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An examination of the utility of the health belief model for predicting adult participation in aerobic exercise

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An examination of the utility of the health belief model for predicting adult participation in aerobic exercise
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Gage, Larry, 1953-
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Behavior modeling ( jstor )
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Motivation ( jstor )
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Thesis (Ph. D.)--University of Florida, 1990.
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Includes bibliographical references (leaves 171-180).
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Typescript.
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Vita.
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by Larry Gage.

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AN EXAMINATION OF THE UTILITY OF
THE HEALTH BELIEF MODEL FOR PREDICTING
ADULT PARTICIPATION IN AEROBIC EXERCISE













By

LARRY GAGE


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


1990


UNI'JRSITY OF tLO"A.IA LI~l..n4










ACKNOWLEDGMENTS


I have been fortunate to have a committee of

scientist-practitioners who have had the time whenever I

have asked for it, and who each by their example have

inspired me. A piece of each now resides within me as I

continue to develop my own identity as a counseling

psychologist. Anchoring this diverse and talented group

has been Dr. Harry Grater, there to support and to

challenge. His guidance has made this project feasible,

with encouragement that has helped to motivate me. His

willingness to step outside his usual purview enabled me

to mount this project; I hope the experience has been

mutually edifying.

Especial thanks go as well to Dr. Jim Archer, whose

mentoring has been invaluable over many spheres, not just

this project. His role as cochair has included prodigious

energy invested in early drafts and discussions of this

work. It was his critical eye that provided for such

meaningful results as occur with this study.

Dr. Peggy Fong provided much of the early impetus and

knowledge that resulted in my choice of this topic, and

her input has been very helpful. In a similar way Dr. Shae

Kosch has provided much expert guidance in my development

as a psychologist in the health area; her matter-of-fact

imparting of substantive guidance and knowledge has been







much appreciated. A special debt of gratitude is owed Dr.

Barbara Probert, whose continuous unconditional positive

regard from my first association with her forward has

helped me to heal past hurts and to believe in myself. Her

support has been a spring whose waters I have gratefully

imbibed, even at a distance.

I must acknowledge the help of Dr. Henry Wang, who

helped advise about the best course to chart in wrestling

with abstract data and the arcane structure of SAS. Also

aiding in the process was Toby Gelman, whose support and

guidance helped me sidestep some deep electronic chasms.

Trenton State College, through the offices of the

Psychological Counseling Services and of Institutional

Computing, has provided critical resources that allowed

the execution of this project.

Finally, I owe deepest thanks to those whose support

has enabled me to approach this threshold. My parents, Joe

and Phyllis Gage, have provided support and encouragement

throughout my life. My wife, Karen Forbes, has supplied

substantial professional advice and consultation, over and

above the many kinds of support I have also gotten from

her as my life partner. She has been an in-house example

of how to set the standard as a new professional, and an

inspiration to me.


iii














TABLE OF CONTENTS


ACKNOWLEDGMENTS ..........................................ii

LIST OF TABLES..........................................vi

ABSTRACT .............................................. viii

CHAPTER

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

The Costs of Illness and Solutions Offered
by Counseling Psychology......................1
Attrition From Exercise Programs.................6
The Health Belief Model and Its Utility
In Exercise Adoption Research................11
The Role of an Attitude/Beliefs Study
in Exercise Adoption Research................15

2 REVIEW OF THE LITERATURE..........................25

The Benefits of Exercise........................25
Exercise Adoption.. ............................37
Factors in Adherence to Exercise................41
The Health Belief Model and Its Role
in Behavioral Research.......................51
Applying the Health Belief Model to
the Exercise Adoption Problem................67
Hypotheses..... .......................... .......86

3 METHOD.................................................. 90

Subjects...................................... .... 90
Instrumentation............................... 93
Procedure.... ............... ...................100

4 RESULTS............... ..................... ...... 104

Evaluation of the Personal Beliefs
Questionnaire.................................. 104
A Test of the Predictive Validity of the
Personal Beliefs Questionnaire.............. 111













5 DISCUSSION.......................................125

The Comparative Efficacy of the Personal
Beliefs Questionnaire........................125
Assessing the Criterion Validity of
The Personal Beliefs Questionnaire.......... 127
Limitations Affecting the Results of This
Study.................... ......... ...........134
Implications for Future Research on the
Precursors to Aerobic Exercise Behavior..... 138
Conclusion.....................................143

