Parents, siblings, friends,
coach,teacher
N = 6
Lacking time, money,
motivation, support
encouragement, exercise
knowledge, and access to
exercise equipment or school
physical activity programs
Bergen
(1996)*
N = 14 male and 11
female chronic pain
patients (M age = 41.6
years), SES = lower to
middle class,
race/ethnicity =
Caucasian, African
American, and Hispanic
N = 51 male and 39 female
chronic pain patients (M age
= 45.6 years), SES = lower
to middle class,
race/ethnicity = Caucasian
(68.9%) and African
American (27.8%)
N = 7
BB were elicited but not described
N = 5
NB were elicited but not
described
N = 8
CB were elicited but not
described
Blissmer
(1997)*
N = 40 male and female
undergraduate students
(M age = N.A.), SES =
N.A., race/ethnicity =
Caucasian
N = 81 male and 92 female
undergraduate students (age
range = 18-24 years, M age
= 19.8), SES = N.A.,
race/ethnicity = Caucasian
(88%)
not elicited
not elicited
N = 7
Perceived barriers = lacking
time, motivation, and energy,
facility too far away and too
crowded, no exercise partner,
other commitments, poor
weather

Table 2.1 Continued
Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics
Blue (1996)*
N = 21 male and female
worksite employees (M
age = N.A.). SES =
N.A., race/ethnicity =
Caucasian
N = 344 male and 109
female worksite employees
(M age = 43.2 years), SES =
N.A., race/ethnicity =
Caucasian (94.5%)
N = 12
Improves health, feel better, controls
weight, improves muscle tone,
increases energy, promotes
relaxation, increases risk of injury,
illness, and sore muscles, too tired,
too time consuming, interferes with
family and other commitments
N = 7
Spouse or girl/boyfriend,
other family members,
coworkers, boss, friends,
physician, nurse
N = 7
Having an exercise partner,
fun and enjoyable,
convenient, had a reminder,
nice weather, inexpensive,
lacking time
Bozionelos &
Bennett (1999)
N = 20 undergraduate
male and female
students (M age =
N.A.), SES = N.A.,
race/ethnicity = N.A.
N = 58 male and 56 female
undergraduate students (M
age = 22.0 years), SES =
N.A., race/ethnicity = N.A.
N = N.A.
BB were elicited but not described
N = N.A.
NB were elicited but not
described
N = N.A.
CB were elicited but not
described
Brenes, Strube,
& Storandt
(1998)
N = 35 male and female
older adults (M age =
71.2 years), SES =
N.A., race/ethnicity =
Caucasian (86.0%) and
African American
(3.0%)
N = 12 male and 93 female
older adults (M age = 68.3
years), SES = N.A.,
race/ethnicity = Caucasian
(66.0%) and African
American (31.1%)
N = 7
Controls weight, feel better,
increases flexibility, improves
muscle tone, energy, health, and
cardiovascular system
N = 4
Spouse or girl/boyfriend,
children, friends,
physician
N = 4
Experiencing illness or
health problems, lacking
time, energy, and motivation
Coumeya
(1995)
N = 30 male and female
older adults (age range
= 60 years and older, M
age = N.A.), SES =
lower-middle class,
race/ethnicity = N.A.
N = 288 male and female
older adults (63% female, M
age = 71.5 years), SES =
lower-middle class,
race/ethnicity = N.A.
N = 7
Improves muscular strength and
tone, improves mental health, feel
better, increases energy level,
muscle strength, and tone, lose
weight, provides opportunity to
socialize
Not elicited
N = 7
Experiencing pain or health
problems, other
commitments, feeling lazy or
unmotivated, bad weather,
too expensive, lacking access
to facilities
Courneya &
Friedenreich
(1997)
N = 24 male and female
cancer patients (M age
= N.A.), SES = middle
class, race/ethnicity =
N.A.
N = 69 male and 41 female
cancer patients (M age =
60.9 years), SES = middle
class, race/ethnicity = N.A.
N = 8
Get mind off cancer treatment, feel
better, improves well-being,
maintain normal lifestyle, cope with
stress, gain control over life, recover
from surgery, controls weight
N = 5
Spouse or girl/boyfriend,
other family members,
friends, physician, other
people with cancer
N = 6
Experiencing illness, nausea,
fatigue, tiredness, pain, and
soreness, no counseling for
exercise, no time and support

Table 2.1 Continued
Author (Year)
Elicitation Study
Sample Characteristics
Main Study Sample
Characteristics
Behavioral Beliefs (BB)
Normative Beliefs (NB)
Control Beliefs (CB)
Courneya &
Friedenreich
(1999)
N = 24 female breast
cancer patients (age range
- less than 70 years, M
age = N.A.), SES =
middle -upper class,
race/ethnicity = N.A.
N = 164 female breast cancer
patients (M age = 53.0
years), SES = middle- upper
class, race/ethnicity = N.A.
N = 8
Get mind off cancer treatment, feel
better, improves well-being,
maintain normal lifestyle, cope with
stress, gain control over life, recover
from surgery, weight loss
N = 5
Spouse or girl/boyfriend,
other family members,
friends, physician, other
people with cancer
N = 7
Experiencing illness, nausea,
fatigue, tiredness, pain, and
soreness, had to work, no
counseling for exercise, no
time and support
Cowell
(1996)*
N = 26 female
undergraduate students
(age range = 20-43 years,
M age = 30.9 years), SES
= N.A., race/ethnicity =
Caucasian only
N= 199 female
undergraduate students (age
range = 20-45 years, M age
= 29.9 years), SES = N.A.,
race/ethnicity = Caucasian
only
N = 3
Improve muscle tone and strength,
control weight, improves
cardiovascular fitness
N = 4
Spouse or girl/boyfriend,
other family members,
physician, athletes
N = 3
Experiencing injury, not
enough time, feeling lazy
Daltroy &
Godin
(1989a)
N = 28 male and female
spouses of cardiac
patients (M age = N.A.),
SES = N.A.,
race/ethnicity = N.A.
N = 13 male and 121 female
spouses of cardiac patients
(M age = 53.5 years), SES =
N.A., race/ethnicity = N.A.
N = 5
Increases energy, more positive
outlook on life, improves health,
inconvenient for spouse, changes
mealtime
Not elicited
Not elicited
Dawson,
Brawl ey,
& Maddux
(2000)
N = N.A. male and
female community adults
(M age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 20 male and 96 female
community adults (M age =
27.0 years), SES = N.A.,
race/ethnicity = N.A.
Not elicited
Not elicited
N = N.A.
CB were elicited but not
fully described
Deyo (1984/
N = N.A. fitness class
participants (sex = N.A.,
M age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 187 fitness class
participants (68.4% female,
M age = 34.8 years); SES =
middle class; race/ethnicity =
N.A.
N = N.A.
BB were elicited but not described
N = N.A.
NB were elicited but not
described
Not elicited

Table 2.1 Continued
Author (Year)
Elicitation Study
Sample Characteristics
Main Study Sample
Characteristics
Behavioral Beliefs (BB)
Normative Beliefs (NB)
Control Beliefs (CB)
Doyl e-Baker
N = 10 patients with
N = 4 male and 137 female
N= 10
N = 7
N = 7
(2000)“
fibromyalgia (sex =
N.A., M age = N.A.),
SES = N.A.,
race/ethnicity = N.A.
patients with fibromyalgia
(M age = 48.6 years); SES =
N.A.; Race/Ethnicity =
Anglo Canadian (57.4%),
European (16.3%), and
Caucasian (12.8%)
Reduces disease symptoms, more
positive life outlook, improves self-
confidence, body image, and sleep,
perform routine tasks more easily,
increases energy for family, return
to work, decreases stress, too tired
Spouse or girl/boyfriend,
other family members,
physician, physical
therapist, other health care
workers, boss, minister or
church official
Lacking time, money, fitness
counseling, transportation,
and exercise knowledge,
having previous exercise
experience
Dzewaltowski
(1989)
N = 55 male and female
undergraduate students
(M age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 136 male and 192
female undergraduate
students (M age = N.A.),
SES = N.A., race/ethnicity =
N.A.
N = 13
BB were elicited but not described
N = N.A.
NB were elicited but not
described
Not elicited
Godin, Cox, &
Shephard
(1983)
N = 55 male and female
adults (M age = N.A.);
SES = N.A.;
race/ethnicity = N.A.
N = 172 male and female
adults (M age = 31.1 years),
SES = N.A., race/ethnicity =
N.A.
N = 11
BB were elicited but not described
N = 3
NB were elicited but not
described
Not elicited
Godin,
Deshamais,
Valois, Lepage,
Jobin, & Bradet
(1994)
(Sample 1)
N = 51 male and female
community adults, SES
= N.A., race/ethnicity =
N.A.
N= 130 male and 219
female community adults (M
age = 38.1 years), SES =
N.A., race/ethnicity = N.A.
Not elicited
Not elicited
N = 5
Perceived barriers = lacking
access to facilities, money,
time, and an exercise partner,
health problems
Godin,
Deshamais,
Valois, Lepage,
Jobin, & Bradet
(1994)
(Sample 2)
N = 45 male and female
cardiovascular disease
patients, SES = N.A.,
race/ethnicity = N.A.
N = 137 male and 25 female
cardiovascular disease
patients (M age = 56.6
years), SES = N.A.,
race/ethnicity = N.A.
Not elicited
Not elicited
N = 10
Perceived barriers = lacking
time, access to facility, and
an exercise partner, age,
experiencing heart pain, fear
of another heart attack,
psychological difficulties
adapting to life after heart
problems, physician’s
counter-indication, laziness

Table 2.1 Continued
Author (Year)
Elicitation Study
Sample Characteristics
Main Study Sample
Characteristics
Behavioral Beliefs (BB)
Normative Beliefs (NB)
Control Beliefs (CB)
Godin,
Deshamais,
Valois, Lepage,
Jobin, & Bradet
(1994)
(Sample 3)
N = 47 postpartum
females (M age =
N.A.), SES = N.A.,
race/ethnicity = N. A.
N = 139 pregnant females
(M age = 27.3 years); SES =
N.A., race/ethnicity = N.A.
Not elicited
Not elicited
N = 6
Perceived barriers = lactation
constraints, lacking time and
support from husband,
experiencing physical health
problems after birth, baby’s
physical health problems,
psychological problems
adapting to life after birth
Hagger, Cale,
& Almond
(1997)
N = N.A. male and
female primary school
children (age range = 9-
11 years, M age =
N.A.), SES = middle
class, race/ethnicity =
N.A.
N = 25 male and 19 female
primary school children (age
range = 9-11 years, M age =
N.A.), SES = middle class,
race/ethnicity = N.A.
N = 6
Feel healthy and better, fim and
enjoyment, make friends, increases
risk of injury, too much effort
N = 5
Parents, grandparents,
other family members,
friends, teachers
Not elicited
Helm (1987)a
N = 18 male and female
older adults (age range
= 60-94, M age = N. A.),
SES = retired,
race/ethnicity =
Caucasian
N = 89 male and 165 female
older adults (age range = 60-
94, M age = 74 years), SES
= retired, race/ethnicity =
Caucasian
N = 10
Increases flexibility, feel better and
more healthy, improves circulation,
alertness, and mental health,
controls weight, aggravates physical
condition, overexertion, time
consuming, messy
N = 9
Spouse or girl/boyfriend,
other family members
(i.e., sister, brother,
daughter, son, grandchild,
spouse of child), friends,
physician
Not elicited
Kemer &
Grossman
(1998)
N = N.A. fitness center
personnel (sex = N.A.,
age range = 20-67
years, M age = N.A.),
SES = middle-upper
class, race/ethnicity =
N.A.
N = 50 male and 23 female
fitness center personnel (age
range = 20-67 years, M age
= 44.7 years), SES = middle-
upper class, race/ethnicity =
N.A.
N = N.A.
BB were elicited but not described
N = N.A.
NB were elicited but not
described
Not elicited

Table 2.1 Continued
Author (Year) Elicitation Study Main Study Sample
Sample Characteristics Characteristics
Kimiecik
(1992)
N = 30 worksite
employees (sex = N.A.,
M age = N.A.); SES =
middle-upper class;
race/ethnicity = N.A.
N = 176 male and 154
female worksite employees
(M age = 39.1 years), SES =
middle-upper class,
race/ethnicity = N.A.
Legg(1987)a
N = 73 male and 63
female undergraduate
students (age range =
18-54 years, M age =
N.A.), SES = N.A.,
race/ethnicity = N.A.
N= 15 male and 15 female
undergraduate students (age
range = 18-54 years, M age
= N.A.), SES = N.A.,
race/ethnicity = N.A.
Michels &
Kugler (1998)
N = N.A. male and
female older adults (age
range = 65-70 years, M
age = N.A.), SES =
upper middle class,
race/ethnicity = N.A.
N = N.A. male and female
older adults (age range = 65-
70 years, M age = N.A.),
SES = upper middle class,
race/ethnicity = Caucasian
(90.8%)
Mummery,
Spence, &
Hudec (2000)
N = N.A. children (sex
= N.A., age range = 8-
16 years, M age =
N.A.), SES = N.A.,
race/ethnicity = N.A.
N = 746 male and female
adolescents: N = 63 3rd
graders (M age = 8.2 years),
N = 139 5th graders (M age =
10.3 years), N= 191 8th
graders (M age = 13.9
years), N = 184 11th graders
(M age = 16.4 years), SES =
N.A., race/ethnicity = N.A.
Norman &
Smith (1995)
N = 18 male and female
undergraduate students
(M age = N.A.), SES =
N.A., race/ethnicity =
N = 83 male and female
undergraduate students (M
age = N.A.), SES = N.A.,
race/ethnicity = N.A.
N.A.
Behavioral Beliefs (BB)
Normative Beliefs (NB)
Control Beliefs (CB)
N = 6 N = 3
BB were elicited but not described NB were elicited but not
described
N = 7
CB were elicited but not
described
N = 15
Feels good, improves health, self-
image, reflexes, concentration, and
cardiovascular fitness, meet new
people, increases energy, controls
weight, time, relieves stress, tired,
sore muscles, expensive
N = 4
Spouse or girl/boyfriend,
parents, physician, friends
Not elicited
N = 4
N = 4
N = N.A.
Improves health, increases energy
Spouse or girl/boyfriend,
CB were elicited but not
level, controls weight, decreases
joint stiffness, causes pain
friends, physician, media
described
N = N.A.
N=N.A.
N = N.A.
BB were elicited but not described
NB were elicited but not
described
CB were elicited but not
described
N = 7
BB were elicited but not fully
described (e.g., improves agility and
suppleness)
N = 4
Other family members,
friends, media, people
who exercise regularly
N = 7
Lacking time, other
commitments, feeling tired
and lazy, too much effort,
too far from facilities,
experiencing pain and
soreness

Table 2.1 Continued
Author (Year) Elicitation Study Main Study Sample Behavioral Beliefs (BB) Normative Beliefs (NB) Control Beliefs (CB)
Sample Characteristics Characteristics
Pender &
Pender(1986)
N = 100 community
adults (sex = N.A., age
range = 18 years and
older, M age = N.A.),
SES = N.A.,
race/ethnicity = N.A.
N = 377 male and female
community adults; 60%
female (M age = 38.0 years),
SES = middle class,
race/ethnicity = Caucasian
N = N.A.
BB were elicited but not fully
described (e.g., controls weight,
cope with stress)
N = 6
Spouse or girl/boyfriend,
children, parents or close
older relative, friends,
coworkers, physician
Not elicited
Rahilly (1994)“
N = 11 females (age
range = 21-50 years, M
age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 88 females (age range =
21-50 years, M age = 34.7
years), SES = N.A.,
race/ethnicity = N.A.
N = N.A.
BB were elicited but not described
N = N.A.
NB were elicited but not
described
Not elicited
Riddle (1980)
N = 40 male and female
exercisers (age range =
30 years and older, M
age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 198 male and 98 female
exercisers (age range = 30
years and older, M age =
N.A.), SES = N.A.,
race/ethnicity = N.A.
N = 19
BB were elicited but not described
N = 7
NB were elicited but not
described
Not elicited
Schlapman
(1994)a
N = 22 male and 44
female older adults (M
age = 44.6 years), SES
= N.A., race/ethnicity =
N.A.
N= 135 male and 296
female older adults (M age =
62.0 years), SES = retired,
race/ethnicity = Caucasian
N = 9
Improves physical and mental
health/fitness, feels good, lowers
blood pressure, controls weight,
socializing, good exercise, wears on
bones and joints
N = 6
Spouse or girl/boyfriend,
children, parents, friends,
physician, coworkers
N = 9
Having a walking partner,
mall meetings and programs,
contests and incentives,
lacking time, motivation, and
access to a facility to walk
indoors, experiencing illness
and injury, other
commitments
Schmelling
(1985)
N = 40 male and female
university faculty and
staff (age range = 30-55
years, M age = N.A.),
SES = N.A.,
race/ethnicity = N.A.
N = 135 male and female
university faculty and staff
(58.5% male, age range =
30-55 years, M age = N.A.),
SES = N.A., race/ethnicity =
N.A.
N= 17
Increases energy, stronger heart and
lungs, improves health, strength,
body appearance, appetite, and
alertness, feel better about self, more
relaxed and structured day, controls
weight, time consuming, aggravates
health condition, muscle aches, and
injuries, too tired, daily interference
N = 4
Spouse or girl/boyfriend,
other family members,
friends, boss, coworkers
Not elicited

Table 2.1 Continued
Author (Year)
Elicitation Study
Sample Characteristics
Main Study Sample
Characteristics
Behavioral Beliefs (BB)
Normative Beliefs (NB)
Control Beliefs (CB)
Sheeran &
Orbell (2000)
Smith & Biddle
(1999) Study 1
N = N.A. undergraduate
students (sex = N.A., M
age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 7 male and 7
female health club
members (age range =
18 years and older. M
age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N= 163 undergraduate
students (sex = N.A., M age
= N.A.), SES = N.A.,
race/ethnicity = N.A.
N = 44 male and 51 female
health club members (M age
= 34.0 years), SES = middle
class, race/ethnicity =
Caucasian
N = N.A.
BB were elicited but not described
N = N.A.
BB were elicited but not described
N = N.A.
NB were elicited but not
described
N = N.A.
NB were elicited but not
described
N = N.A.
CB were elicited but not
described
Not elicited
Smith & Biddle
(1999) Study 2
N = 4 male and 4
female worksite
employees (M age =
N.A.), SES = N.A.,
race/ethnicity = N.A.
N = 74 male and 67 female
worksite employees (M age
= 36.0 years), SES = middle
class, race/ethnicity =
Caucasian
N = N.A.
BB were elicited but not described
N =N.A.
NB were elicited but not
described
Not elicited
Terry &
O’Leary (1995)
N = 25 male and 31
female undergraduate
students (M age = 20.3
years), SES = N.A.,
race/ethnicity = N.A.
N = 73 male and 73 female
undergraduate students (M
age = 20.2 years), SES =
N.A., race/ethnicity = N.A.
N = 12
BB were elicited but not fiilly
described (e.g., tired, improves
physical fitness)
N = 3
Spouse or girl/boyfriend,
parents, friends
N = N.A.
CB were elicited but not
described
Theodorakis
(1994)
N = 120 female fitness
class participants (age
range = 18-45 years. M
age = N.A.), SES =
N.A., race/ethnicity =
N.A.
N = 395 female fitness class
participants (age range = 18-
45 years, M age = 29.3
years), SES = N.A.,
race/ethnicity = N.A.
N = 13
BB were elicited but not described
N = 5
Spouse or boyfriend, other
femily members, friends,
exercise leader
N = 9
CB were elicited but not
described
Note. ‘ = thesis or dissertation; N = number; M = mean; SES = socioeconomic status; N.A. = not available.

35
Results
Elicitation Study Characteristics
Table 2.2 displays a summary of the elicitation and main study characteristics.
The elicitation study participants ranged in age from 20.1 to 71.2 years (M age = 39.1
years, SD = 16.7). Most of the studies examined males and females (71.1%). The
participants were undergraduates (23.7%), worksite employees (13.2%), older adults
(13.2%), community adults (10.5%), children (10.5%), exercise class attendants (10.5%),
and patients (e.g., cardiac, pain, cancer, 10.5%). The majority of the studies did not report
the participant’s race/ethnicity (81.6%) or socioeconomic status (68.4%); however, in the
studies that did report these characteristics, the majority were Caucasian middle-to-upper
class adults.
Main TPB Study Characteristics
Most of the studies were published (71.1%) and were conducted in the 1990’s
(65.8%), followed by the 1980’s (23.7%), and the 2000’s (10.5%). The majority of the
studies included male and female participants (86.8%). The participants were
undergraduates (23.7%), worksite employees (13.2%), older adults (13.2%), community
adults (10.5%), children (10.5%), exercise class attendants (10.5%), and patients (e.g.,
cardiac, pain, cancer, 10.5%). Most of the studies did not report the participant’s
race/ethnicity (65.8%) or socioeconomic status (60.5%); however, in the studies that did
report these characteristics, Caucasian middle-to-upper class adults were the most
frequently studied.

