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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Thesis (Ph. D.)--University of Florida, 2002.
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Includes bibliographical references (leaves 152-164).
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by Danielle Symons Downs.
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Printout.
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Vita.

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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.




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