APPENDICES

A CONTACT LETTER FOR QUESTIONNAIRE..................146
B REPLY-CONSENT FORM................................147
C PERSONAL BELIEFS QUESTIONNAIRE....................148
D SECOND ADMINISTRATION OF QUESTIONNAIRE............156
E LIST OF ORIGINAL ITEMS AND ASSIGNED CODES.........165

REFERENCES ......... ....................................171

BIOGRAPHICAL SKETCH....................................181












LIST OF TABLES


TABLE PAGE

1 Summary of Demographic Descriptors For
All Respondents to Questionnaire One.........92

2 Coefficients Alpha for Initial Groupings
of Questionnaire Items......................105

3 Questionnaire Items Screened Due to Poor
Relative Association With Subscale..........106

4 Questionnaire Subscale Test-Retest
Correlation Coefficients....................107

5 Coefficients Alpha for Final Groupings
of Questionnaire Items......................108

6 Questionnaire Subscale Test-Retest
Correlation Coefficients for Final Item
Groupings ....................................109

7 Subscale Correlation Matrix for Final
Item Groupings..............................110

8 Summary of Factor Analysis Results...........111

9 Distribution of Subjects in Exercise
Adoption Categories.........................112

10 Individual Items Correlating Most Highly
With Adoption Stage Criterion............... 113

11 Sources of Variance in Exercise Adoption
Categories..................................114

12 Sources of Variance From Health Belief
Model Belief Subscales in Exercise
Adoption Categories.........................115

13 Sources of Variance in Exercise
Behavior Categories......................... 116









TABLE


14 Sources of Variance From Health Belief
Model Belief Subscales in Exercise
Behavior Categories......................... 117

15 Sources of Variance From Health Belief
Model Belief Subscales in Antipodal
Exercise Behavior Categories................118

16 Change in Total R-square For Criterion
Variables From First to Second
Administrations Using Independent Belief
Variables Obtained in First Administration..119

17 Number of Observations and Percents
Classified Into Exercise Adoption
Categories.................................121

18 Number of Observations and Percents
Classified Into Exercise Behavior
Categories................................... 122

19 Number of Observations and Percents
Classified Into Antipodal Exercise
Behavior Categories.........................123

20 Number of Observations and Percents
Classified Into Self-Reported Change in
Exercise Behavior Categories................124


vii


PAGE









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

AN EXAMINATION OF THE UTILITY OF
THE HEALTH BELIEF MODEL FOR PREDICTING
ADULT PARTICIPATION IN AEROBIC EXERCISE

By

Larry Gage

August 1990

Chairperson: Harry Grater
Major Department: Psychology

Prior research on successful exercise adoption has

focused on programmatic and behavioral aspects of exercise

programs, often omitting personal factors. This study was

designed to focus on individual beliefs contributing to

aerobic exercise adoption, using the Health Belief Model

(HBM) as a foundation for the instrument developed. The

beliefs selected for examination in this study were

perceived benefits of aerobic exercise, perceived barriers

to aerobic exercise, perceived susceptibility to disease,

perceived severity of possible disease conditions, and

general health motivation. The two purposes of the study

were to develop a valid and reliable measure of beliefs

related to aerobic exercise and to test the performance of

the beliefs in predicting aerobic exercise participation.


viii







A survey based on the HBM was developed to assess

respondents' beliefs about exercise and health. The

questionnaire was sent twice to a convenience sample of

334 adult faculty at a mid-sized college in central New

Jersey. The first administration of the questionnaire

yielded 179 usable responses, with 165 received in the

retest administration.

The questionnaire was evaluated by an item analysis

and measures of content validity, internal reliability

(alpha coefficients from 0.832 to 0.935 were found for the

final five scales), and test-retest reliability (r=0.813

for the total scale). Based on these tests it was

concluded that the measure was reliable with indications

of validity. Correlational and factor analysis tests of

the independence of the beliefs constructs as

operationalized in the questionnaire found some

association between the scales.

Multiple regressions and discriminant function

analyses were computed, providing predictive validity of

the beliefs measure for the criterion variables of

exercise adoption stage and level of exercise reported by

subjects. The independent belief variables accounted for

35% of overall variance (multiple r square) for categories

of exercise behavior, 40% for exercise adoption stages in

multiple regressions on these variables. The instrument

performed best in distinguishing between sedentary







subjects and aerobic exercisers, accounting for 51% of

overall variance and correctly classifying 82% of the

subjects. The main predictor for the criterion categories

was identified as perceived barriers to aerobic exercise,

corroborating similar research using HBM beliefs to

explain other preventive behavior.