36
Table 2.2
The Number fNf and Percent (%1 of Main Theory of Planned Behavior (TPBf and
Elicitation Study Characteristics
Characteristic
N
%
Main TPB Study Characteristics
Publication year
1980’s
9
23.7
1990’s
25
65.8
2000’s
4
10.5
Publication format
Published
27
71.1
Unpublished
11
28.9
Dissertation
9
81.8
Thesis
2
18.2
Participants
Sex
Male and female
33
86.8
Female only
4
10.5
Not available
1
2.6
Race/Ethnicity
Caucasian
9
23.7
Caucasian and African American
2
5.3
Caucasian, Hispanic, and African American
1
2.6
Caucasian, Anglo-Canadian, and European
1
2.6
Not available
25
65.8
Population
Undergraduates
9
23.7
Worksite employees
5
13.2
Older adults
5
13.2
Community adults
4
10.5
Children
4
10.5
Exercise class attendants
4
10.5
Patients (e.g., cardiac, pain, cancer)
4
10.5
Spouses of cardiac patients
1
2.6
Combination (cardiac patients, community adults
1
2.6
pregnant women)
Not available
1
2.6
Socioeconomic status
Middle class
6
15.8
Middle class-upper class
5
13.2
Lower class-middle class
4
10.5
Not available
23
60.5

37
Table 2.2 Continued
Characteristic N %
Type of behavior
Exercise
Physical or leisure activities
Walking
Tonercise
Habit
Elicitation study characteristics
Participants
Sex
Male and female
Female only
Not available
Race/Ethnicity
Caucasian
Caucasian, Hispanic, and African American
Caucasian and African American
Not available
Population
Undergraduates
Worksite employees
Older adults
Community adults
Children
Exercise class attendants
Patients (e.g., cardiac, pain, cancer)
Spouses of cardiac patients
Combination (cardiac patients, community adults,
pregnant women)
Not available
Socioeconomic status
Middle class to upper class
Middle class
Lower class to middle class
Not available
26 68.4
8 21.1
2 5.3
1 2.6
1 2.6
27 71.1
4 10.5
7 18.4
4 10.5
2 5.3
1 2.6
31 81.6
9 23.7
5 13.2
5 13.2
4 10.5
4 10.5
4 10.5
4 10.5
1 2.6
1 2.6
1 2.6
5 13.2
4 10.5
2 5.3
27 71.1
Note. “May not add up to 100% because more than one construct was measured per
study.

38
Elicitation Study Method Characteristics
Correspondence between the elicitation and main TPB study participant
characteristics could not be determined for the majority of studies (94.7%, n = 36)
because not enough information was provided regarding the elicitation studies. For
example, Doyle-Baker (2000) provided information on the main TPB study participants’
sex, M age, and race/ethnicity; however, these characteristics were not provided for the
elicitation study participants. Similarly, the majority of elicitation studies (60.5%, n = 23)
did not provide enough information to determine the measures and procedures used to
elicit the behavioral, normative, and control beliefs. For example, Mummery, Spence, &
Fludec (2000) stated that they elicited participants’ behavioral, normative, and control
beliefs; however, no information was provided as to what these salient beliefs were or
how they were obtained.
Elicitation Study Belief Characteristics
Behavioral beliefs. The majority of the elicitation studies (92.1%) examined
behavioral beliefs, and the average number of beliefs reported per study was 10 (see
Table 2.3). The most salient behavioral advantages of exercise were: a) feeling healthy,
better, or good about self (93.3%); b) controls weight and diet (86.7%); c) increases
physical fitness (80.0%); d) improves daily functioning (73.3%); e) increases energy
(66.7%); f) improves mental health (60.0%); g) relieves stress and promotes relaxation
(53.3%); and h) improves cardiovascular system (53.3%). The most common behavioral
disadvantages were: a) experiencing pain, injury, and soreness; 53.3%); b) tired (40%); c)
inconvenience (40.0%); and d) lacking time (33.3%)'.
'Percents add up to greater than 100% because some people reported several beliefs about
exercise behavior.

39
Table 2.3
The Number fNl and Percent (%) of Elicitation Study Behavioral. Normative, and
Control Beliefs
Beliefs
Higher-order Theme
Raw Data Theme
N
%"
Behavioral
Improves physical
Feeling healthy, better,
14
93.3
Beliefs6
and psychological
or good about self
(Advantages)
health
Controls weight and diet
13
86.7
Increases physical
fitness (e.g., muscular
strength, physical fitness,
toning, flexibility,
and reflexes)
12
80.0
Improves daily
functioning (e.g., get
mind off of cancer
treatment, maintain a
normal lifestyle, gain
control over life,
recover from surgery,
return to work, perform
tasks with more ease,
more daily structure)
11
73.3
Increases energy
10
66.7
Improves mental health
(e.g., better outlook on
life, increases confidence,
concentration, and
alertness)
9
60.0
Relieves stress and
promotes relaxation
(e.g., relieves tension
and joint stiflness, coping
with stress, relax)
8
53.3
Improves cardiovascular
system (e.g., increases
8
53.3
circulation, agility, stronger
heart and lungs, suppleness
decreases blood pressure)

40
Table 2.3 Continued
Beliefs Higher-order Theme
Socialize
Physical activity
Fun
Behavioral Physical and
Beliefs psychological
(Disadvantages) health issues
Raw Data Theme
N
%a
Improves health
and well-being
5
33.3
Improves self and
body image
3
20.0
Stay in shape
2
13.3
Improves sleep
1
6.7
Increases appetite
1
6.7
Decreases disease
symptoms
1
6.7
Make friends
2
13.3
Meet new people
1
6.7
Opportunity to socialize
1
6.7
Athletic performance
1
6.7
Good exercise
1
6.7
Fun and enjoyment
1
6.7
Experiencing pain,
soreness, or injury
8
53.3
Tired
6
40.0
Aggravates physical
Condition
2
13.3
Wears on bones
and joints
1
6.7

41
Table 2.3 Continued
Beliefs Higher-order Theme
Inconvenience
Lacking time
Expensive
Normative
Beliefs1
Family and
friends
Healthcare
professionals
School and
worksite
personnel
Raw Data Theme
N
%*
Daily inconveniences
(e.g., other commitments,
interferes with daily
routine and family, messy,
inconvenient for spouse
6
40.0
Lacking time, no time
5
33.3
Expensive, no money
1
6.7
Friends
16
88.9
Spouse or girl/boyfriend
15
83.3
Family members
not specified
11
61.1
Parents
7
46.7
Children
6
33.3
Siblings
2
11.1
Grandparents
1
5.6
Physician
12
66.7
Nurse
1
5.6
Physical therapist
1
5.6
Heathcare workers
not specified
1
5.6
Boss
4
22.2
Co workers
4
22.2
Teacher
2
11.1
Coach
1
5.6

42
Table 2.3 Continued
Beliefs
Higher-order Theme
Raw Data Theme
N
%*
Miscellaneous
Other exercisers
3
16.7
Other people with cancer
2
11.1
Media
2
11.1
Minister or church official
1
5.6
Control
Social support
Having an exercise partner
2
13.3
Beliefs'1
(Facilitating
Getting encouragement
2
13.3
Factors)
and motivation
Getting a written reminder
1
6.7
Meetings and programs
1
6.7
Contests and incentives
1
6.7
Miscellaneous
Previous exercise
experience
1
6.7
Fun and enjoyment
1
6.7
Convenience
1
6.7
Good weather
1
6.7
Inexpensive
1
6.7
Control
Physical and
Experiencing pain, injury,
13
86.7
Beliefs
psychological
and illness
(Obstructing
Factors)
health issues
Lacking motivation
or feeling lazy
6
40.0
Tiredness and fatigue
5
33.3
Fear (e.g., having another
heart attack)
1
6.7
Age
1
6.7

43
Table 2.3 Continued
Beliefs Higher-order Theme
Raw Data Theme
N
%*
Time
Lacking time, no time
13
86.7
Inconvenience
Lacking access to exercise
facilities and equipment
5
33.3
Other commitments
5
33.3
Bad weather
2
13.3
Facility too crowded
1
6.7
Facility too far away
1
6.7
Lacking transportation
1
6.7
Baby’s health problems
1
6.7
Lactation constraints
1
6.7
Miscellaneous
No exercise partner
6
40.0
Lacking exercise
knowledge or exercise
counseling
5
33.3
Lacking money or
too expensive
4
26.7
Note. N = 38 studies reviewed; “Percent may not add up to 100% because multiple beliefs
were reported per study; bn = 15 studies elicited and described behavioral beliefs, n = 20
studies elicited behavioral beliefs but did not describe in detail, n = 3 studies did not elicit
behavioral beliefs; cn = 18 studies elicited and described normative beliefs, n = 15 studies
elicited normative beliefs but did not describe in detail, n = 5 studies did not elicit
normative beliefs; “n = 12 studies elicited and described control beliefs (Godin et al.,
1994 elicited control beliefs separately for three different populations; these beliefs were
coded as separately, and the percents were calculated by dividing the belief n by 15 rather
than 12), n = 10 studies elicited control beliefs but did not describe in detail, n = 16
studies did not elicit control beliefs.

44
Normative beliefs. The majority of the elicitation studies examined normative
beliefs (86.8%), and the average number of beliefs reported per study was 5. The
normative beliefs were: a) friends (88.9%), b) spouse or girl/boyfriend (83.3%), c)
physician (66.7%), d) family members not specified (61.1%), e) parents (46.7%), f)
children (33.3%), g) boss (22.2%), and h) coworkers (22.2%).
Control beliefs. Slightly more than half (57.9%) of the studies examined control
beliefs, and the average number of beliefs per study reported was 7. The most frequently
reported control belief facilitating exercise was social support (e.g., having an exercise
partner, getting encouragement and motivation; 46.7%). The most common control
beliefs obstructing exercise were; a) experiencing pain, injury, and illness (86.7%); b)
lacking time (86.7%); c) lacking motivation or feeling lazy (40.0%); d) no exercise
partner (40.0%); e) tiredness and fatigue (33.3%); f) lacking access to exercise facilities
and equipment (33.3%); and g) lacking exercise knowledge or exercise counseling
(33.3%).
Discussion
The primary purpose of this study was to identify the salient beliefs reported in
elicitation studies. The secondary purpose of this study was to compare the characteristics
of the elicitation and main TPB studies to determine if there was correspondence between
the participants, methods, and procedures. Several findings warrant discussion. First,
consistent with previous researchers’ conclusions (e.g., Carrón et al., 2003), the most
salient behavioral advantage of exercise was that it improves people’s physical and
psychological health (e.g., improves physical fitness, feeling better about self). In
addition, the most common behavioral disadvantages of exercise were:

45
• Physical and psychological health issues (e.g., experiencing pain, soreness, and
injury, and invoking tiredness).
• Inconvenience (e.g., interferes with daily routine, inconvenient for spouse).
• Lacking time.
These findings indicate that people have a variety of positive and negative behavioral
beliefs regarding exercise, and elicitation studies help researchers determine which of
these beliefs are the most salient for their population of interest.
Moreover, because researchers have found that people’s attitude most strongly
predict their exercise intentions (i.e., Symons Downs & Hausenblas, 2002), it is
important to consider a population’s behavioral advantages and disadvantages for
exercise. For example, while healthy populations may believe that exercising will
improve their health, some special populations (e.g., cardiovascular disease and chronic
pain patients) may believe that exercising will debilitate their health. Thus, identifying
how people feel about exercise is an important step in determining the factors that may
facilitate or inhibit their exercise behavior. In addition, understanding people’s salient
behavioral advantages and disadvantages of exercise can assist researchers with tailoring
their exercise interventions to meet the specific thoughts, needs, and beliefs of
populations that are at risk for sedentary behavior (e.g., elderly, overweight, pregnant;
Carrón et al., 2003).
Second, consistent with the findings of Carrón et al. (2003), the most frequently
reported normative influences were friends and family. Specifically, it was found that for
exercise behavior, people value the opinions and wishes of their friends and spouse or
girl/boyfriend the most, followed by the expectations of their parents, children, and
siblings. In some studies, however, the normative influence of family members was not

46
completely described (e.g., Blue, 1996; Coumeya & Friedenreich, 1997, 1999). That is, a
“family member” was reported as a normative influence, however, the researchers did not
identify who this family member was (e.g., a parent, spouse, brother). Moreover,
identifying which important others have the strongest impact can be helpful for
researchers who are designing and implementing exercise interventions. For example,
social support plays an important role in exercise adherence, and knowing who provides a
person with the most social support may help to increase his or her exercise participation
and adherence (Coumeya & McAuley, 1995; Coumeya, Plotnikoff, Hotz, & Birkett,
2000). Thus, researchers are encouraged to be more specific when reporting the influence
of significant others on people’s exercise intention and behavior.
Third, consistent with previous researchers’ conclusions (Carrón et al., 2003),
another frequently reported normative influence was a person’s physician. That is, people
consider their physician to be an important authority regarding their exercise behavior.
Thus, physicians and other healthcare workers may play a valuable role in promoting
exercise behavior and adherence with their patients. In addition, it is important to note
that while 70% of adults are seen by a healthcare provider at least one time per year,
some special populations (e.g., cancer patients, the elderly, pregnant women) are in more
frequent contact with their primary caretaker (Logsdon, Lazaro, & Meier, 1989). Thus,
because there is a need for research examining populations that are at risk for sedentary
behavior (e.g., cancer, patients, the elderly, pregnant women; USDHHS, 2000) and
because access to these populations can be challenging (e.g., getting diseased, elderly,
and pregnant populations to volunteer for studies), researchers studying the determinants

47
of exercise behavior in special populations may consider collaborating with physicians
and other healthcare professionals when conducting their studies (Koniak-Griffin, 1994).
Fourth, while Carrón et al. (2003) stated that the most common control beliefs
inhibiting exercise participation were a lack of time, energy, and motivation, I found that
the most common control beliefs obstructing exercise were:
• Physical and psychological issues (e.g., experiencing pain, injury, and illness, lacking
motivation, tiredness and fatigue).
• Lacking time.
• Inconvenience (e.g., lacking access to exercise facilities or equipment, other
commitments).
• No exercise partner.
One explanation for this discrepancy is that I reviewed studies that included special
populations, while Carrón et al.’s conclusions were based on healthy populations. For
example, in this review, different salient beliefs emerged for healthy populations (i.e.,
lacking time and motivation) compared to special populations such as cancer patients
(i.e., recovering from surgery, experiencing nausea; Coumeya & Friedenreich, 1997,
1999), older adults (i.e., experiencing illness, injury, or health problems; Brenes et al.,
1998), and postpartum women (i.e., experiencing physical health problems after birth;
Godin et al., 1994). These findings demonstrate the importance of conducting elicitation
studies, and they emphasize the need to examine the determinants of exercise in special
populations. That is, what obstructs exercise participation for a person during cancer
treatment may be different than what inhibits exercise participation for a mother with a
newborn baby.

48
In addition, the most salient control belief facilitating exercise behavior was
receiving social support from other people, including having an exercise partner and
receiving encouragement and motivation. Consistent with the findings for normative
beliefs, these findings indicate that people’s exercise behavior can be positively
influenced by other people, and they illustrate that significant others may assist
researchers with increasing exercise behavior in populations that are at risk for
sedentariness. Moreover, identifying what people perceive as facilitating and obstructing
factors of exercise participation may help researchers to emphasize the advantages of
exercise (e.g., improves self-esteem and increases energy), as well as assist people with
overcoming their perceived barriers (e.g., exercise may cause injury). These are
important facets of increasing people’s exercise motivation, and ultimately, their exercise
adherence (Lynch et al., 2000). Thus, the findings from this review may aid researchers
in: understanding the determinants of exercise behavior, developing exercise
interventions to increase exercise participation, and promoting exercise adherence.
Fifth, because of the lack of information provided for elicitation studies, I was
unable to examine the elicitation study methods (i.e., participants, measures, and
procedures). More specifically, 95% of the studies did not report sufficient information
for the participant characteristics, and 61% of the studies did not report adequate details
to determine the measures and procedures used to elicit the beliefs. For example, only
two of the studies reviewed (i.e., Bergen, 1996; Helm, 1987) provided enough detail
regarding the elicitation and main TPB study participants (i.e., population type, number
of participants, sex, M age or age range, race/ethnicity, and socioeconomic status) for
correspondence to be determined. Similarly, a limited number of studies (e.g., Ajzen &

49
Driver, 1991; Coumeya & Friedenreich, 1997, 1999; Smith & Biddle, 1999) described
the elicitation study measures and procedures with sufficient detail. This is problematic
for two reasons. First, it is not clear whether the elicitation study participants were similar
to the main TPB study participants. When correspondence cannot be determined, it is
possible that the elicitation study may have been conducted with people who have
different beliefs about exercise than the main TPB study. Second, when the measures and
procedures of an elicitation study are not properly described, researchers are not able to
determine how the beliefs were obtained, and they cannot replicate the measures and
procedures in future studies. Both of these problems can jeopardize the utility of the TPB
in predicting exercise intention and behavior (Ajzen, 1991).
Two limitations of the studies included in this review must be noted. First, when
interpreting the findings regarding the salient behavioral, normative, and control beliefs,
researchers should consider that some of the elicitation studies were conducted with
nonrandom samples (e.g., Brenes et al., 1998; Godin et al., 1994), and samples with a
small number of participants (e.g., n = 8 participants; Smith & Biddle, 1999). Second,
because there was limited information provided for the majority of the elicitation studies,
the salient behavioral, normative, and control beliefs that emerged from this review are
based on the small number of studies that elicited and described these beliefs. Thus, these
findings have limited generalizability.
Moreover, it is important that elicitation study methods are reported with more
detail for researchers to generalize their findings to a variety of populations and replicate
these studies. For example, researchers must present the elicitation study methods and
specify the participants, measures, and procedures for the study to be replicated. Thus,

50
researchers are encouraged to report more details regarding elicitation studies in an
attempt to improve the predictive utility of the TPB (Ajzen, 1991).
In summary, Ajzen and Fishbein (1980) developed theoretical guidelines for
researchers to direct their studies and improve the predictive utility of the TPB by using
elicitation studies. When researchers adhere to these guidelines, the TPB is more
powerful in predicting exercise intentions and behavior (Symons Downs & Hausenblas,
2002). Thus, it is important for researchers examining the TPB to use the recommended
theoretical guidelines to effectively increase people’s physical activity behavior (Carrón
et al., 2003; Maddux & DuCharme, 1997). In short, because elicitation studies determine
a population’s salient behavioral, normative, and control beliefs which provide the
necessary framework for examining people’s attitude, subjective norm, and perceived
behavioral control, researchers are encouraged to:
• Adhere to the TPB guidelines and conduct elicitation studies.
• Obtain correspondence between the elicitation and main TPB study participants.
• Report more details regarding the elicitation study participants (i.e., population type,
M age or age range, sex, race/ethnicity, and socioeconomic status), measures, and
procedures.
This information may assist researchers with planning and implementing programs
designed to increase exercise involvement and improve exercise adherence across all
types of populations (e.g., children, diseased, elderly, economically disadvantaged).
Moreover, this is important considering that the majority of North Americans are low
active or sedentary, which increases their risk for a variety of physical and psychological
diseases (USDHHS, 2000). Thus, understanding people’s beliefs about exercising can

51
assist researchers with strategies that may increase their exercise behavior, change their
lifestyle, and ultimately, improve their physical and psychological health.
Prelude to Chapter 3
This review of TPB and exercise elicitation studies was necessary for two
reasons. First, because few TPB and exercise studies have conducted elicitation studies, it
was important that I could identify the type of behavioral, normative, and control beliefs
that people have reported about exercise. Thus, the best method for me to obtain a more
comprehensive understanding about people’s exercise beliefs was to conduct this review
study. Second, the findings from this review provided the framework for the next chapter.
Specifically, understanding the methods that previous researchers have used to obtain
people’s exercise beliefs allowed me to effectively design and implement an elicitation
study with a sample of postpartum women. The next chapter (Chapter 3) will:
• Provide the rationale and purpose for conducting an exercise elicitation study with
postpartum women.
• Describe in detail the study methods and results.
• Highlight the important study findings for discussion.

CHAPTER 3
STUDY 2: THE THEORY OF PLANNED BEHAVIOR
AND EXERCISING DURING PREGNANCY AND POSTPARTUM:
AN ELICITATION STUDY
In the past 50 years, many scientific and medical innovations have increased
people’s lifespan, including artificial organ transplants, microscopic surgery, and gene
therapy (Eaton, Cordain, & Lindeberg, 2002; Eaton et al., 2002). Despite these advances,
chronic behavioral ailments such as cardiovascular disease, cancer, diabetes, and fiver
disease are currently responsible for the greatest mortality among American adults (AHA,
1997; CDC, 1999; NCHS, 1997). While genetics may predispose people to certain
conditions, most chronic diseases are associated with negative behaviors such as
smoking, poor diet, and sedentariness (Mitchell et al., 1999). Thus, people can reduce
their risk of chronic disease by adopting positive lifestyle patterns such as eating a
balanced diet, maintaining a healthy weight, and engaging in regular physical activity
(AHA; CDC; Taylor, 1999; Twisk et al., 2000).
In regard to physical activity, regular exercise contributes positively to
physiological heath and psychological well-being (USDHHS, 1996, 2000). Most U.S.
adults, however, are physically inactive because they are not participating in 30 min of
accumulated moderate to vigorous physical activity on most, if not all, days of the week
(ACSM, 1999, 2000). The people most at risk for a low active or sedentary lifestyle
include special populations such as ethnic minorities, the elderly, women, and people of
low socioeconomic status and education (USDHHS). Promoting physical activity in these
52

53
special populations is difficult due to the unique barriers obstructing their participation
that are not found in nonrisk populations. For example, women are faced with several
physical and psychological challenges that can reduce their exercise behavior. For
example, life events unique to women (e.g., menstruation, pregnancy, and menopause)
may place them at greater risk for decreased physical activity compared to men
(USDHF1S). Specifically for pregnancy, Zhang and Savitz (1996) conducted a prevalence
study on 9,953 U.S. women and they found that:
• 45% were sedentary before and during pregnancy.
• 13% exercised before pregnancy but stopped after they found out they were pregnant.
• 7% did not exercise before pregnancy but exercised during pregnancy.
• 35% exercised before and during pregnancy.
These findings illustrate that 58% of pregnant women are sedentary, placing them above
the national average (i.e., 30% of U.S. adults are sedentary; USDHHS). Thus, pregnancy
is an important event in women’s lives that may promote decreased physical activity.
For many women, exercising during pregnancy is compromised by the
physiological and psychological demands of this time. For instance, pregnancy is
associated with increases in maternal cardiac output, ventilation, oxygen constraints, and
body mass index (Bungum et al., 2000; Carter et al., 2000). In addition, symptoms of
depression, stress, and anxiety can occur during pregnancy (Monk et al., 2000;
Zuckerman, Amaro, Bauchner, & Cabral, 1989). For example, approximately one-third of
women experience depressive symptoms during their pregnancy (Zuckerman et al.).
Moreover, exercising during pregnancy can elevate maternal core temperature, decrease
blood flow to the fetus, and increase a woman’s risk of exercise-related injuries (e.g.,

54
physical changes from gaining weight; Wallace & Engstrom, 1987). Consequently, many
women find these added physical and psychological demands stressful, and thus, they
either decrease or stop exercising during their pregnancy.
Regardless of these concerns, there is a general consensus that most previously
active women can continue to exercise during their pregnancy without risk to either
themselves or their fetus (Bungum et aL, 2000; Clapp, 1990; Jackson, Gott, Lye, Knox-
Ritchie, & Clapp, 1995; Lokey, Tran, Wells, Myers, & Tran, 1991; Rice & Fort, 1991).
For example, Lokey et ai. meta-analytically reviewed 18 exercise and pregnancy studies,
and they found that exercising during pregnancy was not associated with harmful
physical effects for either the mother or the fetus. Moreover, the ACOG (1994)
recommended that women without obstetric or medical problems exercise moderately
during their pregnancy. Their specific guidelines are that pregnant women should:
• Warm-up before exercise.
• Avoid overexertion (e.g., heart rate should not exceed 140 beats per min, strenuous
exercise not to exceed 15 min).
• Drink plenty of fluids.
• Consume calories in addition to the 300 extra kilocalories required by pregnancy.
• Avoid activities that may cause abdominal trauma.
• Modify or stop activity if uncomfortable.
In addition, some researchers have concluded that exercising during pregnancy is
associated with decreased depression, and improved self-esteem, mood, and body image
(Bungum et aL, 2000; Koniak-Griffin, 1994; Walker et aL, 1999). For example, Koniak-
Griffin examined the effects of exercise on pregnant women’s psychological health, and

55
she found that women’s self-esteem increased and depressive symptoms decreased over a
6-week aerobic exercise program. Moreover, exercising during pregnancy can assist
women with controlling their weight by reducing excessive weight gain (Bungum et al.;
Carter et al., 2000). Considering that weight gain during pregnancy is associated with
negative affective symptoms (e.g., anxiety, depression) during both pregnancy and
postpartum, it is important to examine the effects of exercise as a way to control
excessive weight gain (Carter et al.).
While there is an abundance of studies examining exercise in nonrisk populations,
the research examining physical activity during pregnancy is scant and limited by several
factors. First, the majority of the researchers have focused on the physiological effects of
exercise during pregnancy (i.e., risk to the fetus), and few studies have examined its
psychosocial effects on the mother (e.g., Koniak-GrifiSn, 1994; Zhang & Savitz, 1996).
Second, due to the difficulty associated with recruiting pregnant participants, many
studies have been conducted with animal versus human subjects (Koniak-Griffin). Third,
many studies including pregnant women have had small samples sizes or inadequate
control groups (Berg, 1999).
Fourth, while physical activity is a valuable treatment for alleviating
psychological symptoms such as anxiety and depression in clinical and nonclinical
populations (e.g., USDHHS, 1996), there are a limited number of studies that have
examined the effects of exercise as a treatment for the psychological changes (i.e., mood
disturbances) experienced during pregnancy. It is important to examine if exercise
improves women’s mood during pregnancy because of the higher likelihood for women
to experience negative affect during this time (Carter et al., 2000). Fifth, researchers have

56
found that exercise behavior decreases during pregnancy and postpartum, however, most
of this research is based on author-developed measures of exercise (Eisen et al., 1991).
Thus, there is a need to examine exercise behavior during pregnancy and postpartum with
standardized measures (Eisen et al.). Sixth, the research examining women’s thoughts,
feelings, and beliefs about the facilitating and obstructing factors of exercising during
pregnancy is scant. It is important to examine what women feel about exercising during
their pregnancy to determine how to prevent decreased physical activity during this time.
Finally, while researchers have stated the need for theoretically examining exercise
determinants, most of the research with pregnant populations is atheoretical (Maddux &
DuCharme, 1997; Walker et al., 1999).
One conceptual framework that may provide researchers with a better
understanding of women’s beliefs about exercising during pregnancy and postpartum is
the theory of planned behavior (TPB; Ajzen, 1988, 1991; Ajzen & Fishbein, 1980). The
TPB is a belief-based model that includes the following eight constructs:
• Behavioral beliefs (i.e., perceived consequences, either positive or negative of
engaging in a behavior, and one’s personal evaluation of these consequences).
• Normative beliefs (i.e., whether people believe that significant others such as family
and friends think that they should engage in a behavior).
• Control beliefs (i.e., factors that facilitate and obstruct behavior adoption such as
personal skills, resources, and opportunities).
• Attitude (i.e., people’s beliefs about a behavior, the strength of this association, and
the perceived consequences of performing the behavior).
• Subjective norm (i.e., people’s normative beliefs about a behavior and their
motivation to comply with the expectations of significant others).
• Perceived behavioral control (i.e., how people feel about the facilitating and
obstructing factors of behavioral adoption and how much control they think they have
over engaging in a behavior).

57
• Intention (i.e., a person’s plan, and their level of motivation for behavior adoption).
• Behavior (i.e., any activity that people wish to engage in such as exercise, smoking
cessation, and eating a balanced diet).
According to Ajzen and Fishbein, people’s behavioral, normative, and control beliefs
about a behavior formulate their attitude, subjective norm, and perceived behavioral
control. These factors then influence people’s intentions, and ultimately their behavior.
Ajzen and Fishbein (1980) developed guidelines for the TPB. One of their
recommendations is that an elicitation study be performed to establish the salient
behavioral, normative, and control beliefs of a population. An elicitation study should be
conducted with the following three procedures. First, open-ended questions are used to
retrospectively elicit the beliefs (e.g., retrospective accounts are recommended because
they provide a more accurate assessment of people’s beliefs since there has been time for
their beliefs to form; K. S. Coumeya, personal communication, 2002). Second, a content
analysis (i.e., frequency count) is performed to rank-order the beliefs. Third, structured
TPB items are developed from the most salient beliefs to measure people’s attitude,
subjective norm, perceived behavioral control, intention, and behavior.
Researchers have identified the most frequently reported beliefs of exercise
participants (Carrón et al., 2003; Symons Downs, Chapter 2). For healthy populations,
Carrón and his colleagues have suggested that the most salient behavioral beliefs include
both positive (e.g., exercise improves health) and negative (e.g., exercise reduces time
with family and friends) evaluations regarding exercise. Carrón et al. suggested that the
most frequently reported normative beliefs include the influences of significant
individuals (e.g., spouse, mother, brother) and groups (e.g., friends, coworkers). In

58
addition, the authors concluded that the most common control beliefs are a lack of time,
energy, and motivation.
Recently, Symons Downs (Chapter 2) reviewed 38 studies that elicited exercise
beliefs in healthy and special populations, and she found that:
• The most salient behavioral advantage of exercise was that it improves physical and
psychological health.
• The most important normative influences were friends, spouses, physicians, and
family members.
• The most common control beliefs obstructing exercise behavior were physical and
psychological health issues, a lack of time, and inconvenience.
The findings of Carrón et al. (2003) and Symons Downs illustrate the importance of
assessing people’s beliefs, and they demonstrate that exercise beliefs can vary from one
population to another.
Moreover, the findings from several narrative (e.g., Blue, 1995; Godin, 1993) and
statistical (e.g., Hagger et al., 2002; Hausenblas et al., 1997; Symons Downs &
Hausenblas, 2002) reviews of the literature have determined that the TPB has been
successfiilly applied to exercise behavior. The constructs of attitude, subjective norm, and
perceived behavioral control have explained 40% to 60% of the variance in intentions,
and 20% to 40% of the variance in exercise behavior (Culos-Reed et al., 2001). In
addition, Symons Downs and Hausenblas meta-analytically examined 87 studies, and
they found that attitude was a stronger predictor of intention than perceived behavioral
control, and intention was the strongest predictor of exercise behavior. In addition, less
than half of the reviewed studies included an elicitation study, and smaller intention-
behavior and perceived behavioral control-behavior associations were found when an
elicitation study was not conducted. These findings demonstrate that most researchers

59
are not adhering to the theory guidelines, and that the utility of the TPB is compromised
when elicitation studies are not conducted.
Furthermore, Symons Downs and Hausenblas (2002) found that the number of
TPB studies examining exercise with at-risk populations is scant. That is, only 22.9% of
the studies they reviewed included special populations (see Appendix A for a detailed list
of these studies). For example, only three located studies have examined the TPB for
exercise behavior with pregnant or postpartum populations (i.e., Godin, Valois, &
Lepage, 1993; Godin, Vezin, & Leclerc, 1989; Godin et al., 1994). Godin et al. (1989)
examined the TPB constructs and habit in predicting 98 pregnant women’s intentions to
exercise after giving birth, and they found that perceived barriers emerged as the
strongest predictor. Godin et al. (1993) examined the TPB constructs and habit in
predicting 136 pregnant women’s exercise intentions and behavior, and they found that
habit was the only predictor of exercise behavior, and attitude, habit, and perceived
behavioral control predicted intention. Finally, Godin et al. (1994) examined the control
beliefs and perceived barriers to exercise of 139 pregnant women, and they found that
perceived barriers (e.g., baby’s health and time management problems) were negatively
associated with intention.
These studies, however, are limited by two methodological concerns. First, Godin
et al. (1989) and Godin et al. (1993) did not conform to the TPB guidelines with respect
to the model constructs (Ajzen, 1991; Ajzen & Fishbein, 1980). That is, in one study (i.e.,
Godin et al., 1989), perceived barriers were substituted for perceived behavioral control,
and in both studies, habit was added to the model to predict intention and behavior.
According to Ajzen, when researchers substitute or add variables to the TPB, the utility

60
of the model in predicting exercise intentions and behavior is compromised. Second, only
one study (i.e., Godin et al., 1994) conducted an elicitation study to ascertain the salient
beliefs of postpartum women. However, this study only assessed women’s control
beliefs. Participants in this study reported that the most important control beliefs
obstructing their exercise were:
• Lactation constraints.
• Lacking time.
• Physical health problems following delivery.
• Psychological problems adapting to life after being pregnant.
• The baby’s health problems.
Thus, no located elicitation studies have examined women’s salient behavioral and
control beliefs regarding exercising during pregnancy and postpartum.
Therefore, due to the limited number of studies examining the TPB and exercise
during pregnancy and postpartum, the methodological concerns regarding these studies
(i.e., nonstandardized exercise measures, substituting and adding variables to the TPB),
and the lack of elicitation studies in the literature, the objective of this study was to
examine postpartum women’s beliefs about exercising during pregnancy and postpartum
using the theoretical framework of the TPB. The first study purpose was to examine the
frequency of women’s behavioral, normative, and control beliefs for exercising during
their pregnancy and postpartum, and to determine their most salient beliefs. Because the
aim of elicitation studies is to generate people’s beliefs, and because beliefs are expected
to vary across time and situation (e.g., Ajzen, 1991; Carrón et al., 2003), no apriori
hypotheses were established for pregnant women’s beliefs. The second study purpose

61
was to examine participant’s physical activity during three periods (i.e., before
pregnancy, during pregnancy, and in postpartum) with a standardized self-report measure
of exercise behavior. Consistent with the conclusions of Zhang and Savitz (1996), it was
hypothesized that the participant’s exercise behavior would be greater before pregnancy
compared to during and after pregnancy (i.e., postpartum). The third study purpose was
to examine the participant’s body mass index before pregnancy and during in postpartum.
Based on the findings of Carter et al. (2000), it was hypothesized that the participant’s
body mass index would be lower before pregnancy compared to postpartum.
Method
Participants
Participants were 74 postpartum women (M age = 31.30 years, SD = 4.37, age
range = 19-40 years). Postpartum was operationalized as being within 1-year of the
child’s birth (Anderson, Anderson, & Glanze, 1994). The majority of participants were
Caucasian (81.1%), married (86.5%), college graduates (44.6%), business employees
(39.2%), and earning a family income of $40,000 to $100,000 (62.2%; see Table 3.1).
Measures
Personal History Questionnaire. The Personal History Questionnaire was
developed for this study, and it assessed age, height, weight, date of birth of most recent
child, race/ethnicity, marital status, highest level of education achieved, employment, and
family income (see Appendix B).
Body Mass Index (BMP, BMI was measured with self-reported height and
weight, and it was calculated by converting weight from pounds to kilograms, and
changing height from inches to meters (kg/m2). BMI is a reliable estimate of obesity,

62
Table 3.1
The Number IN! and Percent (%) of the Demographic Characteristics for the Participants
Characteristic
N
%*
Race/Ethnicity
Caucasian
60
81.1
Hispanic American
5
6.8
African American
1
1.4
Other
4
5.4
Marital Status
Married
64
86.5
Single
5
6.8
Divorced
3
4.1
Common Law
1
1.4
Widow
1
1.4
Employment
Business
29
39.2
Teacher
8
10.8
Secretary or Administrative Assistant
8
10.8
Housewife
7
9.5
Cashier or Waitress
7
9.5
Nurse
5
6.8
Doctor
4
5.4
Lawyer
2
2.7
Not Employed
1
1.4
Education
High School
16
21.6
College
33
44.6
Graduate
17
23.0
Grade School
1
1.4
Trade
5
6.8
Other
1
1.4
Family Income
Less than $10,000
2
2.7
$10,000 to $20,000
4
5.4
$20,000 to $40,000
9
12.2
$40,000 to $100,000
46
62.2
Greater than $ 100.000
12
16.2
Note. “May not add up to 100% due to missing data.

63
however, there is a 5% standard error when using BMI to estimate body fat percentage
(ACSM, 2000; Garrow & Webster, 1985).
Leisure-Time Exercise Questionnaire (LTEO). The LTEQ (Godin, Jobin, &
Bouillon, 1986) assesses the frequency of strenuous, moderate, and mild leisure-time
exercise done for at least 20 min during a typical week (see Appendix C). A total exercise
index (in weekly metabolic equivalents, METS) was calculated for participant’s exercise
behavior before, during, and after pregnancy by weighing the frequency of each intensity
and summing them for a total score with the following formula: 3(mild) + 5(moderate) +
9(strenuous). The LTEQ is a reliable and valid measure of exercise behavior (Jacobs,
Ainsworth, Hartman, & Leon, 1993).
Exercise Beliefs Questionnaire. Adhering to the TPB guidelines, the participants
reported their beliefs about exercising during their pregnancy and postpartum (Ajzen &
Fishbein, 1980). Following each question were five double-spaced blank lines for
participants to record as many beliefs that applied to them (see Appendix D). Behavioral
beliefs were measured by the following four questions: “List the main advantages of
exercising during your pregnancy,” “List the main disadvantages of exercising during
your pregnancy,” “List the main advantages of exercising following the birth of your
child,” and “List the main disadvantages of exercising following the birth of your child.”
Normative beliefs were measured by the following two questions: “List the individuals or
groups who were most important to you when you thought about exercising during your
pregnancy,” and “List the individuals or groups who were most important to you when
you thought about exercising following the birth of your child.” Control beliefs were
assessed by the following four questions: “List the main factors that helped you to

64
exercise during your pregnancy,” “List the main factors that prevented you from
exercising during your pregnancy,” “List the main factors that helped you exercise
following the birth of your child,” and “List the main factors that prevented you from
exercising following the birth of your child.” Content validity of the Exercise Beliefs
Questionnaire was established by having two TPB and exercise experts examine the
items (i.e., the experts obtained 100% content validity agreement).
Procedures
Approval was obtained from the University’s Institutional Review Board to
conduct this study (see Appendix E). Consent was obtained from a private practice
physician specializing in obstetrics and gynecology, who agreed to assist with the data
collection. The consent form (see Appendix F) and the questionnaire packets (i.e.,
Personal History Questionnaire, the LTEQ, and the Exercise Beliefs Questionnaire) were
mailed to the doctor’s office in New Britain, CT at the end of October, 2000, and the data
were collected from November, 2000 to April, 2001.
The participants volunteering for this study were given a questionnaire packet
while they waited for their doctor’s appointment. They completed the questionnaire
packets in a medium-sized furnished waiting room, and the measures took approximately
15 min to finish. Upon completing the packet, each participant was instructed to place
their consent form and questionnaires in a sealed envelope and return it to the
receptionist’s desk. From a total of 74 questionnaires that were distributed to the
participants in the doctor’s office, 74 women completed and returned their
questionnaires; thus, representing a 100% response rate. All participants were treated in

65
accordance with the guidelines for human participants as specified by the American
Psychological Association (1992). The completed questionnaire packets were mailed
back to the Principal Investigator at the end of April, 2001.
Data Analysis
Paired t-tests were undertaken with Bonferonni correction (.05/4, g = .01) to
compare participant’s: a) BMI before and after pregnancy, and b) total LTEQ scores
before pregnancy and during postpartum, c) total LTEQ scores before pregnancy and
during pregnancy, and c) total LTEQ scores during postpartum and pregnancy. To
determine the meaningfulness of these results, eta squared (q2) was calculated with .20,
.50 and .80 representing small, medium, and large effects, respectively (Cohen, 1969,
1992).
To assess the salient beliefs, I followed the recommendations of Ajzen and
Fishbein (1980) and used a 5-step procedure. First, the raw data themes (i.e., open-ended
responses) were tabulated and categorized by belief type (i.e., behavioral, normative,
control) and time (i.e., during pregnancy or postpartum). Second, the raw data themes
were organized into higher-order themes based on the procedures of Patton (1990). Third,
a content analysis was conducted to determine the most salient beliefs. Consistent with
previous researchers, the most salient beliefs were identified (i.e., the most frequent 5 to
10 beliefs; Ajzen, 1991; Carrón et al., 2003). The content analysis was conducted by: a)
sorting participant’s responses into sets of statements which involved the same
underlying belief, b) obtaining a frequency count for each set of beliefs to determine the
most salient beliefs, and c) double-checking the belief sets to ensure that all of the beliefs
were appropriately sorted (Patton). Fourth, to determine consistency in the classifications,

66
the belief sets were reviewed by four experts (i.e., two experts on the TPB and two
doctoral students specializing in exercise psychology). Fifth, the beliefs were rank-
ordered from the most to the least salient. A detailed list of the exercise beliefs for
pregnancy and postpartum are located in Table 3.2 and Table 3.3, respectively.
Results
Exercise behavior and BMI. The LTEQ total scores were significantly higher
before pregnancy (M = 33.08, SD = 27.20) compared to during pregnancy (M = 18.25,
SD_= 17.89) [t (50) = 5.81, p < .001, r\2= .40], and compared to postpartum (M = 16.56,
SD = 15.18) [t (51) = 4.38, p < .001, r]2= .27]. No significant differences were observed
in participant’s LTEQ total scores during pregnancy compared to postpartum, [t (50) =
.65, p > .05, r)2 = .01]. Participant’s BMI was significantly higher in postpartum (M =
28.26, SD = 6.07) compared to before pregnancy (M = 26.71, SD =6.32), [t (62) = 4.85,
E < .001, r|2 = .28]. Figure 3.1 presents the LTEQ total scores before, during, and after
pregnancy. Figure 3.2 displays the participant’s BMI before and after pregnancy.
Behavioral beliefs. The behavioral advantages of exercising during pregnancy
were that exercise: a) improves overall mood (33.8%), b) increases energy and stamina
(29.7%), c) assists with staying fit (21.6%), d) controls weight (18.9%), e) assists with
labor and delivery (14.9%), and f) provides stress relief (8.1%). The behavioral
disadvantages were: a) causes physical discomfort (24.3%), b) tiredness and fatigue
(24.3%), and c) time limits (10.8%). For exercising during postpartum, the advantages
were that exercise: a) controls weight (37.8%), b) assists with staying fit (36.5%), c)
improves overall mood (31.1 %), d) increases energy and stamina (10.8%), e) decreases