CHAPTER 1
INTRODUCTION

The Costs of Illness and Solutions
Offered by Counseling Psychology

Americans spend eleven and one half percent of their

gross national product for health care in all its forms

("A Solution", 1988). This figure represents a two percent

increase since 1984, when concerted efforts began to limit

the growth of spending, and a five and a half percent

increase since 1965. In 1990, the projected share of the

GNP devoted to health care is expected to be twelve

percent, for a total expenditure of 750 billion dollars

(Kiesler & Morton, 1988).

It has been noted that "health" care actually refers

primarily to interventions with an illness, not to actual

promotion of health; only about two percent of U.S.

expenditures on health are for disease prevention and

control measures (Knowles, 1977). The rest of the budget

primarily services the Medicare and Medicaid programs,

programs oriented primarily toward remediation of existing

illness or injury.

This allocation of budget priorities misses the cause

of many of the illnesses treated, allowing the genesis of

most health problems to go unchanged and unaddressed.

Janis, in an article detailing counselor behavior







effective in supporting client behavior change, notes that

"the most serious medical problems that today plague the

majority of Americans and Europeans are not primarily

medical; they are behavioral problems requiring the

alteration of personal habits, preferences, and

decisions." (Janis, 1983, p. 146). Supporting this

observation, Powell (1988) cited an analysis of the causes

leading to lost years of life, noting that Lifestyle

factors were the largest proportion at 53 percent.

Following Lifestyle, in order, were Environment (22%),

Human Biology (16%), and the Health Care System itself

(10%; note: percentages rounded).

The lack of effort in the area of disease prevention

and control is not for lack of knowledge about what

personal health behavioral changes might be effective.

Belloc and Breslow (1972), in a very large longitudinal

study of over 7000 adults, found seven health practices

significantly related to health and life expectancy: 1)

three meals a day at regular times and no snacking; 2)

breakfast every day; 3) moderate exercise two or three

times a week; 4) adequate sleep; 5) no smoking; 6)

moderate weight; 7) no alcohol or only in moderation. A

45-year-old man who practices 6-7 of these habits has a

life expectancy ten and one-half years longer than one who

practices 0-3 of them (Belloc & Breslow, 1972). Despite








the availability of this study and others like it, few

programs to alter behavior exist.

Part of the problem in adopting a health promotion

focus is with the lack of immediacy of results from

efforts directed at changing health habits. Knowles

(1977), in comparing such an undertaking to traditional

public health practice, found "the knowledge required to

persuade the individual to change his habits is far more

complex, far less dramatic in its results, far more

difficult to organize and convey--in short, far less

appealing and compelling than the need for immunization"

(p. 61). For the person with questionable health habits,

the personal consequences of those habits are not visible

in their daily accretion or change, making programs for

behavior change difficult to target and execute.

In a description of the World Health Organization's

Health for All by the Year 2000 (HFA/2000) program,

Diekstra and Jansen (1988) note a large potential role for

the profession of psychology in accomplishing the

ambitious goals set forth there. They specify the fields

of psychological medicine, behavioral medicine, and health

psychology. As HFA/2000 concerns itself chiefly with

prevention and health-enhancing lifestyles, imagining its

realization without psychological support is indeed

difficult (WHO, 1981).







Many possible contributions of the field of

psychology with the goals of HFA/2000 can be identified.

Kiesler and Morton (1988) describe such opportunities for

"psychology in the public interest", citing facets of

psychology that well suit it to preventive efforts in the

area of health: 1) an empirical orientation; 2) expertise

not traditionally allied with medicine and health care; 3)

emphasis on both prevention and wellness; and 4) knowledge

about the effect of the environment on behavior and

well-being. Such expertise is pivotal to the ultimate aim

of changing behavior to reduce risk factors in the

population at large.

Indeed, the concept of "behavioral health" has been

discussed for most of this century, with some recent

attempts to specify and codify what is meant by the term.

Matarazzo (1980) defines behavioral health as

a new interdisciplinary field dedicated to promoting
a philosophy of health that stresses individual
responsibility in the application of behavioral and
biomedical science knowledge and techniques to the
maintenance of health and the prevention of illness
and dysfunction by a variety of self-initiated
individual or shared activities." (p. 813. Emphasis
in original).

He proposes this field as a way of progressing beyond the

limits of traditional approaches to health.