Table 3.2
Type. Number fNO. and Percent (%) of Beliefs Reported Purine Pregnancy
Belief Type
Higher-order Theme
Raw Data Theme(s)
Na
%
Behavioral
Beliefs
(Advantages)
Improves overall mood
Feel good, better about
self, more comfortable,
mental health, improve
mood and overall
well-being
25
33.8
Increases energy
and stamina
More energy, maintain
current level of energy,
less tired, improve
stamina and endurance
22
29.7
Stay fit
Fitness and flexibility,
stay in shape, keep muscle
tone, to walk
16
21.6
Controls weight
Keeps weight in check,
help weight
14
18.9
Assist in labor and
and delivery
Make delivery easier
and faster
11
14.9
Provides stress relief
Stress reduction,
relaxation
6
8.1
Behavioral
Beliefs
(Disadvantages)
Causes physical
discomfort
Swelling, soreness,
cramping, nausea, too
big, shortness of breath
18
24.3
Tiredness and
fatigue
Too much effort, need
to conserve energy
18
24.3
Time limits
Time limits in schedule,
no time, lacking time
8
10.8
Normative
Beliefs
Husband or fiancé
Children
27
13
36.5
17.6

68
Table 3.2 Continued
Belief Type
Fligher-order Theme
Raw Data Theme(s)
Na
%
Family members
other than husband
11
14.9
and children
Friends
9
12.2
Doctors
2
2.7
Gym instructors
2
2.7
Physical therapist
1
1.4
Control
Physical limitations
Vomiting, nausea,
42
56.8
Beliefs
and restrictions
cramps, swelling,
(Obstructing
Factors)
uncomfortable
Tiredness and
Tired, fatigued,
20
27.0
fatigue
no energy
No time
Lacking time,
time restrictions
19
25.7
Gaining weight
Weight gain, size,
too big
10
13.5
Other children
Taking care of
children, being a mom
7
9.5
Fear
Afraid to harm unborn
baby or self
7
9.5
Bad weather
Bad weather, rain,
too cold
6
8.1
No motivation
No motivation or
ambition, feel lazy
6
8.1
Control
Improves overall
Feel good, healthy,
11
14.9
Beliefs
(Facilitating
Factors)
mood
mental health

69
Table 3.2 Continued
BeliefType
Higher-order Theme
Raw Data Theme(s)
If
%
Controls weight
Keeps weight in
in check, controls
weight and feeling fat
11
14.9
Motivation
from others
Motivation from
husband, encouraging
friends
8
10.8
Stay healthy
Wanting to stay healthy
for good delivery and
a healthy baby
6
8.1
Other children
Son, daughter, children
6
8.1
Stay fit
To stay fit, stay in shape
6
8.1
Note. * = May not add up to 100% because some participants reported multiple beliefs.

70
Table 3.3
Type. Number ASP, and Percent (%) of Beliefs Reported Purine Postpartum
Belief Type
Higher-order Theme
Raw Data Theme(s)
if
%
Behavioral
Controls weight
Keep weight in check,
28
37.8
Beliefs
helps weight
(Advantages)
Stay fit
Fitness and flexibility,
stay in shape, keep
muscle tone, to walk
27
36.5
Improves overall
Feel good, better about
23
31.1
mood
self, more comfortable,
mental health, improves
mood and overall
well-being
Increases energy
More energy, maintain
22
29.7
and stamina
current level of energy,
less tired, improve
stamina and endurance
Decreases physical
Relieves leg cramps,
3
4.1
discomfort
soreness, swelling
Provides stress
Stress reduction.
2
2.7
relief
relaxation
Behavioral
Causes physical
Swelling, soreness,
17
23.0
Beliefs
discomfort
cramping, nausea, too
(Disadvantages)
big, shortness of breath
Time limits
Time limits in schedule,
no time, lacking time
16
21.6
Tiredness and
Too much effort, need
13
17.6
fatigue
to conserve energy
Difficulty with
Difficulty doing some
2
2.7
exercises
exercises
Normative
Husband or fiancé
28
37.8
Beliefs
Family members
11
14.9

71
Table 3.3 Continued
Belief Type
Higher-order Theme
Raw Data Theme(s)
Na
%
Family members
other than husband
14
18.9
and children
Friends
9
12.2
Children
7
9.5
Doctors
3
4.1
Gym instructor
1
1.4
Physical therapist
1
1.4
Control
No time
Lacking time,
36
48.6
Beliefs
time restrictions
(Obstructing
Factors)
Physical limitations
Vomiting, nausea,
16
21.6
and restrictions
cramps, swelling,
uncomfortable
Tiredness and
Tired, fatigued,
10
13.5
fatigue
no energy
Fear
Afraid to harm self
8
10.8
No motivation
No motivation or
ambition, feel lazy
6
8.1
Control
Controls weight
Keeps weight in
16
21.6
Beliefs
check, controls
(Facilitating
Factors)
weight and feeling fat
Improves overall
Feel good, healthy,
11
14.9
mood
mental health
Motivation
Motivation from
9
12.2
from others
husband and friends
Stay fit
To stay fit, stay in shape
9
12.2
Note. a = May not add up to 100% because some participants reported multiple beliefs.

72
40
35
Prior to Pregnancy During Pregnancy During Postpartum
Figure 3.1. Mean Leisure-Time Exercise Questionnaire (LTEQ) total scores for before
pregnancy, during pregnancy, and during postpartum. Women had significantly higher
LTEQ total scores before pregnancy compared to during pregnancy (p < .001) and during
postpartum (p < .001). No significant differences in LTEQ total scores were observed for
during pregnancy compared to during postpartum.
30
29
Prior to Pregnancy During Postpartum
Figure 3.2. Mean Body Mass Index (BM1) before pregnancy and during postpartum.
Women had significantly higher BM1 during postpartum compared to before pregnancy
(pc.001).

73
physical discomfort (4.1%), and f) provides stress relief (2.7%). The disadvantages were:
a) causes physical discomfort (23.0%), b) time limits (21.6%), c) tiredness and fatigue
(17.6%), and d) difficulty with some exercises (2.7%). Figure 3.3 presents the salient
advantages of exercising during pregnancy and Figure 3.4 displays the advantages of
exercising during postpartum.
Normative beliefs. For exercising during pregnancy, the normative beliefs were:
a) husband or flaneé (36.5%), b) children (17.6%), c) family members other than husband
or children (14.9%), d) friends (12.2%), e) doctors (2.7%), f) gym instructors (2.7%), and
g) physical therapist (1.4%). For exercising during postpartum, the normative beliefs
were: a) husband or flaneé (37.8%), b) family members other than husband or children
(18.9%), c) friends (14.9%), d) children (9.5%), e) doctors (4.1%), f) gym instructor
(1.4%), and g) physical therapist (1.4%). Figure 3.5 presents the salient normative beliefs
for exercising during pregnancy. Figure 3.6 displays the salient normative beliefs for
exercising during postpartum.
Control beliefs. For exercising during pregnancy, the reported control beliefs that
obstructed exercise were: a) physical limitations and restrictions (56.8%), b) tiredness
and fatigue (27.0%), c) no time (25.7%), d) gaining weight (13.5%), e) other children
(9.5%), 1) fear of harming self or the baby (9.5%), g) bad weather (8.1%), and h) no
motivation (8.1%). The control beliefs that facilitated exercise were: a) improves overall
mood (14.9%), b) controls weight (14.9%), c) motivation from others (10.8%), d) stay
healthy, e) other children (8.1%), and f) assist with staying fit (8.1%). For exercising
during postpartum, the obstructing control beliefs were: a) no time (48.6%), b) physical
limitations and restrictions (21.6%), c) tiredness and fatigue (13.5%), d) fear of harming

74
â–¡ Improves overall mood
â–  Increases energy & stamina
IS Stay fit
â–¡ Controls weight
Figure 3.3. The most salient behavioral advantages of exercising during pregnancy were:
a) improves overall mood (34%), b) increases energy and stamina (30%), c) stay fit
(22%), and d) controls weight (19%).
â–¡ Improves overall mood
â–  Increases energy & stamina
â–¡ Stay fit
â–¡ Controls weight
Figure 3.4. The most salient behavioral advantages of exercising during postpartum were:
a) controls weight (38%), b) stay fit (37%), c) improves overall mood (31%), and d)
increases energy and stamina (30%).

75
Figure 3.5. The most salient normative beliefs for exercising during pregnancy were: a)
husband or fiance (37%), b) children (18%), c) family members other than husband or
children (15%), and friends (12%).
Figure 3.6. The most salient normative beliefs for exercising during postpartum were: a)
husband or fiancé (38%), b) family members other than husband or children (19%), c)
friends (15%), and d) children (10%).

76
self (10.8%), and e) no motivation (8.1%). The facilitating control beliefs were: a)
controls weight (21.6%), b) improves overall mood (14.9%), c) motivation from others
(12.2%), and assists with staying fit (12.2%). Figure 3.7 presents the salient control
beliefs obstructing exercising during pregnancy. Figure 3.8 displays the salient control
beliefs obstructing exercising during postpartum.
Discussion
The purpose of this study was three-fold. The first purpose was to use the
theoretical framework of the TPB to examine the frequency of behavioral, normative, and
control beliefs of women regarding exercising during their pregnancy and postpartum,
and to determine which of their beliefs were most salient. The second purpose was to
assess the participant’s physical activity before pregnancy, during pregnancy, and during
postpartum with a standardized measure of exercise behavior. The third purpose was to
examine the participant’s BMI before pregnancy and during postpartum. Several findings
warrant discussion.
First, the frequency of behavioral beliefs varied from pregnancy to postpartum.
These findings are consistent with the conclusions of researchers who have suggested that
people’s beliefs can vary depending on the time and situation (Ajzen, 1991; Carrón et al.,
2003). For example, the most common behavioral advantage during pregnancy was that
exercise helped to improve women’s overall mood; whereas in postpartum, the most
common behavioral advantage was that exercise helped to control women’s weight.
Researchers aiming to increase exercise during pregnancy and postpartum should
consider the differences in women’s salient behavioral beliefs during these times.

77
Figure 3.7. The most salient control beliefs obstructing exercising during pregnancy
were: a) physical limitations and restrictions (57%), b) tiredness and fatigue (27%), and
c) no time (26%).
Figure 3,8. The most salient control beliefs obstructing exercising during pregnancy
were: a) no time (49%), b) physical limitations and restrictions (22%), and c) tiredness
and fatigue (14%).

78
Specifically, researchers conducting exercise interventions during pregnancy may want to
focus on methods that help to improve women’s overall mood (e.g., muscle relaxing and
imagery techniques). Alternatively, researchers conducting interventions during
postpartum may want to concentrate on methods that assist women in weight control
(e.g., calorie expending activities such as aerobics and running, and proper dieting).
Second, the most common normative influence during pregnancy and postpartum
was from a woman’s husband or fiancé. These findings are consistent with the
conclusions of Symons Downs (Chapter 2). Specifically, I reviewed 38 TPB and exercise
elicitation studies, and I found that the most salient normative influences for healthy and
special populations were people’s friends, spouses, physicians, and other family
members. The current findings indicate that women’s spouses have an important
influence on their exercise behavior during pregnancy and postpartum. Future researchers
are encouraged to examine other factors that may influence women’s exercise behavior
such as marital satisfaction and the type of feedback (i.e., positive versus negative) that
women receive from their spouses regarding exercising during pregnancy and
postpartum.
In addition, it is important to note that the women in this study did not indicate
that their physicians were an important normative influence for exercising during
pregnancy or postpartum. Considering that 70% of adults are examined by a healthcare
provider at least one time per year, it has been suggested that physicians may play a
valuable role in promoting exercise behavior with their patients (Logsdon et al., 1989).
However, more research is needed that examines the normative influence of physicians

79
before any conclusions can be made regarding their impact on women’s exercise
behavior during pregnancy and postpartum.
Third, the frequency of control beliefs varied from pregnancy to postpartum. The
most common control beliefs obstructing exercising during pregnancy were physical
limitations and restrictions; whereas during postpartum, the most frequently reported
obstructing control belief was having no time. Thus, researchers aiming to promote
physical activity during pregnancy may consider methods that make women feel more
comfortable (e.g., home-based exercise programs tailored to women’s specific needs and
limitations, water calisthenics). In comparison, researchers promoting physical activity
during postpartum may focus on methods that provide women with useful skills for
scheduling exercise into their daily routines (e.g., time management, organizing,
preparing, planning, goal-setting). For example, Symons Downs and Singer (2002) found
that exercise goals formed with implementation intentions (i.e., specifying where, when,
and at what time exercise would occur) assisted college students with increasing their
exercise performance over eight weeks. These same techniques may assist researchers
with promoting exercising during pregnancy and postpartum.
Fourth, consistent with the hypothesis, participant’s LTEQ total scores were
higher before pregnancy compared to during pregnancy and postpartum. That is, the
participants were engaging in more exercise before they were pregnant compared to
during their pregnancy and postpartum. These findings are consistent with previous
researchers conclusions that pregnancy can promote decreases in exercise behavior
during pregnancy and postpartum (USDFÍHS, 1996, 2000; Zhang & Savitz, 1996). While
the temporary decrease in exercise during pregnancy and postpartum may not be harmful;

80
over time, lower levels of exercise behavior are associated with increasing people’s risk
of disease, gaining weight, and decreasing longevity (USDHHS). Thus, more research is
warranted that promotes exercising during pregnancy and postpartum, and that examines
physical activity prospectively and longitudinally to determine when and if women return
to their prepregnancy exercise behavior.
Fifth, as predicted, women’s BMI was greater during postpartum compared to
before pregnancy. It is important to note that the participant’s BMI was greater than 25
before pregnancy and during postpartum; thus, classifying these women as overweight
during both of these periods (ACSM, 1999, 2000). These findings are concerning because
higher BMI is associated with an increased risk for cardiovascular disease, type II
diabetes, and obesity (USDHHS, 2000). In addition, some researchers have suggested
that higher BMI before and during pregnancy may predict the onset of depressive
symptoms occurring in postpartum (Carter et al., 2000). For example, Carter and her
colleagues found that higher BMI was not associated with anxiety and depression during
pregnancy, however, it was associated with these affective symptoms during postpartum.
Moreover, according to Ross’s (1994) Self-Reflected Appraisal Theory, when
increased weight is perceived as accepted (e.g., women may feel that gaining weight is
justified during pregnancy because they are nurturing their growing infant), higher BMI
will be less likely to influence depression. However, higher BMI during pregnancy may
exacerbate affective symptoms during postpartum (e.g., women may feel that being
overweight during postpartum can no longer be justified; Carter et al., 2000).
Furthermore, the fact that BMI had not returned to baseline values after pregnancy
illustrates the need for longitudinal studies that assess if and when women return to their

81
prepregnancy weights. This is important to examine because postpartum may be a critical
event that promotes increased weight gain, and interventions that include exercise may
assist women in controlling and maintaining their weight during postpartum (Bungum et
al., 2000; Carter et al.).
There are three limitations of this study that should be noted. First, my original
intention was to examine exercise behaviors across ethnically diverse women. However,
difficulties in recruiting participants from African American and Hispanic American
populations narrowed the participant pool to mostly middle to upper class Caucasian
Americans; and thus, there is limited generalizability in the findings to low
socioeconomic status and ethnic minority populations. Second, while BMI was measured
before and after pregnancy, it was not assessed during pregnancy. While it is assumed
that the participants’ BMI was higher during pregnancy due to the baby, it is important to
assess BMI before, during, and after pregnancy to examine how much it fluctuates
throughout the pregnancy. In addition, this information may be a helpful intervention tool
for researchers. That is, BMI can be used as a benchmark for improving women’s weight
during postpartum (e.g., women can use their BMI to keep track of their progress with
losing weight). Thus, future researchers are encouraged to measure BMI before, during,
and after pregnancy.
Third, the postpartum period was operationalized as “within one year of the
child’s birth.” However, because participants were not asked to report when they filled-
out the questionnaire packet, the time that they completed the surveys during postpartum
(e.g., 6-weeks postpartum or 6 months postpartum) could not be determined. Researchers
examining exercise beliefs during pregnancy are encouraged to record when the

82
participants complete their surveys because women’s beliefs may vary across trimesters.
For example, what women identify as obstructing factors early in pregnancy (e.g.,
nausea, vomiting) may not be the same factors that limit their exercise later on in
pregnancy (e.g., physical size, too uncomfortable). Similarly, women’s beliefs can vary
from early postpartum (e.g., exercising helps to control weight) to later in postpartum
(e.g., exercising takes away from other family and work commitments).
Prelude to Chanter 4
Pregnancy places a tremendous amount of physiological and psychological stress
on a woman’s body including changes in weight, posture, diet, and cardiovascular and
gastrointestinal functioning (Bungum et al., 2000; Wallace & Engstrom, 1987). Despite
these demands, exercise during pregnancy and postpartum is a recommended and
beneficial activity for alleviating affective symptoms (e.g., anxiety, depression) and
controlling weight gain during this time (ACOG, 1994). The findings from this study
indicated that women’s beliefs about exercising varied from pregnancy to postpartum,
and researchers aiming to understand the determinants of exercising during pregnancy
and postpartum should consider those differences when planning and implementing then-
exercise interventions. In addition, following the recommendations of Ajzen and Fishbein
(1980), the salient behavioral, normative, and beliefs elicited from this study provided the
framework for the belief measures used in Study 3. The next chapter (i.e., Chapter 4) is a
prospective study of the TPB and exercising from pregnant women’s second to their third
trimester (i.e., Study 3).

CHAPTER4
STUDY 3: EXAMINING PREGNANT WOMEN’S EXERCISE INTENTION AND
BEHAVIOR FROM THEIR SECOND TO THEIR THIRD TRIMESTER: A
PROSPECTIVE EXAMINATION OF THE THEORY OF PLANNED BEHAVIOR
Regular physical activity contributes positively to physical health (e.g.,
decreasing risk of atherosclerosis, diabetes, and obesity) and psychological well-being
(e.g., decreasing anxiety and depression; USDHHS, 1996, 2000). Despite these benefits,
approximately 58% of pregnant women are sedentary, which is almost twice the national
average for sedentary adults (i.e., 30% of U.S. adults are sedentary; USDHHS; Zhang &
Savitz, 1996). This is alarming because low physically active and sedentary lifestyles are
associated with a greater risk of disease, poorer mental health, and increased weight
(USDHHS). Thus, it is important to understand the facilitating and obstructing factors of
exercising during pregnancy to increase women’s physical activity during this time.
Pregnancy is associated with a variety of physical (e.g., increased cardiac output,
ventilation, and weight) and psychological (e.g., symptoms of anxiety, stress, and
depression) demands; and thus, many women either decrease or stop exercising during
this time (Bungum et al., 2000; Monk et al., 2000; Zuckerman et al., 1989). Despite the
challenges of pregnancy, exercise is a safe and beneficial activity for most women
(Lokey et al., 1991). For example, Lokey and his colleagues meta-analytically examined
the physical effects of exercising during pregnancy, and they concluded that regular
physical activity is not associated with harming either the mother or the fetus. Exercising
during pregnancy also has psychological benefits such as decreasing anxiety and
83

84
depression, and improving self-esteem, mood, and body image (Bungum et al., 2000;
Koniak-Griffin, 1994; Walker et al., 1999). In addition, exercising during pregnancy
controls excessive weight gain, which is important considering that 30% of normal
weight and 60% of overweight women gain more weight during their pregnancy than is
recommended (i.e., normal weight gain is 20 to 30 lbs; Polley, 2001). Researchers have
found that greater weight gain during pregnancy is associated with negative affective
symptoms (e.g., anxiety and depression), and greater postpartum weight retention in both
pregnancy and postpartum (Carter et al., 2000; Polley). Thus, exercise is a valuable
method for managing the physical and psychological challenges of pregnancy (Bungum
et al.).
Although exercising during pregnancy contributes to women’s health (ACOG,
1994; USDHHS, 2000), the research examining women’s attitude, behavior, and
cognition about exercising during their pregnancy is scant and limited by several
conceptual and methodological factors (see Chapter 3 for a detailed list). A main
conceptual concern is the lack of theoretical research that examines exercise behavior
during pregnancy. For example, while the theory of planned behavior (TPB; Ajzen &
Fishbein, 1980; Ajzen, 1991) has been successfully applied to exercise behavior in
healthy populations (see Symons Downs & Hausenblas, 2002 for a statistical review), its
application to exercise behavior during pregnancy is scant. Moreover, Symons Downs
(Chapter 3) found that only three studies from a recent meta-analysis of the TPB and
exercise (i.e., Symons Downs & Hausenblas) included pregnant populations, and these
studies were limited by methodological issues (Godin et al., 1994; Godin et al., 1993;
Godin et al., 1989).

85
For instance, Godin et al. (1989) examined 98 pregnant women’s attitude,
subjective norm, perceived barriers, and habit in predicting their intention to exercise
after giving birth. Godin and his colleagues found that perceived barriers was the
strongest predictor of intention. However, the predictive utility of the TPB was
compromised when the authors substituted perceived barriers for perceived behavioral
control and added habit to the model. That is, according to Ajzen and Fishbein, when
constructs other than the theoretical tenets of the TPB are substituted or added to the
model, the predictive utility of the TPB is jeopardized.
In addition, Godin et al. (1993) examined 136 pregnant women’s attitude,
perceived behavioral control, and habit in predicting their exercise intention and
behavior. The authors found that all three constructs predicted intention; however, only
habit predicted exercise behavior. While Godin and his colleagues concluded that
perceived behavioral control contributed to the understanding of intention but not
behavior, this assumption was compromised by not including subjective norm in the
model, and by adding habit to the model (Ajzen & Fishbein, 1980).
Moreover, only Godin et al. (1994) followed Ajzen and Fishbein’s (1980)
recommendations and conducted an elicitation study to establish the participants’ salient
beliefs about exercising during their pregnancy. Godin and his colleagues assessed
postpartum women’s control beliefs for exercising during pregnancy, and they found that
the most important beliefs were lactation constraints, lack of time, physical health
problems for the mother and baby, and difficulties adapting to life after pregnancy.
However, the authors did not obtain the salient behavioral and normative beliefs of these
women. Thus, because women’s exercise behavior can decrease during pregnancy, and

86
because there are few studies assessing the TPB constructs and exercise with pregnant
populations, more research is needed that examines pregnant women’s behavioral,
normative, and control beliefs for exercising during pregnancy. In addition, research is
needed that examines the utility of the TPB constructs (i.e., attitude, subjective norm,
perceived behavioral control) in predicting pregnant women’s exercise intention and
behavior.
A second limitation with the exercise and pregnancy literature is that most of the
research is cross-sectional (e.g., Koniak-Griffin, 1994), and few studies have
prospectively examined pregnant women’s exercise behavior. Thus, there is a need for
research that prospectively examines the determinants of exercising during pregnancy.
While the framework of the TPB allows researchers to prospectively examine the
constructs, the literature examining the TPB and exercising during pregnancy is scant.
More specifically, no studies have been found examining the TPB and exercising from
pregnant women’s second to their third trimester. Moreover, prospective investigations of
the TPB and exercising during pregnancy are needed to determine which of the TPB
constructs most strongly predict exercise intention and behavior from pregnant women’s
second to their third trimester. This information can assist researchers with developing
exercise and pregnancy interventions that are specific to the needs of women during these
trimesters.
A third limitation of the exercise and pregnancy literature is the lack of research
examining exercise behavior during pregnancy with standardized exercise measures
(Eisen et al., 1991). That is, most of the studies examining exercising during pregnancy
are based on dichotomous (yes/no) self-report items (e.g., “Do you participate in regular

87
physical activity during pregnancy?”), nonstandardized author-developed questionnaires,
and frequency or duration of exercise behavior (Stemfeld, 1997). For example, Kulpa,
White, and Visscher (1987) classified pregnant women as exercisers if they participated
in aerobic exercise more than once per week for at least 15 min. This type of
classification is problematic because women are being categorized as exercisers when
they may only be exercising twice a week, which is less than the prescribed exercise
guidelines (Le., ACOG, 1994; ACSM, 2000). In addition, because the ACOG
recommends that women do not exceed 144 bpm when exercising during their
pregnancy, it is necessary to examine exercise intensity with a standardized measure of
exercise. For example, the Leisure-Time Exercise Questionnaire (Godin et al., 1986)
assesses the frequency of strenuous, moderate, and mild leisure-time exercise, which can
assist researchers in determining women’s exercise intensity during their pregnancy, and
if women are meeting the ACOG guidelines for exercising during their pregnancy. In
short, research is needed that examines exercising during pregnancy with standardized
self-report measures such as the Leisure-Time Exercise Questionnaire.
Finally, researchers have found that pregnancy is associated with increased
negative mood and body image disturbance (Bungum et al., 2000; Koniak-Griffin, 1994).
This is important considering that weight gain during pregnancy is associated with
negative affective symptoms (e.g., anxiety, stress, depression) during pregnancy and
postpartum (Cameron et al., 1996). For example, researchers have found that 8% of
women are concerned about their weight during pregnancy, and 75% of women are
unhappy with their weight during the first few weeks of postpartum (Baker, Carter,
Cohen, & Brownell, 1999; Hisner, 1986). However, the research prospectively examining

88
body mass index and exercise behavior during pregnancy is scant. In one of the few
located prospective studies, Carter and her colleagues (2000) found that higher body
mass index was not associated with negative affect (i.e., anxiety and depression) during
pregnancy, whereas it was associated with these symptoms during the first four weeks of
postpartum. These findings illustrate that higher body mass index can place women more
at risk for experiencing mood disturbances during postpartum. Thus, there is a need to
prospectively examine body mass index during pregnancy. In summary, the absence of
studies prospectively examining the TPB, body mass index, and exercise behavior during
pregnancy demonstrates that more research examining these constructs is warranted.
There were four purposes of this study. The first purpose was to prospectively
examine the utility of the TPB in predicting pregnant women’s exercise intention and
behavior from their second to their third trimester. Consistent with the findings of
previous researchers (i.e., Symons Downs & Hausenblas, 2002) for exercise behavior, it
was hypothesized that intention and perceived behavioral control would predict exercise
behavior, with intention being the strongest predictor of exercise behavior. For intention,
it was hypothesized that attitude, perceived behavioral control, and subjective norm
would predict intention, with attitude being the strongest predictor of intention.
The second purpose was to examine the associations among the TPB constructs.
Based on theoretical assumptions of Ajzen and Fishbein (1980; Ajzen, 1991), it was
hypothesized that during the second pregnancy trimester women’s behavioral beliefs
would be positively associated with their attitude, their normative beliefs would be
positively associated with their subjective norm, and their control beliefs would be
positively associated with their perceived behavioral control.

89
The third purpose was to examine pregnant women’s mild, moderate, and
strenuous physical activity during their second and third trimester. It was hypothesized
that the participants would engage in more mild, moderate, and strenuous physical
activity in their second compared to their third trimester (ACOG, 1994; Zhang & Savitz,
1996). The fourth purpose was to examine pregnant women’s body mass index during
their second and third trimester. Based on the conclusions of previous researchers (i.e.,
Carter et al., 2000), it was hypothesized that participants’ body mass index would be
higher in their third trimester compared to their second trimester.
Method
Participants
Participants were 81 pregnant women (M age = 29.93 years, SD = 4.52, age range
= 22 to 43 years). The majority of participants were Caucasian (87.7%), married (88.9%),
college graduates (49.4%), worked full-time (56.8%), had an occupation in medicine
(23.5%) and education (22.2%), or they were homemakers (22.2%), and they earned a
family income of between $40,000 and $ 100,000 per year (61.7%). In addition, most of
the participants were not on maternity leave (93.8%) and had 1 child (43.2%; see Table
4.1). In addition, correspondence was obtained between the participants in Study 2 (i.e.,
the elicitation study) and the participants in this study (i.e., the main TPB study; see
Table 4.2).
Measures
Personal History Questionnaire. The Personal History Questionnaire was
developed for this study, and it assessed the following information: age, height, weight,

90
Table 4.1
The Number INI and Percent (%) of Demographic Characteristics for the Participants
Characteristic
N
%a
Race/Ethnicity
Caucasian
71
87.7
Asian American
2
2.5
Other
1
1.2
Marital Status
Married
72
88.9
Single
5
6.2
Divorced
2
2.5
Common Law
1
1.2
Employment
Full-time
46
56.8
Homemaker
22
27.2
Part-time
10
12.3
Unemployed
1
1.2
Self-employed
1
1.2
Other
1
1.2
Occupation
Medicine
19
23.5
Nurse
8
Dental assistant
4
Physical therapist
3
Doctor
2
Medical technologist
2
Education
18
22.2
Teacher
7
Professor
4
School counselor
4
Researcher
3
Mother/housewife
18
22.2
Business
16
19.8
Manager
9
Secretary/Administrative Assistant
7
Service
4
4.9
Police officer
2
Cashier
1
Waitress
1
Education
Less than high school
1
1.2
High school
8
9.9
College
40
49.4

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Table 4.1 Continued
Characteristic
N
%a
Graduate or professional
28
34.6
Trade school
2
2.5
Other
1
1.2
Family Income
Less than $10,000
1
1.2
$10,000 to $20,000
3
3.7
$20,000 to $40,000
12
14.8
$40,000 to $100,000
50
61.7
greater than $100,000
10
12.3
Children
No children
32
39.5
1 child
35
43.2
2 children
10
12.3
3 children
2
2.5
Note. “May not add up to 100% due to missing data.

92
Table 4.2
Corresponding Demographic Characteristics for the Elicitation Study Participants and the
Main Theory of Planned Behavior 1TPB ) Study Participants
Characteristic
Elicitation Study
Main TPB Study
N
74
81
M age (SD)
31.30(4.37)
29.93 (4.52)
Age range
19 to 40 years
22 to 43 years
Marital status (married)
86.5%
88.9%
Race/ethnicity majority
(Caucasian)
81.1%
87.7%
Education majority
(college graduates)
44.6%
49.4%
Family income majority
($40,000 to $100,000)
62.2%
61.7%
Note. N = number of participants, M = mean, SD = standard deviation.
race/ethnicity, socioeconomic status, marital status, highest level of education achieved,
employment, family income, date of conception, baby’s due date, number of children,
and home address (see Appendix G).
Body Mass Index (BMP. BMI is a reliable estimate of obesity (Garrow &
Webster, 1985), and it is calculated by converting self-reported weight from pounds to
kilograms, and by transforming self-reported height from inches to meters (kg/m2). There
is a 5% standard error when using BMI to estimate body fat percentage (ACSM, 2000).
Leisure-Time Exercise Questionnaire (l.TEOl. The LTEQ (Godin et al., 1986)
assesses the frequency of mild, moderate, and strenuous leisure-time exercise that is done
for at least 15 min during an average week (see Appendix C). A total LTEQ score is
calculated by adding the sum of the weighted exercise frequencies: (mild*3) +
(moderate*5) + (strenuous*9). The LTEQ is a valid and reliable measure of exercise
behavior (Jacobs et al., 1993).

93
Elicitation study. According to Ajzen and Fishbein’s (1980; Ajzen, 1991)
guidelines, an elicitation study was necessary to establish the salient exercise behefs of
the participants in this study. The elicitation study was performed beforethis study, and
the behavioral, normative, and control belief items listed below were generated from the
elicitation study findings (see Chapter 3 for the elicitation study findings).
Behavioral beliefs. The following seven items emerged in the elicitation study as
the most salient behavioral advantages about exercising during pregnancy: a) help to
improve my overall mood, b) help to increase my energy/stamina, c) help to assist in my
labor/delivery, d) help to keep me fit, e) make me feel tired/fatigued, f) be difficult due to
time limits in my schedule, and g) produce stress relief. These items were preceded by
the statement “Exercising regularly during my second trimester of pregnancy does/will
,” and they were rated on a 7-point Likert Scale ranging from 1 (extremely unlikely)
to 7 (extremely likely; see Appendix H). The internal consistency score for these seven
items was good (alpha = .89).
Normative beliefs. The normative beliefs that emerged as the most salient from
the elicitation study were: a) husband or fiancé/partner, b) friends, c) children, d) family
members other than one’s husband and children, e) doctors, and f) nurses. Each
normative belief was preceded by the statement “How strongly does/will each of the
following persons approve or disapprove of you exercising regularly during your second
trimester of pregnancy?” (see Appendix I). These items were assessed with a 7-point
Likert scale ranging from 1 (extremely unlikely) to 7 (extremely likely), and the internal
consistency score of these six items was excellent (alpha = .90).

94
Control beliefs. The following nine control belief items emerged from the
elicitation study as the most common factors obstructing exercising during pregnancy: a)
having other children to care for, b) gaining weight, c) experiencing bad weather, d)
having physical limitations and restrictions, e) having no time to exercise, f) having no
motivation to exercise, g) experiencing fatigue or tiredness, h) having a fear of harming
the unborn baby, and i) having a fear of harming myself. These items were preceded by
the statement “How strongly does/will each of the following items influence your level of
regular exercise during your second trimester of pregnancy?” These items were assessed
with a 7-point Likert scale ranging from 1 (extremely unlikely) to 7 (extremely likely; see
Appendix J). The internal consistency score of the nine control belief items was adequate
(alpha = .79).
Attitude. Based on Ajzen and Fishbein’s (1980; Ajzen, 1991) recommendations,
the following seven semantic differential pairs were used to assess pregnant women’s
attitude about exercise: a) useless-useful, b) harmful-beneficial, c) bad-good, d) foolish-
wise, e) unpleasant-pleasant, f) unenjoyable-enjoyable, and g) boring-interesting (see
Appendix K). The statement “Exercising during my second trimester of pregnancy is/will
be” preceded these item pairs, and they were assessed with a 7-point unipolar scale
ranging from 1 (i.e., useless, harmful, bad, foolish, unpleasant, unenjoyable, boring) to 7
(i.e., useful, beneficial, good, wise, pleasant, enjoyable, interesting). The internal
consistency score of these seven attitude items was good (alpha = .89).
Subjective norm. Subjective norm was assessed with the following item: “People
who are important to me think that I should exercise during my second trimester of
pregnancy,” ranging from 1 (strongly disagree) to 7 (strongly agree; see Appendix L). A

95
single item to measure subjective norm is consistent with previous research (Ajzen,
1991).
Perceived behavioral control. Consistent with previous research, the following
three items were used to measure perceived behavioral control: a) “For me to exercise
during my second trimester of pregnancy is/will be ” ranging from 1 (extremely
difficult) to 7 (extremely easy); b) “If I wanted to, I can easily exercise during my second
trimester of pregnancy” ranging from 1 (strongly disagree) to 7 (strongly agree); and c)
“How much control do you have over exercising during your second trimester of
pregnancy?” ranging from 1 (very little control) to 7 (complete control; Coumeya,
Friedenreich, Arthur, & Bobick, 1999; see Appendix M). The internal consistency score
for these three perceived behavioral control items was good (alpha = .85).
Intention. Following the recommendations of Coumeya and McAuley (1993), the
following continuous-open item was used to assess intention: “It is my intention to
exercise days a week during my second trimester of pregnancy” ranging from 1 to 7
days a week (see Appendix N). A single item to assess intention was necessary to obtain
scale correspondence (Coumeya & McAuley, 1994, 1995).
Exercise behavior. Coumeya and McAuley’s (1995) recommended that a
continuous-open format should be used to achieve scale correspondence between the
measure of intention and behavior. Thus, exercise behavior was measured with the
following continuous-open item: “I exercised days a week during my second
trimester of pregnancy” ranging from 1 to 7 days a week (see Appendix O). A single item
to measure exercise behavior is consistent with previous research (i.e., Bonzionelos &
Bennett, 1999).

96
Procedure
Approval to conduct the study was obtained from the University’s Institutional
Review Board (see Appendix P). In May 2001, the Principal Investigator was given the
consent of a private practice physician specializing in obstetrics and gynecology to
collect data from her office, and the data collection procedures began on June 1, 2001.
Upon the participants’ first prenatal visit to the doctor’s office, the intake nurse gave
them a form explaining the study (see Appendix Q). The participants volunteering for the
study were then given the consent form (see Appendix R) and the Personal History
Questionnaire. Completion of these two forms took approximately 5 min. Participants
returned the consent form and the questionnaire to the nurse, and they were then told that
the next questionnaire packet would be sent to them in the mail.
Approximately three months from the time they completed the Personal History
Questionnaire (i.e., during their first four weeks of their second trimester), 180
participants received a questionnaire packet with a cover letter (see Appendix S), the
LTEQ, and two personal history items (i.e., height and weight to calculate BMI). They
were asked to return their completed questionnaires to the Exercise Psychology
Laboratory in the business-reply envelope that was provided. In an attempt to improve
the response rate, several procedures were conducted (Ransdell, 1996). First, the cover
letters were printed on department letterhead, and they were personalized with a hand
written note requesting the women’s participation. Second, the questionnaire packets
were printed on bright colored paper (i.e., blue and yellow) to make the survey more
attractive. Third, for those participants not returning the questionnaire, a post-card
reminder was mailed out to participants one week after their second trimester mailing

97
(see Appendix T). If the participant did not return the questionnaire within the following
week, another second trimester packet was sent. If the participant still did not return her
second trimester questionnaire (n = 31), her data were coded “did not return,” and she
was eliminated from the third trimester mailing. Participants withdrawing from the study
during the second trimester (n = 18) did so for one of the following reasons: a)
miscarriage (n = 13), b) did not wish to participate (n = 2), c) complications restricting
exercise (n = 2), and d) refused mail (n = 1). In addition, returned mail packets from
participants that did not have a forwarding address (n = 4) were dropped from the study.
Participants who returned their second trimester questionnaire (n = 127;
representing a 71.1% response rate) were sent another packet during their first four weeks
of their third trimester that contained the cover letter (see Appendix U), the LTEQ, and
two personal history items (i.e., height and weight to calculate BMI). Again, participants
were asked to return their completed questionnaires to the lab in the return envelope that
was provided. The same procedures that were used for improving the second trimester
response rate were also used for the third trimester. Reasons for participant attrition
during the third trimester included: a) did not return their questionnaire (n = 43), b)
experienced pain and put on bed rest (n = 2), and c) received return mail without a
forwarding address (n = 1). Participants completing both their second and third trimester
packets (n = 81) were included in the data analyses. This represents a response rate of
63.8% (N = 81/127) from the second trimester, and 45.0% (N = 81/181) from the original
sample. All participants were treated in accordance with the APA’s (1992) guidelines for
human participants. The data collection procedures were finished in May 2002.

98
Data Analysis
Descriptive statistics were used to describe the participant characteristics. To
examine the first study purpose (i.e., the utility of the TPB in predicting pregnant
women’s intention and behavior from their second to their third trimester), two forced
entered hierarchical regression analyses were conducted. Based on Green’s (1991)
guidelines, adequate power was obtained to conduct these analyses. The order and
content of the blocks of variables for the regression procedures were based on the
theoretical tenets of the TPB and previous research (Ajzen, 1991; Coumeya &
Friedenreich, 1997, 1999; Symons Downs & Hausenblas, 2002). In the first regression
model, exercise behavior (dependent variable) was regressed on intention (Block 1),
followed by perceived behavioral control (Block 1). In the second regression model,
intention (dependent variable) was regressed on attitude and subjective norm (Block 1),
and attitude, subjective norm, and perceived behavioral control (Block 2).
To examine the second study purpose, bivariate correlations were conducted to
determine the association between behavioral beliefs and attitude, normative beliefs and
subjective norm, and control beliefs and perceived behavioral control. To examine the
third and fourth study purposes, paired t-tests were undertaken with Bonferonni
correction (.05/4, p = .01) to determine if women’s mild, moderate, and strenuous
exercise behavior was greater in their second compared to their third trimester (i.e., third
purpose), and if women’s BMI was greater in their third compared to their second
trimester (i.e., fourth purpose). To determine the meaningfulness of these findings, eta
squared (p2) was calculated with .20, .50, and .80 representing small, medium, and large

99
effects, respectively (Cohen, 1969, 1992). All statistical tests were conducted with alpha
set at .05.
Results
Predicting intention and behavior. In the first regression, intention and perceived
behavioral control (Block 1) explained 43% of the variance in exercise behavior,
(dependent variable), F (2, 72) = 26.23, p < .001. Intention ((3 = .53, g < .001) was a
significant predictor of behavior. Perceived behavioral control was not a significant
predictor of behavior, however, it did approach significance (P = .20, g = .07). In the
second regression model, attitude and subjective norm (Block 1) explained 26% of the
variance in intention (dependent variable), F (2, 72) = 12.47, g < .001. Perceived
behavioral control (Block 2) explained an additional 5% of the variance in intention,
Echange (1,71) = 5.32, g = .024), with attitude (P = .26, g = .047) and perceived behavioral
control (p = .31, g = .024) maintaining their unique contribution, and perceived
behavioral control emerging as the strongest predictor of intention (see Table 4.3).
TPB associations. Pearson correlations were undertaken and the results indicated
that the attitude-behavioral beliefs (r = .464, g < .01) and the subjective norm-normative
beliefs (r = .613, g < .01) associations were significant. The perceived behavioral control-
control beliefs (r = -.143, g > .05) association was not significant (see Table 4.4).
Exercise behavior and BMI. The LTEQ mild, moderate, and strenuous exercise
scores were not significantly higher in the second trimester compared to the third
trimester (g’s > .05). Participants’ BMI was significantly greater during their third
trimester (M = 27.73, SD = 5.35) compared to their second trimester (M = 25.33, SD =
5.22) of pregnancy, t (61) = 7.18, g < .001 (see Table 4.5).

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Table 4.3
Hierarchical Regression Analyses for the Theory of Planned Behavior Constructs
Variable
R2
E
Echange
E
Beta
Predicting Behavior
Block 1
.428
26.23
.000
1. Intention
.000
.533
2. Perceived behavioral control
.068
.195
Predicting Intention
Block 1
.257
12.47
.000
1. Attitude
.004
.364
2. Subjective norm
.091
.207
Block 2
.309
10.59
5.32
.000
1. Attitude
.047
.256
2. Subjective norm
.549
.078
2. Perceived behavioral control
.024
.309

Table 4.4
Correlations. Means (Ml, and Standard Deviations (SD1 Among the Theory of Planned Behavior Constructs
Variable 2
3
4
5
6
7
8
M
SD
1. Behavior .632**
.349**
.357**
.480**
.148
.364**
.008
2.60
1.68
2. Intention
.477**
.401**
.504**
.343**
.382**
-.189
3.39
1.38
3. Attitude
.535**
.561**
.464**
.468**
-.174
5.47
1.02
4. Subjective norm
.629**
.410**
.613**
-.110
4.99
1.55
5. Perceived behavioral control
.185
.455**
-.143
4.69
1.29
6. Behavioral beliefs
.412**
-.107
5.83
0.86
7. Normative beliefs
-.093
5.47
1.18
8. Control beliefs
4.20
1.16
Note. ** = g < .01.

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Table 4.5
Number (NI. Means (Ml. Standard Deviations (SDl. t-test Mean Comparisons, and Eta
Squared Values (til for the Leisure-Time Exercise Questionnaire (LTBO) and Body Mass
Index (BMP
Variable
N
M
SD
LTEQ
Mild exercise, t (53) = .00, p = 1.00, q = .00
Second trimester
54
8.69
6.07
Third trimester
54
8.69
6.63
Moderate exercise, t (58) = .60, g = .55, q = .01
Second trimester
59
9.41
8.76
Third trimester
59
8.77
8.76
Strenuous exercise, t (55) = 1.39, g = . 17, q = .03
Second trimester
56
4.74
10.35
Third trimester
56
2.73
9.85
BMI. t (61) = 7.18, g < .001, q = .46
Second trimester
62
25.33
5.22
Third trimester
62
27.73
5.35
Discussion
There were four purposes of this study. The first purpose was to prospectively
examine the utility of the TPB in predicting pregnant women’s intention and behavior.
The second purpose was to determine the associations among the TPB constructs. The
third purpose was to examine pregnant women’s mild, moderate, and strenuous exercise
behavior during their second and their third trimesters. The fourth purpose was to
examine pregnant women’s BMI during their second and their third trimesters.
In general, it was found that the TPB was successful in predicting pregnant women’s
exercise intention and behavior. Several findings warrant discussion.
First, consistent with the hypothesis and previous researchers’ conclusions,
intention was the strongest predictor of pregnant women’s second trimester exercise

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behavior (Blue, 1995; Hausenblas et al., 1997; Symons Downs & Hausenblas, 2002).
These findings illustrate that pregnant women’s motivation to exercise (i.e., their
intention), and not their evaluation of the ease or difficulty of participating in exercise
(i.e., their perceived behavioral control), most strongly influences their exercise behavior
during their pregnancy. Researchers aiming to increase exercise behavior during
pregnancy may want to more closely examine women’s intention to exercise. That is,
they may want to focus on women’s plans or objectives for exercising during their
pregnancy. For example, one technique that can be used in an intervention designed to
promote physical activity during pregnancy is the use of implementation intentions (i.e.,
specifying where, when, and how their exercise behavior will occur). Gollwitzer and his
colleagues (Gollwitzer, 1999; Gollwitzer & Brandstatter, 1997; Gollwitzer & Moskowitz,
1996) have proposed that implementation intentions can strengthen people’s intention to
engage in behavior. Future researchers examining exercising during pregnancy are
encouraged to use methods that can positively influence women’s intention to exercise.
Second, partial support was found for the hypothesis regarding the prediction of
intention. More specifically, it was hypothesized that attitude and perceived behavioral
control would contribute in predicting intention, and that attitude would be the strongest
predictor of intention. Flowever, in contrast to the hypothesis, perceived behavioral
control was found to be the strongest predictor of intention. These findings are consistent
with previous researchers’ conclusions that perceived behavioral control is a stronger
predictor of exercise intention than attitude and subjective norm (Brenes et al., 1998;
Coumeya, Nigg, & Estabrooks, 1998). For example, Brenes and her colleagues
prospectively examined the TPB constructs and older adults’ exercise participation, and

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they found that perceived behavioral control was the only predictor of intention. In
addition, Godin et al. (1993) found that perceived behavioral control was a strong
predictor of 136 pregnant women’s intention.
Thus, pregnant women’s perceptions of the ease or difficulty in engaging in
exercise (i.e., their perceived behavioral control) may more strongly influence their
intention than how they feel about exercise (i.e., their attitude). For example, even if
women enjoy exercising, evaluate it positively, and believe that it has a number of
physical and psychological benefits, certain factors (e.g., nausea, vomiting, fatigue, pain)
that are unique to pregnancy may have a stronger impact on their intention to exercise.
Understanding which exercise determinants have a stronger impact on pregnant women’s
intentions can assist researchers with designing effective interventions for promoting
exercising during pregnancy. For example, researchers can design exercise programs that
can alleviate some of the negative symptoms of pregnancy while also allowing women to
experience the benefits of exercise (e.g., combining progressive muscle relaxation
techniques with yoga or water calisthenics).
Moreover, the finding that subjective norm did not contribute to the prediction of
intention is consistent with the conclusions of previous researchers (e.g., Symons Downs
& Hausenblas, 2002), and it suggests that the influence of significant others has less of an
influence on pregnant women’s intention to exercise from their second to their third
trimester compared to their perceived behavioral control and attitude. One explanation for
why subjective norm did not predict pregnant women’s intention is that there may be
limitations with how subjective norm is operationalized (Hausenblas et al., 1997). In
addition, Coumeya and McAuley (1995) have suggested that inconsistencies in

105
measuring subjective norm may be associated with why it is frequently a poor predictor
of people’s exercise intention. These authors found that social support (i.e., the assistance
that people receive through interpersonal contact) was more strongly related to people’s
exercise behavior than subjective norm. Thus, because social support was not examined
as a purpose of this dissertation, more research is needed that examines its influence on
pregnant women’s intention to exercise during their pregnancy.
Third, as predicted, pregnant women’s behavioral beliefs were positively
associated with their attitude, and their normative beliefs were positively associated with
their subjective norm. These findings are consistent with the theoretical assumptions of
the TPB (Ajzen, 1991). However, in contrast to the hypothesis, women’s control beliefs
were not significantly associated with their perceived behavioral control. One explanation
for these findings may have to do with pregnant women’s evaluations of the obstructing
factors that limit their exercise participation during pregnancy. Specifically, pregnancy is
a time in women’s lives that is associated with a variety of physical and psychological
demands, however, not all women perceive these demands as barriers to exercise
(Bungum et al., 2000). It is possible that some of the participants in this study believed
that certain control beliefs (e.g., physical limitations, feeling tired and fatigued, gaining
weight) may influence their exercise behavior during their pregnancy; however, they may
also perceive that they can continue to exercise despite these factors. Thus, pregnancy
may be a unique time in which women’s control beliefs and their perceived behavioral
control are incongruent. More research is needed, however, before any conclusions can
be made regarding the association between control beliefs and perceived behavioral
control during pregnancy.

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Fourth, in contrast to the hypothesis, pregnant women’s exercise behavior was not
significantly higher in their second compared to their third trimester. Although these
findings were nonsignificant, examining the mean LTEQ scores revealed that women
were engaging in approximately the same amount of mild exercise, and slightly more
moderate and strenuous exercise in their second compared to their third trimester.
However, the frequency of mild, moderate, and strenuous exercise during both of these
trimesters (i.e., 1-2 days of mild and moderate, and less than 1 day of strenuous exercise
per week) was still below the recommended guidelines for exercising during pregnancy
(i.e., 3-5 days per week of moderate to strenuous exercise for 15-30 min, depending on
physical conditioning; ACOG, 1994). On a positive note, these findings also indicate that
women’s exercise behavior did not decline from their second to their third trimester.
This is important because women are expected to have the greatest decline in exercise
during their third trimester (ACOG). Thus, more research is warranted that prospectively
examines exercise behavior during the first, second, and third trimesters, as well as
during postpartum to determine when, if ever, women meet the prescribed exercise
guidelines (ACOG; ACSM, 1999, 2000).
Fifth, consistent with the hypothesis and previous research (e.g., Carter et al.,
2000), pregnant women’s BMI was greater in their third compared to their second
trimester. It is important to note that women’s second and third trimester BMI was
greater than 25, classifying them as overweight (USDHHS, 2000). While weight gain is
expected during pregnancy, excessive weight gain can lead to physical and psychological
problems such as increased negative aftect during pregnancy and postpartum (i.e.,
anxiety and depression; Bungum et al., 2000), physical complications during labor and

107
delivery (Carter et al.), and an increased risk of diseases such as diabetes, obesity, and
heart disease (USDHHS). Healthcare professionals aiming to control women’s weight
during pregnancy may want to prescribe an exercise program that allows them to expend
energy (e.g., walking or swimming), yet prevents them from exceeding the ACOG (1994)
guidelines for maximum heart rate and body temperature. Future research is needed that
longitudinally examines women’s BMI during pregnancy and postpartum to determine
when and if their BMI decreases within a healthy range.
While this study has improved on previous TPB, exercise, and pregnancy studies
by examining the TPB constructs prospectively and by using a standardized measure of
exercise behavior, there are four limitations that should be considered when interpreting
these findings. First, similar to Study 2, the majority of participants were well-educated,
of middle to high socioeconomic status, and Caucasian. Thus, the findings from this
study have limited generalizability to people of low socioeconomic status, the less
educated, and racial or ethnic minorities. While it was my original intention to examine
the exercise behavior of a variety of populations, difficulty with recruiting ethnically
diverse and low socioeconomic status participants restricted the data collection. Thus,
future research is warranted that examines exercising during pregnancy across a variety
of at risk for sedentary behavior populations. Second, because the study measures were
assessed in a noncontrolled environment, the effect that extraneous factors (i.e., time and
place the questionnaires were completed, environmental cues such as exercise magazines
and pamphlets in the doctor’s office, and feedback from others) had on participants’
responses cannot be determined. However, it should be noted that the TPB was
successful in predicting pregnant women’s exercise intention and behavior during their

108
second to their third trimester despite the potential influences of extraneous variables.
Third, it is important to note that the study measures were self-report. While the use of
self-report instruments to measure exercise behavior is acceptable, researchers are
encouraged to also use objective measures such as heart rate or exercise tests (e.g., 1-mile
walk, cycle ergometer) to more accurately assess exercise behavior (Carrón et al., 2003;
Sallis & Owen, 1998). In addition, self-reported height and weight was used to calculate
women’s BMI. Researchers are encouraged to obtain actual height and weight
measurements, as well as objective measures (e.g., skin fold and circumference
measurements) to more accurately assess women’s body composition. Finally, while the
response rate of this study is comparable to other studies examining exercise behavior
with self-report measures (e.g., Craig, Goldberg, & Dietz, 1996), it was not 100%. That
is, despite following Ransdell’s (1996) procedures to improve the response rate (e.g.,
cover letters with personalized notes, multicolored questionnaires), several participants
(36.2%) dropped out of the study from the second to the third trimester. Thus, researchers
are encouraged to use additional reminder techniques (e.g., phone calls, flyers at the
doctors office) to increase the response rate.
In conclusion, the findings of this study suggest that the TPB provides researchers
with a conceptual framework for examining pregnant women’s exercise intention and
behavior. By understanding women’s beliefs, thoughts, and perceptions about exercising
during their pregnancy, intervention specialists can develop and implement effective
programs promoting exercising during this time. In addition, the findings from this study
can help future researchers with designing longitudinal studies examining the TPB
constructs and exercising during pregnancy. Finally, healthcare professionals can use the

109
findings of this study to guide their education programs for pregnant women. That is,
women who are informed about the benefits of exercising during their pregnancy, and
who are taught how to exercise properly during this time may engage in increased
exercise behavior.

CHAPTER 5
GENERAL DISCUSSION
The general objective of this dissertation was to examine the predictive utility of
the theory of planned behavior (TPB; Ajzen, 1991) in explaining pregnant women’s
exercise intention and behavior. In an attempt to achieve this objective, and adhere to the
theory guidelines established by Ajzen and Fishbein (1980), the following three studies
were conducted:
• The TPB and elicitation studies: A systematic review of exercise beliefs (Study 1).
• The TPB and exercising during pregnancy and postpartum: An elicitation study
(Study 2).
• Examining pregnant women’s exercise intention and behavior from their second to
their third trimester: A prospective examination of the TPB (Study 3).
There are four purposes of this chapter. The first purpose is to summarize the main
findings, strengths, limitations, and conclusions of Studies 1,2, and 3. The second
purpose is to identify recommendations for future research with the TPB, exercise, and
pregnant populations. The third purpose is to discuss the practical implications of this
dissertation. The fourth purpose is to provide a general conclusion.
Summary of the Dissertation Studies
Study 1
Main findings. The primary purpose of Study 1 (Chapter 2) was to review the
salient behavioral, normative, and control beliefs of exercise elicitation study
participants. The secondary purpose was to examine elicitation study methods (i.e.,
110

Ill
participants, measures, and procedures). A total of 38 TPB exercise elicitation studies
were reviewed, and four important findings emerged. First, the most salient behavioral
belief about exercising was that it improves physical and psychological health, and this
included the following eight advantages:
• Feeling healthy, better, or good about self.
• Controls weight and diet.
• Increases physical fitness.
• Improves daily functioning.
• Increases energy.
• Improves mental health.
• Relieves stress and promotes relaxation.
• Improves cardiovascular system.
Second, the most common normative beliefs about exercise were from friends, spouses or
girl/boyfriends, physicians, family members not specified, and parents. Third, the most
frequently reported control beliefs about exercise were:
• Experiencing pain, injury, and illness.
• Lacking time.
• Lacking motivation
• Not having an exercise partner.
Finally, most of the studies did not provide sufficient information to examine the
elicitation study participant characteristics and the elicitation study measures and
procedures.

112
Strengths, limitations, and conclusions. It is important to note that this systematic
review is the first known review to date examining the TPB and exercise elicitation
studies. It was found that only a limited number of studies described the elicitation study
methods (i.e., participants, measures, and procedures). Based on the findings of this
review, it was concluded that researchers should adhere to the TPB guidelines developed
by Ajzen and Fishbein (1980), and conduct elicitation studies before examining the TPB
constructs. In addition, researchers should report more details regarding the elicitation
study methods. When researchers adhere to the TPB guidelines and conduct elicitation
studies, the model is more powerful in predicting exercise intention and behavior
(Symons Downs & Hausenblas, 2002).
Study 2
Main findings. The primary purpose of Study 2 (Chapter 3) was to examine the
frequency of women’s behavioral, normative, and control beliefs for exercising during
their pregnancy and postpartum. These beliefs were elicited from 74 postpartum women
(M age = 31.30 years, SD = 4.37), and the majority of the participants were Caucasian,
married, college graduates, and middle-to-upper class income level. Women’s most
salient beliefs about exercising during their pregnancy were:
• Behavioral beliefs:
o Improves overall mood,
o Increases energy and stamina,
o Assists with staying fit.
o Controls weight.
• Normative beliefs:
o Husband or fiancé,
o Children.
o Other family members,
o Friends.

113
• Control beliefs:
o Physical limitations and restrictions,
o Tiredness and fatigue,
o No time,
o Gaining weight.
Women’s most salient beliefs about exercising during postpartum were:
• Behavioral beliefs:
o Cntrols weight,
o Assists with staying fit.
o Improves overall mood,
o Increases energy and stamina.
• Normative beliefs:
o Husband or fiancé,
o Other family members,
o Friends,
o Children.
• Control beliefs:
o No time.
o Physical limitations and restrictions,
o Tiredness or fatigue,
o Fear of harming self.
Strengths, limitations, and conclusions. It is important to note that Study 2 is one
of the few TPB elicitation studies examining women's beliefs about exercising during
their pregnancy and postpartum. Moreover, this study was designed in accordance with
Ajzen and Fishbein’s (1980) recommendations for elicitation studies. In addition,
consistent with these guidelines, the salient beliefs emerging from this study were used to
develop the beliefs instrument for Study 3. There are limitations of this study that must be
mentioned. First, because of the difficulty with recruiting participants, the majority of the
participants in this study were Caucasian and middle-to-upper class income level.
Therefore, caution is warranted when generalizing these results to non-Caucasian and
lower socioeconomic status populations. Second, the beliefs were elicited with a self-

114
report instrument. There is an inherent limitation in self-report measures due to socially
desirable responses (Sallis & Owen, 1998). Finally, because the participants completed
the questionnaires in a noncontrolled environment, the impact that extraneous factors
(e.g., other people, the media) had on women’s responses cannot be determined.
In conclusion, the findings from Study 2 indicated that women’s beliefs varied
from pregnancy to postpartum, which is consistent with previous researchers’
conclusions that people’s beliefs can vary depending on the time and situation (Ajzen,
1991; Carrón et al., 2003). Thus, it is important for researchers to conduct an elicitation
study with their population of interest to obtain a more accurate assessment of their
beliefs.
Study 3
Main findings. The primary purpose of Study 3 (Chapter 4) was to prospectively
examine the utility of the TPB in predicting pregnant women’s exercise intention and
behavior from their second to their third trimester. Participants were 81 pregnant women
(M age = 29.93 years, SD = 4.52), and the majority of participants were Caucasian,
married, college graduates, and middle-to-upper class income level. For exercise
behavior, it was found that intention and perceived behavioral control explained 43% of
the variance in behavior, and intention was the only significant predictor of exercise
behavior. For intention, attitude, subjective norm, and perceived behavioral control were
found to explain 31 % of the variance in intention. However, only attitude and perceived
behavioral control were significant predictors of intention.
Strengths, limitations, and conclusions. It is important to note that Study 3 is one
of the few prospective studies examining the TPB constructs and exercising during

115
pregnancy. In addition, following the recommendations of Ajzen and Fishbein (1980),
there was correspondence between the samples used in the elicitation (i.e., Study 2) and
the main TBP study (i.e., Study 3) with respect to the participant characteristics (i.e.,
population type, age, race/ethnicity, and socioeconomic status). Moreover, improving on
the previous TPB and exercise literature, scale correspondence was obtained between the
measures of intention and behavior (Coumeya & McAuley, 1994; Culos-Reed et al.,
2001). This is important because scale correspondence improves the predictive utility of
the TPB (Symons Downs & Hausenblas, 2002).
There were also limitations of this study worthy of mention. The following three
limitations were similar to the confines identified in Study 2. First, because the elicitation
sample and main TPB samples should correspond with respect to their participant
characteristics (Ajzen & Fishbein, 1980), the women in Study 3 were also mostly
Caucasian and middle-to-upper class income level. Thus, the study findings have limited
generalizability to non-Caucasian and lower socioeconomic populations. Second, the
TPB constructs were obtained with self-report measures, and there is an inherent bias in
people’s self-report because of socially desirable responses (Sallis & Owen, 1998). Third,
because the participants completed their questionnaires in a nonlaboratory setting, the
impact that extraneous factors (e.g., exercise pamphlets from the doctor’s office,
conversations with other people) had on the women’s responses cannot be determined.
In conclusion, the TPB constructs were found to predict pregnant women’s
exercise intention and behavior from their second to their third trimester. By
understanding women’s beliefs, thoughts, and perceptions about exercising during their
pregnancy, researchers and healthcare professionals can develop and implement effective

116
programs promoting exercise behavior during this time. In addition, the findings from
Study 3 can assist researchers with developing longitudinal studies examining the TPB
constructs and exercise during pregnancy.
Recommendations for Future Research
Despite the success of the TPB in predicting exercise intention and behavior in a
variety of populations, several concerns have emerged in the literature warranting future
research. These limitations include the influence of moderator variables, conceptual
issues, and measurement concerns. While the influence of moderator variables and
conceptual and measurement concerns may impact the TPB constructs, examining then-
impact was beyond the scope of this dissertation. Nonetheless, they are important topics
for future research, and they will be discussed in more detail below.
Moderator Variables
The research examining the influence of moderator variables on exercise intention
and behavior is limited because the TPB does not account for the moderating influence of
demographic variables, personality influences, and past exercise behavior. More
specifically, the TPB does not explain the moderating influence of demographic variables
(e.g., age, sex, socioeconomic status) or personality influences (e.g., obsessive¬
compulsiveness, perfectionism) on exercise behavior. For example, physical activity
involvement varies as a function of age, sex, and socioeconomic status (USDHHS, 2000).
That is, low physical activity is associated with increasing age, lower socioeconomic
status, and it is more prevalent in women compared to men. In addition, while
perfectionism, obsessive-compulsiveness, and trait anxiety have been found in excessive
exercisers, the TPB framework fails to consider the impact of these influences on

117
behavior (Davis, Brewer, & Ratusny, 1993; Hausenblas & Symons Downs, in press).
Thus, future researchers are encouraged to examine the moderating influences of these
variables on the TPB constructs.
In addition, the TPB does not account for the moderating influence of oast
exercise behavior. Some researchers have observed the positive influence of past exercise
behavior on future exercise behavior, and they have argued that it should be included as a
determinant in the TPB (Bentler & Speckart, 1979, 1981; Godin & Shephard, 1990;
Godin, Valois, Shephard, & Deshamais, 1987). For example, Norman and Smith (1995)
investigated the role of past behavior in predicting exercise over a 6-month period, and
they found that it was a stronger predictor of exercise behavior than attitude, perceived
behavioral control, and subjective norm. Thus, these authors concluded that because past
exercise behavior contributed to explaining exercise behavior, its moderating influence
should be examined in future research.
However, Ajzen (1988, 1991) suggested that past behavior has no explanatory
value, and therefore it cannot be considered to be an influential factor similar to the TPB
constructs. Moreover, Ajzen (1991) argued that adding or substituting variables to the
TPB compromises its utility. Thus, future research is warranted that examines the
moderating influence of past behavior to determine its impact on the predictive utility of
the TPB.
Conceptual and Measurement Issues
Considerable attention has been given to the operational definition and
measurement of the TPB constructs. However, conceptual and measurement issues
concerning the way that perceived behavioral control and subjective norm are

118
operationally defined and measured has lead some researchers to more closely examine
these constructs (i.e., Bonzionelos & Bennett, 1999; Biddle, Goudas, & Page, 1994;
Blissmer, 1997; Coumeya & McAuley, 1995; Coumeya, Plotnikoff, Hotz, & Birkett,
2000; Estabrooks & Carrón, 1998).
For example, the influence of perceived behavioral controls on exercise intention
and behavior is equivocal. That is, some researchers have found that perceived behavioral
control predicts intention and behavior (e.g., Bagozzi & Kimmel, 1995; Coumeya &
Friedenreich, 1999; Notani, 1998), and others have found that it is not a significant
predictor of these constructs (e.g., Van Ryn, Lytle, & Kirscht, 1996). One explanation for
these inconsistent findings is that perceived behavioral control has also been
conceptualized as self-efficacv and perceived barriers (Culos-Reed et al., 2001).
Thus, some researchers have compared perceived behavioral control to self-
efficacy and perceived barriers to determine which construct is the strongest predictor of
exercise intention and behavior (e.g., Bonzionelos & Bennett, 1999; Biddle et al., 1994;
Blissmer, 1997; Estabrooks & Carrón, 1998). For example, Estabrooks and Carrón
compared perceived behavioral control (i.e., defined as the ease or difficulty in attending
an exercise class) to self-efficacy (i.e., defined as people’s confidence in scheduling daily
exercise) and perceived barriers (i.e., defined as the confidence in getting to an exercise
class despite barriers such as illness and bad weather) to determine which
conceptualization most strongly predicted 157 elderly participant’s exercise intention and
behavior. The authors found that self-efficacy was a stronger predictor of exercise
intention and behavior than perceived behavioral control, and that perceived barriers did
not predict exercise intention or behavior. Estabrooks and Carrón suggested that their

119
results are consistent with Skinner’s (1996) proposition that scheduling self-efficacy most
closely approximates people’s subjective control, whereas perceived behavioral control
and perceived barriers more closely reflect people’s actual control. Thus, the authors
concluded that perceived behavioral control, self-efficacy, and perceived barriers are
conceptually different constructs.
In addition, Bozionelos and Bennett (1999) examined the predictive utility of the
TPB in explaining college student’s exercise intention and behavior. They found that
perrceived behavioral control (i.e., defined as the participants degree to which they had
control over exercise) and perceived barriers (i.e., defined as the factors that would
prevent them from exercising regularly) contributed independently to predicting exercise
intention and behavior. The authors concluded that perceived behavioral control and
perceived barriers should be conceptualized as separate constructs that explain exercise
intention and behavior.
Moreover, attempting to clarity the ambiguity surrounding the measurement of
perceived behavioral control, Symons Downs and Hausenblas (2002) meta-analytically
examined the associations between perceived behavioral control, self-efficacy, and
perceived barriers with exercise intentions and behavior. They found a significantly
larger self-efficacy-intention association (effect size d = 1.06) compared to perceived
barriers and intention (effect size d = -.17), but not compared to perceived behavioral
control and intention (effect size d = 1.03). In addition, they discovered a larger perceived
behavioral control-behavior association (effect size d = .70) compared to perceived
barriers and behavior (effect size d = .06), but not compared to self-efficacy and behavior
(effect size d = .38). Thus, more research is warranted that examines the conceptual and

120
operational differences among perceived behavioral control, self-efficacy, and perceived
barriers before conclusions can be made regarding which construct is the most strongly
associated with exercise intention and behavior.
Furthermore, it is important to note that recently Ajzen (in press) proposed a
hierarchical model of perceived behavioral control in an attempt to elucidate the
measurement issue surrounding its conceptualization (see Figure 5.1). Ajzen posited
that perceived self-efficacy (e.g., ease or difficulty in performing the behavior) and
perceived controllability (e.g., beliefs about the extent to which performing the behavior
is up to the person) contribute to people’s perceived behavioral control. In short, Ajzen
argued that the constructs of perceived behavioral control, self-efficacy, and
controllability represent a two-level hierarchical model whereby perceived behavioral
control is the superior construct that is comprised of two lower level constructs (i.e., self-
efficacy and controllability). However, future research is needed that examines this two-
Fiaure 5.1. Hierarchical conceptualization of perceived behavioral control. Various
facilitating and obstructing control factors (i.e., Ci though C6) may separately influence
perceived self-efficacy and perceived controllability. However, together, these constructs
comprise the higher-order construct of perceived behavioral control (Ajzen, in press).

121
level model with exercise intention and behavior before any conclusions can be made
regarding its predictive utility.
In regard to subjective norm, some researchers have found that it influences
people’s intention to exercise (e.g., Coumeya & Friedenreich, 1999; Gatch &
Kendzierski, 1990), while others have found that it is less associated with exercise
intention compared to attitude and perceived behavioral control (e.g., Brenes et al., 1998;
Coumeya & Friedenreich, 1997; Coumeya, Bobick, & Schinke, 1999; Godin et al., 1989;
Van Ryn et al., 1996). For example, the findings from Study 3 of this dissertation
indicated that while the model of attitude, subjective norm, and perceived behavioral
control explained 31% of the variance in pregnant women’s intention to exercise from
their second to their third trimester, subjective norm did not provide any unique
contribution in explaining intention.
Culos-Reed et al. (2001) attempted to explain the weak contribution of subjective
norm in the TPB and exercise literature. They suggested that significant others may not
play an important role in exercise intentions for physically active individuals. In addition,
Culos-Reed and her colleagues argued that it is not well understood whether intention is
affected by an individual’s motivation to comply with the belief that others want he or
she to exercise, or whether it is the actual presence of social support and praise associated
with exercising that influences intention.
In support of Culos-Reed and her colleagues (2001) second argument, Coumeya
and McAuley (1995) examined the influence of subjective norm (i.e., defined as the
perceived social pressures that people may or may not feel to exercise) and social support
(i.e., defined as the comfort and assistance that people receive through individual and

122
group contacts) of people's exercise class attendance. They found that social support was
more strongly related with exercise adherence than subjective norm. These authors
suggested that inconsistencies in measuring subjective norm may have let to its poor
association with the other TPB constructs. In addition, Coumeya et al. (2000) found that
in a sample of over 1,500 adults, social support was superior to subjective norm in
predicting exercise intention. These authors concluded that researchers should consider
the influence of social support when aiming to increase people’s exercise behavior.
Furthermore, Symons Downs and Hausenblas (2002) attempted to meta-
analytically examine associations between subjective norm and social support, however,
a small number of effect sizes prevented them from examining any comparisons. Thus,
more research is warranted that examines the conceptual differences between subjective
norm and social support to determine which construct, if any, has the strongest influence
on exercise intention, and ultimately, exercise behavior.
Practical Implications of This Dissertation
Explaining and predicting exercise behavior is an important facet of exercise
promotion and adherence (Carrón et al., 2003). Increasing exercise behavior in pregnant
women can be a challenge due to the unique barriers that limit their exercise behavior
during this time. Thus, the findings from this dissertation may assist healthcare
professionals with designing research studies using the TPB and pregnant populations
that that follow the theory guidelines (Ajzen & Fishbein, 1980). In addition, the findings
from Studies 2 and 3 can assist researchers with developing and implementing effective
exercise interventions and exercise programs. More specifically, because it was found
that women reported different beliefs about exercising during pregnancy compared to

123
postpartum, researchers are encouraged to tailor their interventions and programs to meet
the beliefs and needs of women depending on whether they are in their pregnancy or
postpartum stage. For example, healthcare professionals are encouraged to use methods
during pregnancy that assist women with improving their overall mood (e.g., muscle
relaxing techniques, imagery, and yoga), increasing their energy and stamina (e.g., low
impact aerobics), and decreasing their physical discomfort (e.g., water callisthenics). In
comparison, researchers and healthcare professionals may consider methods during
postpartum that assist women with controlling their weight (e.g., energy expending
activities such as aerobics, running, weight lifting) and diet (e.g., diet education, planning
meals), and help them with improving their time management skills (e.g., planning,
organizing, and preparing skills, implementation intentions).
Conclusion
In conclusion, this dissertation examined the utility of the TPB in explaining
pregnant women's exercise intention and behavior. The findings from the three studies
suggest that the TPB provides researchers with a conceptual framework for
understanding, predicting, and explaining pregnant women’s exercise intention and
behavior. Future researchers are encouraged to guide their studies with the theoretical
recommendations developed by Ajzen and Fishbein’s (1980), and conduct elicitation
studies before examining the predictive utility of the TPB. In addition, researchers are
encouraged to examine the influence of the moderator variables and the conceptual and
methodological concerns addressed in this chapter in an attempt to better understand the
determinants of pregnant women’s exercise intention and behavior.

124
Finally, this dissertation was my first step toward understanding, explaining, and
predicting pregnant women’s exercise intention and behavior. Because there is a need to
promote exercising during pregnancy, and because the research examining exercising
during this time is scant, more research is warranted that examines women’s exercise
behavior from their first trimester through postpartum. Thus, my future research goals
and objectives are to examine exercising during pregnancy and postpartum in an attempt
to better understand the determinants of women’s exercise behavior, and to increase
women’s exercise behavior during pregnancy and postpartum.

APPENDIX A
THEORY OF PLANNED BEHAVIOR AND EXERCISE STUDIES
WITH SPECIAL POPULATIONS

Table A.l
Theory of Planned Behavior and Exercise Studies With Special Populations
Study
Sample Characteristics
Measure of Behavior
Predicting Intention (INT)
Predicting Behavior (BEH)
Bergen
(1996)“’b
N= 115 chronic pain
patients (43% female, M
age = 45.6 years); 78%
RR
Exercise frequency, duration,
and intensity
HMR model of ATT, SN, and PBC
accounted for 49% variance in INT, with
ATT (R2 - .41) and PBC (R2 = .07)
maintaining unique contributions
HMR model of INT and PBC
accounted for 19% variance in BEH,
with INT (P = .43) maintaining its
unique contribution
Brenes, Strube, &
Storandt (1998)b
N = 12 male and 93
female older adults from
YMCA (M age = 68.3
years); 89% RR
Self-report of exercise
HMR model of ATT, SN, and PBC
accounted for 7% variance in INT, with
PBC (R2 = .07) maintaining its unique
contribution
INT did not predict BEH; HMR model
of ATT, SN, and PBC explained 9%
variance in BEH, with PBC (P = .24)
maintaining its unique contribution
Coumeya(1995)b
N = 288 Kerby Center
older adults (63% female,
M age = 71.5 years); 39%
RR
Stage of Readiness
Questionnaire
Path analysis and HMR; model of ATT,
SN, and PBC explained 38% variance in
INT, with ATT (p = .22), PBC (P = .18),
and SN (p = .17) maintaining unique
contributions
Path analysis and HMR; model of INT,
PBC, ATT, and SN explained 63%
variance in BEH, with INT (P = .57),
PBC (P = .16), and ATT (p = .15)
maintaining unique contributions
Coumeya &
Friedenreich (1997)b
N = 110 cancer patients
(63% F; M age = 60.9
years); 77% RR
Leisure-Time Exercise
Questionnaire
HMR model of ATT, SN, and PBC
explained 56% variance in INT, with
ATT (P = .45) maintaining its unique
contribution
HMR model of INT, PBC, and
exercise prediagnosis explained 63%
variance in BEH (exercise during
treatment), with all three (INT P = .16,
PBC p = .26, exercise prediagnosis p =
.45) maintaining unique contributions
Coumeya &
Friedenreich (1999)b
N = 164 female breast
cancer patients (M age =
53.0 years); 80% RR
Leisure-Time Exercise
Questionnaire
HMR model of ATT, SN, and PBC
explained 23% variance in INT, with
ATT (P = .29) and SN (p = .30)
maintaining unique contributions
HMR model of INT and PBC
explained 14% variance in BEH
(exercise during treatment) with INT
(p = .26) and PBC (P = .22)
maintaining unique contributions

Table A.1 Continued
Study
Sample Characteristics
Measure of Behavior
Predicting Intention (INT)
Predicting Behavior (BEH)
Coumeya,
Friedenreich,
Arthur, & Bobick
(1999)
N = 38 male and 27
female colorectal cancer
patients (M age = 60.8
years); 53% RR
Leisure-Time Exercise
Questionnaire
HMR model of PBC, ATT, and SN
explained 23% variance in INT, with
ATT (P = .43) maintaining its unique
contribution
INT explained 26% variance in BEH
(post-surgical exercise); PBC
explained an additional 4% of the
variance with INT (P = .45) and PBC
(P = .21) maintaining unique
contributions; Exercise prediagnosis
explained an additional 8% variance
with INT (P = .33) maintaining its
unique contribution
Coumeya, Keats, &
Turner (2000)
N = 37 cancer patients
(40% female, M age =
47.8 years); 81.3% RR
Cycle ergometer and
exercise log during treatment
HRA of PBC, ATT, and SN explained
69% variance in INT, with ATT (P = .51)
and PBC (P = .39) maintaining unique
contributions; the addition of exercise
prediagnosis explained an additional 2%
of the variance in ATT, with ATT (P =
.50), PBC (P = .33), and exercise
prediagnosis (P = .14) maintaining
unique contributions
INT explained 31% variance in BEH;
PBC explained an additional 6% of the
variance with INT (P = .32) and PBC
(P = .33) maintaining unique
contributions; addition of exercise
prediagnosis added 8% and was only
variable to make a significant
contribution in equation (P = .33)
Coumeya, Nigg, &
Estabrooks (1998)
N= 131 Kerby Center
older adults (sex = N.A.,
M age = 71.5 years) 94%
RR
Leisure-Time Exercise
Questionnaire
Path analysis and HRA of SN, ATT, and
PBC explained 37% variance in INT,
with SN (p = .24), ATT (P = .23), and
PBC (P = .29) maintaining unique
contributions
Path analysis; INT mediated
association between SN, ATT, and
PBC and exercise stage (R2 = .29),
with INT maintaining its unique
contribution (p = .55)
Daltroy & Godin
(1989b )b
N = 264 male and female
cardiovascular disease
patients and spouses (132
pairs, M age = 53.5 years);
82% RR
Exercise program attendance
Stepwise forward regression; spouse-
reported approval, patient-perceived
approval, and agreement of approval
explained 15% variance in INT with
patient-perceived approval maintaining
its unique contribution (P = .20)
Stepwise forward regression; spouse-
reported approval, patient-perceived
approval, and agreement of approval
explained 26% variance in exercise
class attendance, with spouse-reported
approval maintaining its unique
contribution (P =. 17)

Table A.l Continued
Study Sample Characteristics Measure of Behavior Predicting Intention (INT)
Estabrooks &
Carrón (1998)
N = 157 elderly adults
(74.0% female; M age =
68 years)
Exercise class attendar
Godin, Colantonio,
N = 62 males with a
Self-report of physical
Davis, Shephard, &
Simard (1986)
disability (M age = 30.7
years)
activity habit
Godin, Deshamais,
N = 349 male and female
Self-report of physical
Valois, Lepage,
Jobin, & Bradet
(1994)b
community members (M
age = 38.1 years), 162
male and female cardiac
patients (M age = 56.6
years), and 139 pregnant
women (M age = 27.3
years)
activity
Godin, Valois,
N = 137 male and 24
Self-report of physical
Jobin, & Ross
(1991)
female cardiac patients (M
age = 52.8 years); 67%
RR
activity habit
Godin, Valois, &
N = 136 females currently
Self-report of physical
Lepage (1993)
Study 2
pregnant (age range = 18-
40 years)
activity
Path analysis rotated order of variables;
PBC (R2 = .03) and self-efficacy (R2 =
.04) explained INT
HRA of ATT, SN, and habit explained
7% variance in INT, with habit
maintaining its unique contribution (P =
.30)
Correlations, no predictions
HRA of ATT, SN, and perceived barriers
explained 24% variance in INT, with
ATT (P = .32) and perceived barriers (P
= -.29) maintaining unique contributions
LISREL analyses; ATT, PBC, and habit
influenced INT
Godin, Vezina, &
Leclerc (1989)
N = 98 females currently Self-report of leisure-time
pregnant (M age = 28.6 physical activity
years); 99% RR
HRA model of ATT, perceived barriers,
and habit explained 51% variance in INT,
with perceived barriers (R2 = .35), ATT
(R2 = .12), and habit (R2 = .04)
explaining INT
Helm
(1987)*-b
N = 89 male and 165
female retired adults (M
age = N.A); 41% RR
Self-report of exercise (e.g., HRA of ATT and SN explained 57%
tonercise) variance in INT, with ATT (p = .74) and
SN (P = .14) maintaining unique
contributions
Predicting Behavior (BEH)
Path analysis rotated order of
variables; INT (R2 = .37) and self-
efficacy (R2 = .03) explained BEH
HRA of ATT, SN, and NT explained
35% variance in BEH, with INT (P =
.31) and ATT (P = .26) maintaining
unique contributions
Correlations, no predictions
No predictions
LISREL analyses; INT influenced
BEH
No predictions
HRA of ATT and SN explained 57%
variance in INT, with ATT
maintaining its unique contribution (P
= .74)

Table A.l Continued
Study
Sample Characteristics
Measure of Behavior
Predicting Intention (INT)
Predicting Behavior (BEH)
Michels & Kugler
(1998)b
N = 394 older adults (50%
female; age range = 65-70
years)
self-report of physical
activity and exercise habit
HRA of ATT, SN, PBC, and habit
explained 47% variance in INT, with all
variables maintaining unique
contributions (P = N.A.)
HRA of INT, PBC. and habit
explained 11% variance in BEH with
INT maintaining its unique
contribution (P = N.A.)
Miller, Wikoff,
McMahon, Garrett,
& Ringel (1984)
N = 87 male and 25
female cardiac
rehabilitation patients (M
age = 56.0 years); 79%
RR
Miller Attitude Scale for
physical activity
HRA of ATT and perception of beliefs of
others explained 25% variance in INT,
with perception of beliefs (P = .39) and
ATT (P = .23) maintaining unique
contributions
HRA of ATT and perceived adherence
explained 31% variance in BEH, with
ATT (P = .48) and perceived
adherence (P = .22) maintaining
unique contributions
Schlapman (1994)“’b
N= 135 male and 296
female mall walking older
adults (M age = 62.0
years); 35% RR
Self-report of walking
Forward selection regression; model of
ATT, health status, gender, and age
explained 13% variance in INT, with
ATT (P = .11) maintaining its unique
contribution
No predictions
Sellberg
(1995)*
N = 111 elderly adults
(70% female. M age =
80.0 years); 51% RR
Self-report of physical
activity
Correlations, no predictions
Correlations, no predictions
Note, "thesis/dissertation; bconducted an elicitation study; N = number; M = mean; N.A. = not available; RR = response rate; ATT
attitude, SN = subjective norm, PBC = perceived behavioral control; HRA = hierarchical regression analyses.

APPENDIX B
PERSONAL HISTORY QUESTIONNAIRE
1. Age
2. Your height ft in
3. Your current weight lb
4. Your weight before getting pregnant lb
5. Date of birth of most recent child month day year
6. Marital status: single married divorced widow common law
7. Highest level of education:
< high school high school college trade school grad/professional other
8. Family income: <$10,000 $10-20,000 $20-40,000 $40-100,000 >$100,000
9. Ethnic background:
African American/Black American Indian Asian Caucasian Hispanic other
10. Current occupation: frill-time part-time unemployed homemaker self-employed other
130

APPENDIX C
LEISURE-TIME EXERCISE QUESTIONNAIRE
Instructions. This is a scale that measures your leisure-time exercise (i.e., exercise that
was done during your free time). Considering a typical week, please indicate how often
(on average) you have engaged in strenuous, moderate, and mild exercise more than 15
minutes during your free time before pregnancy, DURING your pregnancy, and
CURRENTLY.
Currently Before During
Pregnancy Pregnancy
Strenuous exercise: heart
beats rapidly (e.g., running,
basketball, hockey, squash,
judo, roller skating, vigorous
swimming, long distance
bicycling, aerobic dance
classes, heavy weight training)
How many times per typical
week do you perform
strenuous exercise for 15
minutes or longer?
Moderate exercise: not
exhausting, light sweating
(e.g., fast walking, baseball,
tennis, easy bicycling,
volleyball, badminton, easy
swimming, popular folk
dancing)
How many times per typical
week do you perform
moderate exercise for 15
minutes or longer?
Mild exercise: minimal effort,
no sweating (e.g., easy
walking, yoga, archery,
fishing, bowling, lawn
bowling, shuffleboard,
horseshoes, golf)
How many times per typical
week do you perform mild
exercise for 15 minutes or
longer?
131

APPENDIX D
ELICITATION BELIEFS QUESTIONNAIRE
Part A Instructions. The following questions relate to your exercise behavior during
your pregnancy. List as many that apply to you in the space provided below.
1.List the main advantages of exercising during your pregnancy.
2.List the main disadvantages of exercising during your pregnancy.
3.List the main factors that prevented you from exercising during your pregnancy.
132

133
4. List the main factors that helped you to exercise during your pregnancy.
5. List the individuals or groups who were most important to you when you thought
about exercising during your pregnancy.
Part B Instructions. The following questions relate to your current exercise behavior
following birth. List as many that apply to you in the space provided below.
1. List the main advantages of exercising following the birth of your child.

134
2.List the main disadvantages of exercising during your pregnancy.
3.List the main factors that prevented you from exercising following the birth of your
child.
4.List the main factors that helped you to exercise following the birth of your child.
5.List the individuals or groups who were most important to you when you thought
about exercising following the birth of your child.

APPENDIX E
IRB APPROVAL FORM FOR STUDY 2
UNIVERSITY OF
FLORIDA
Institutional Review Board
98A Psychology Bldg
PO Box 11225
Gainesville, FL 32611-225'
Phone: (352) 392-043:
Fax:(352)392-923-
E-mail: irb2@ufl.edi
http://web.ortge.ufl.edu/irb/irbO:
DATE:
24- Aug-2001
TO:
Dr. Heather Hausenblas
Box 118205
Campus
FROM:
C. Michael Levy, Chair /a
University of Florida ' u
Institutional Review Board
SUBJECT:
Reapproval of Protocol # 2000 - 673
TITLE:
Examination of the theory of planned behavior in predicting and explaining exercise
behavior in women during pregnancy and postpartum.
(Examination of exercise beliefs during pregnancy and postpartum)
FUNDING:
Unfunded
Your request to continue your research protocol involving human participants has been reapproved.
Participants are not placed at more than minima] risk by the research. You are reminded that any changes,
including the need to increase the number of participants authorized, must be approved by resubmission of
the protocol to the Board.
Reapproval of this protocol extends for one year from the date of the review, the maximum duration
permitted by the Office for Human Research Protection. If this project will not be completed by 23-Aug-
2002, please telephone our office (392-0433) at least six weeks in advance so we can advise you how to
reapply.
It is important that you keep your Department Chair informed about the status of this research project.
Also, if your project is funded, you should send a request to extend your grant along with a copy of this
project renewal notification to DSR, Awards Administration, P.O. Box 115500.
135

APPENDIX F
CONSENT FORM FOR STUDY 2
To: Volunteers for the Exercise Study
From: Dr. Heather Hausenblas
RE: Informed Consent
The purpose of this statement is to summarize the study I am conducting, explain what I
am asking you to do, and assure you that all participants in the study will be assigned a
coded number; individuals will not be identified by name but by the last four digits of
their SSN; all data will be treated in strict confidence and will be locked in a filing
cabinet in the exercise psychology laboratory located at Room 145 Florida Gymnasium.
I am interested in examining your exercise beliefs and behaviors during pregnancy and
postpartum. If you agree to participate you will be asked to complete a series of
questionnaires assessing your beliefs and behaviors regarding exercise during pregnancy
and postpartum. Four months later you will be contacted via telephone or mail and asked
to indicate your exercise behavior. Upon completion of the questionnaires you will be
debriefed as to the study’s purpose and any questions will be answered. I want to
emphasize that your questionnaire responses will remain confidential. In the presentation
of results, I will be focusing on group data. Your participation in this study is voluntary,
and you are free to refuse to answer any questions or stop answering questions at any
point. Your identity will be confidential to the extent provided by law and you may
withdrawal from the study without penalty. The benefits associated with the study are a
better understanding of your exercise attitudes and behaviors. There are no anticipated
risks for participating in the study.
It is hoped that you will agree to take part in this study. Without the cooperation of
volunteers such as yourself, projects of this type would not be possible. Please ask any
questions you may have at this time, and if you have any additional questions or concerns
during the course of the study, please contact Dr. Hausenblas (392-0584 ext. 292).
Questions or concerns about research participants’ rights may be directed to the UFIRB
Office, Box 112250, University of Florida, Gainesville, FL 32611-2250 (392-0433).
I have read the procedure above. I voluntarily agree to participate in the procedure, and I
have received a copy of this description.
Participant’s signature:
Date:
Principal Investigator’s Signature:
136

APPENDIX G
PERSONAL HISTORY QUESTIONNAIRE
Current address:
1. Age
2. Your height ft in
3. Your current weight lb
4. Approximately on what date did you conceive? month day year
5. When is your due date? month day year
6. Date of birth of most recent child _____ month day year
7. How many children do you have? Their ages:
8. Marital status: single married divorced widow common law
9. Highest level of education:
< high school high school college trade school grad/professional other
10. Family income: <$10,000 $10-20,000 $20-40,000 $40-100,000 >$100,000
11. Ethnic background:
African American/Black American Indian Asian Caucasian Hispanic other
12. Current occupation:
fUll-time part-time unemployed homemaker self-employed other
137

APPENDIX H
BEHAVIORAL BELIEFS ITEMS
Instructions. The following questions pertain to your second trimester of pregnancy. Regular
exercise is defined as engaging in moderate to strenuous physical activity at least 3 times a week
for a minimum of 15 minutes a session. Please use this definition of exercise when answering the
following questions.
1
2
3
4
5
6
7
extremely
quite
slightly
slightly
quite
extremely
unlikely
unlikely
unlikely
likely
likely
likely
Exercising regularly during my 2nd trimester of pregnancy does/will...
1. help to improve my overall mood.
2. help to increase my energy/stamina.
3. help to assist in my labor/delivery.
4. help to keep me fit.
5. help to keep my weight in check.
6. cause physical discomfort.
7. make me feel tired/fatigued.
8. be difficult due to time limits in my schedule.
9. provide stress relief.
2 3 4
2 3 4
2 3 4
2 3 4
2 3 4
2 3 4
2 3 4
2 3 4
2 3 4
5
5
5
5
5
5
5
5
5
6 7
6 7
6 7
6 7
6 7
6 7
6 7
6 7
6 7
138

APPENDIX I
NORMATIVE BELIEFS ITEMS
Instructions. The following questions pertain to your second trimester of pregnancy. Regular
exercise is defined as engaging in moderate to strenuous physical activity at least 3 times a week
for a minimum of 15 minutes a session. Please use this definition of exercise when answering the
following questions.
1
2
3
4
5
6
7
extremely
quite
slightly
slightly
quite
extremely
unlikely
unlikely
unlikely
likely
likely
likely
How strongly does/will each of the following persons approve of you exercising regularly during your 2nd
trimester of pregnancy:
1. husband/fiancé/partner.
2. friends.
3. children.
4. family members other than husband/children.
5. doctors.
6. nurses.
139

APPENDIX J
CONTROL BELIEFS ITEMS
Instructions. The following questions pertain to your second trimester of pregnancy Regular
exercise is defined as engaging in moderate to strenuous physical activity at least 3 times a week
for a minimum of 15 minutes a session. Please use this definition of exercise when answering the
following questions.
1 2 3
extremely quite slightly
unlikely unlikely unlikely
4
5
slightly
likely
6
quite
likely
7
extremely
likely
How difficult is/would it be for you to exercise regularly during your 2nd trimester of pregnancy given
the following circumstances:
1. having other children to care for.
1
2
3 4
5
6
7
2. gaining weight.
1
2
3 4
5
6
7
3. experiencing bad weather.
1
2
3 4
5
6
7
4. having physical limitations/restrictions.
1
2
3 4
5
6
7
5. having no time to exercise.
1
2
3 4
5
6
7
6. having no motivation to exercise.
1
2
3 4
5
6
7
7. experiencing fatigue/tiredness.
1
2
3 4
5
6
7
8. having a fear of harming the unborn baby.
i
2
3 4
5
6
7
9. having a fear of harming yourself.
1
2
3 4
5
6
7
140

APPENDIX K
ATTITUDE ITEMS
Instructions. The following questions pertain to your 2nd trimester of pregnancy. Choose your
answer by circling the number that most appropriately answers the statement. Exercise is defined
as engaging in moderate to strenuous physical activity at least 3 times a week for a minimum of
15 minutes a session. Please use this definition of exercise when answering the following
questions.
1. Exercising during my 2nd trimester of pregnancy is/will be:
useless
1 2
3
4
5
useful
6 7
2.
Exercising during my 2nd trimester of pregnancy is/will be:
harmful
1 2
3
4
5
beneficial
6 7
3.
Exercising during my 2nd trimester of pregnancy is/will be:
bad
1 2
3
4
5
good
6 7
4.
Exercising during my 2nd trimester of pregnancy is/will be:
foolish
1 2
3
4
5
wise
6 7
5.
Exercising during my 2nd trimester of pregnancy is/will be:
unpleasant
1 2
3
4
5
pleasant
6 7
6.
Exercising during my 2nd trimester of pregnancy is/will be:
unenjoyable
1 2
3
4
5
enjoyable
6 7
7.
Exercising during my 2nd trimester of pregnancy is/will be:
boring
1 2
3
4
5
interesting
6 7
141

APPENDIX L
SUBJECTIVE NORM ITEM
Instructions. The following question pertains to your 2nd trimester of pregnancy. Choose your
answer by circling the number that most appropriately answers the statement. Exercise is defined
as engaging in moderate to strenuous physical activity at least 3 times a week for a minimum of
15 minutes a session. Please use this definition of exercise when answering the following
question.
1. People who are important to me think that 1 should
strongly disagree
strongly agree
exercise during my second trimester of pregnancy:
1 2 3
4
5 6 7
142

APPENDIX M
PERCEIVED BEHAVIORAL CONTROL ITEMS
Instructions. The following questions pertain to your 2nd trimester of pregnancy. Choose your
answer by circling the number that most appropriately answers the statement. Exercise is defined
as engaging in moderate to strenuous physical activity at least 3 times a week for a minimum of
15 minutes a session. Please use this definition of exercise when answering the following
questions.
1. For me to exercising during my 2nd trimester of pregnancy
is/will be:
extremely difficult extremely easy
1 2 3 4 5 6 7
2. If I wanted to, I could easily exercise during my 2nd trimester
of pregnancy:
strongly disagree strongly agree
1 2 3 4 5 6 7
3. How much control do you have over exercising during your
2nd trimester of pregnancy:
very little control complete control
1 2 3 4 5 6 7
143

APPENDIX N
INTENTION ITEM
Instructions. The following question pertains to your 2nd trimester of pregnancy. Choose your
answer by circling the number that most appropriately answers the statement. Exercise is defined
as engaging in moderate to strenuous physical activity at least 3 times a week for a minimum of
15 minutes a session. Please use this definition of exercise when answering the following
question.
1. It is my intention to exercise days a
week during my second trimester of pregnancy. 1 2 3 4 5 6 7 days/week
144

APPENDIX O
EXERCISE BEHAVIOR ITEM
Instructions. The following question pertains to your 2”1 trimester of pregnancy. Choose your
answer by circling the number that most appropriately answers the statement. Exercise is defined
as engaging in moderate to strenuous physical activity at least 3 times a week for a minimum of
15 minutes a session. Please use this definition of exercise when answering the following
question.
1. I exercised days a week
during my second trimester of pregnancy. 1
2
3
4
5
6
7 days/week
145

APPENDIX P
IRB APPROVAL FORM FOR STUDY 3
Institutional Review Board
DATE: 31-May-2001
98A Psychology Bldg.
PO Box 112250
Gainesville. FL 32611-2250
Phone: (352) 392-0433
Fax: (352) 392-9234
E-mail: irb2@ufl.edu
http://web.ortge.ufl.edu/irb/irb02
TO:
Dr. Heather A. Hausenblas
Box 118205 J
CampUS
FROM:
C. Michael Levy, Chair (/» "
University of Florida
Institutional Review Board
SUBJECT:
Approval of Protocol # 2001 -417
TITLE:
Examination of the theory of planned behavior in predicting and explaining exercise
behavior in women during pregnancy and postpartum
FUNDING;
Unfunded
I am pleased to advise you that the University of Florida Institutional Review Board has recommended
approval of this protocol. Based on its review, the UFIRB determined that this research presents no more
than minimal risk to participants. Given your protocol, it is essential that you obtain signed documentation
of informed consent from each participant Enclosed is the dated, IRB-approved informed consent to be
used when recruiting participants for the research.
If you wish to make any changes to this protocol, including the need to increase the number of participants
authorized, you must disclose your plans before you implement them so that the Board can assess their
impact on your protocol. In addition, you must report to the Board any unexpected complications that
affect your participants.
If you have not completed this protocol by 30-May-2002, please telephone our office (392-0433), and we
will discuss the renewal process with you.
146

APPENDIX Q
STUDY 3 EXPLANATION
SiN UNIVERSITY OF
Pflorida
100 Florida Gym
PO Box 118205
Gainesvlle. FL 32611-8205
(352) 392-05 84
www .hhp.ufl.edu/ess
We are researchers at the University of Florida who are interested in learning more about your
exercise habits during your pregnancy. With the staff of The Women's Center, we are able to ask
women like yourself if you would be willing to take part in a brief questionnaire study conducted
through the mail regarding how you feel about exercising during your pregnancy. Unfortunately,
there is not a lot of research available regarding pregnant women's exercise thoughts and habits.
This study mil provide us mth a great deal of insight.
Participation in this study is voluntary and anonymous. Your participation will only take a few
minutes of your time but it will provide us with a great deal of valuable information. If you are
willing to participate in the study, we will be able to provide you with information regarding safe
exercise habits during your pregnancy and postpartum.
If you have any questions or would like information regarding exercise during your
pregnancy please contact us at: 392-0580 x 1298.
We wish you all the best during your pregnancy!
Dr. Heather Hausenblas
Danielle Symons Downs, M.A.
147

APPENDIX R
CONSENT FORM
To: Volunteers for the Exercise Study
From: Dr. Hausenblas and Danielle Symons Downs
RE: Informed Consent
The purpose of this statement is to summarize the study we are conducting, explain what
we are asking you to do, and assure you that all participants in the study will be assigned
a coded number; individuals will not be identified by name but by the last four digits of
their SSN; all data will be treated in strict confidence and will be locked in a filing
cabinet in the exercise psychology laboratory located at Room 145 Florida Gymnasium.
We are interested in examining your exercise beliefs. We want to emphasize that your
questionnaire responses will remain confidential. In the presentation of results, we will be
focusing on group data. Your participation in this study is voluntary, and you are free to
refuse to answer any questions or to stop answering questions at any point. The benefits
associated with the study are a better understanding of your exercise attitudes and
behaviors. There are no anticipated risks for participating in the study.
It is hoped that you will agree to take part in this study. Without the cooperation of
volunteers such as yourself, projects of this type would not be possible. Please ask any
questions you may have at this time, and if you have any additional questions or concerns
during the course of the study, please contact Dr. Hausenblas (392-0584 ext. 292).
Questions or concerns about research participants’ rights may be directed to the UFIRB
Office, Box 112250, University of Florida, Gainesville, FL 32611-2250 (392-0433).
I have read the procedure above. I voluntarily agree to participate in the procedure, and I
have received a copy of this description.
Participant’s signature:
Date:
Principal Investigator’s Signature:
148

APPENDIX S
SECOND TRIMESTER COVER LETTER
100 Florida Gym
PO Box 118205
Gainesville, FL 32611-8205
(352) 392-0584
www .hhp. ufl. ed u/ess
Department of Exercise and Sport Sciences
College of Heath and Human Performance
Because we are studying exercise habits during your entire pregnancy we w ou Id
appreciate if you would take a few m inutes to com píete the enclosed questionnaire
regarding your exercise habits during your 2nd trim ester. Once you have com pie ted
the questionnaire please place it in the self-addressed stam ped envelope to return to
the E xercise Psychology Laboratory. P articipation in this study is voluntary and
anonym ous. Your participation w ill only take a few m in u tes of your tim e but it w ill
provide us w ith a great deal of valuable inform ation. If you participate in this study we
will send you inform ation regarding safe exercise habits during your pregnancy and
postpartum .
U nfortunately, there is n ot a lot of research a vailable regardin g pregnant worn en's
exercis e th ou ghts and h a bits. This stu d y w ill provide us w ith a great deal of insight.
If you have any questions or w ould like inform ation regarding exercise during your
pregnancy please contactus at 392-0580 x 1 298.
W e wish you all th e bestduring yourpregnancy!
Dr. HeatherH ausenblas
Dan ie lie Symons Downs, M . A .
149

APPENDIX T
POSTCARD REMINDER
(front)
Dear Exercise Participant,
Approximately two weeks ago you received a package containing a
questionnaire for a study I am conducting on exercise attitudes and behaviors
during pregnancy. I would greatly appreciate it if you could take a few
minutes to complete the questionnaire and return it to me in the self-
addressed stamped envelope Without the cooperation of volunteers such as
you, this project would not be possible. If you have any questions or
concerns during the course of the study, please contact me at: (252) 392-
0584 ext. 1298.
Thank you,
Dr. Heather Hausenblas
University of Florida
150

APPENDIX U
THIRD TRIMESTER COVER LETTER
n UNIVERSITY OF
Florida
100 Florida Gym
PO Box 118205
Gainesville. FL 32611-8205
(352) 392-0584
www.hhp.ufl.edu/ess
Thank you for completing the questionnaire that we sent you approximately 8 weeks
ago regarding your exercise habits during your second trimester. W e greatly
appreciate your time and effort in helping us understanding women’s exercise
behaviors during this exciting time.
B ecause we are studying exercise habits during your entire pregnancy we would
appreciate if you would take a few minutes to complete the enclosed questionnaire
regard in g your ex ere is e h a bits d u rin g y ou r 3rd trim ester. 0 nee you have com pie ted
the questionnaire please place it in the self-addressed stamped envelope to return to
the Exercise Psychology Laboratory. Participation in this study is voluntary and
anonymous. Your participation will only take a few m inutes of your tim e but it will
provide us with a great deal of valuable information. W e have enclosed some
inform ation regarding safe exercise habits during your pregnancy and postpartum.
W e hope that you find the information interesting and informative.
U nfortunately, there is not a lot of research available regarding pregnant worn en's
exercise thoughts and habits. This study will provide us with a great deal of insight.
If you have any questions or would like information regarding exercise during your
pregnancy please contact us at 392-0580 x 1298.
W e wish you all the best during your pregnancy and delivery!
Dr. HeatherHausenblas
Danielle Symons Downs, M A.
151

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BIOGRAPHICAL SKETCH
I, Danielle Symons Downs, was bom on July 20, 1973, in Buffalo, New York. I
received my Bachelor of Arts degree in psychology and sociology from Baldwin-Wallace
College, in Berea, Ohio in the spring of 1995. After graduating, I was accepted to the
State University of New York, College at Brockport where I received a Master of Arts
degree in applied behavior change psychology in the spring of 1998. Joyfully, I was
accepted in the fall of that year to the graduate program in sport and exercise science at
the University of Florida, where I have been pursuing my Doctor of Philosophy degree,
concentrating in exercise and sport psychology. In the summer of2002,1 will be
graduating from the University of Florida, and my husband, Jon Downs, and I will be
moving to State College, Pennsylvania. I will begin a tenure-track appointment
specializing in the sociology of physical activity in the Department of Kinesiology at The
Pennsylvania State University, and Jon will be working as a school counselor and
finishing his Ph.D. in counselor education from the University of Florida. While we are
sad to leave Gainesville, we are also excited to move closer to our families, and begin a
new part of our lives in State College. In the words of my husband, “We are orange and
blue through and through, but blue and white we sure can do!”
165

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
/utykJtc.y
Heather A. Hausenblas, Chair
Assistant Professor of Exercise and Sport Sciences
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
ercise and Sport Sciences
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
Peter R. Giacobbi, Jr.
Assistant Professor of Exercise and Sport Sciences
I certify that 1 have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
0
ckav^A
Jam :s A. Shepperd
Associate Professor of Psychology
This dissertation was submitted to the Graduate Faculty of the College of Health
and Human Performance and to the Graduate School apd was accepted as partial
fulfillment of the requirements for the degree of gpct(ij/of^>hilosippl]
August, 2002 _ ,
Deán, Colli of Health and Human Performance
Dean, Graduate School

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