In a discussion of the potential role of counseling

psychology in public health, Thoresen and Eagleston (1985)

emphasize the traditional educational model that serves as

a foundation for the field. This approach lends itself to







health promotion in two related ways: "(1) the promotion

and maintenance of good health through the development of

healthy habits and lifestyle (2) the prevention and

treatment of disease through changing unhealthy behaviors,

especially those that may be associated with certain

chronic diseases and health problems." (Thoresen and

Eagleston, 1985, p. 70). They argue for consideration of

the cognitive, behavioral, and environmental factors that

have an impact on the issue of health along with

physiological ones.

Harris and Guten (1979) point out that an avenue

little explored in the area of health protective behavior

is how individuals attempt to attain health as producers

of this commodity rather than be consumers of others'

services. This suggestion is made in a discussion of their

findings in a study of how individual beliefs relate to

self-identified health protective behavior. Such a view

represents a challenge to the paradigm of conceptualizing

health; it also argues for investigation of the personal

characteristics that affect involvement in health

protective or enhancing activities.

A principal health protective and enhancing activity

that is receiving more research attention is aerobic

exercise. Regular aerobic exercise has been shown to be

beneficial in a number of different human functions,

including both physiological and psychological realms

(Folkins & Sime, 1981; Morgan, 1981; Paffenbarger and Hyde








(1988); Sinyor, Schwartz, Peronnet, Brisson, & Serganian,

1983; Stern & Cleary, 1981; Taylor, Sallis, & Needle,

1985). The need for exercise can be self-assessed or

prescribed by a health professional who has determined an

appropriate application. Exercise has been used

successfully in the treatment of depression (Greist,

Klein, Eischens, Faris, Gurman, & Morgan, 1979), coronary

heart disease risk modification (Stern & Cleary, 1981),

and obesity (Epstein & Wing, 1980). As has been observed,

the problem of adherence has compromised better assessment

of the efficacy of exercise in treatment regimens (Martin

& Dubbert, 1982).

Even moderate amounts of exercise have been shown to

be beneficial. In a very large study examining the

relationship varying levels of fitness to subsequent

mortality, a group of researchers found a "strong, graded,

and consistent inverse relationship between physical

fitness and mortality in men and women" (Blair, Kohl,

Paffenbarger, Clark, Cooper, & Gibbons, 1989). In

reporting their findings the authors observe that the

prevalent sedentary lifestyle presents an important public

health problem.

Attrition From Exercise Programs

The casual observer might well form the impression

that most people in the population at large exercise.

Exercisers are quite visible, as are advertisements for







health clubs and other "health-oriented" services. Such an

impression would be in error, however, when compared to

figures describing actual exercise behavior. A recent

overview of American participation in exercise found that

only 20% of the population exercise intensely enough and

often enough to meet current guidelines for fitness or

reduce the risk of chronic disease or premature death.

(Dishman, 1988). Another 40% are active to some level, but

not enough to derive a fitness benefit. This shows that

most Americans fail to perform a behavior with proven

efficacy in health promotion and remediation of health

problems.

Despite the growing recognition of the value of

exercise among professionals and laypersons alike, a

continuing pattern is the failure of most beginners in

exercise programs to persist in their efforts. This

pattern is observed even in the face of urgent medical

conditions for which exercise has proven an effective

treatment (Carmody, Senner, Malinow, & Matarazzo, 1980;

Dishman, Ickes, & Morgan, 1980; Martin & Dubbert, 1982).

Martin and Dubbert (1982) summarized findings on

clinical applications and promotion of exercise in

behavioral medicine, contending that measuring the

efficacy of exercise as a clinical treatment regimen was

hampered by poor adherence rates. They maintain that this

pattern introduces doubt even in areas where exercise is

generally agreed to be effective, as in obesity or








cardiovascular risk reduction. Commenting on the lack of

an effective means of keeping patients identified as

at-risk in a program of exercise, they state: "we believe

that far too little attention has been directed toward the

cognitive/psychological/social variables controlling

exercise adherence." (Martin & Dubbert, 1982, p. 1013).

They recommend the tailoring of individual packages to the

needs and profile of the individual undertaking an

exercise program. They document a need for more

information about the impact of different personal

variables on the success or failure of an exercise program

before being able to employ such packages successfully.

Attrition, or its parallel phenomenon relapse, is not

a problem unique to exercise (McAlister, Farquhar,

Thoresen, & Maccoby, 1976; Meichenbaum & Turk, 1987).

Representative of a number of writers is the Martin et al.

(1984) observation that the exercise relapse curve appears

similar to the negatively accelerated curve found for the

addictions; the majority of the relapses occur during the

first several months, followed by continued, more gradual

rates, finally leveling off at one year between 55% and

75% dropout. For exercise, relapse refers to the

phenomenon of discontinuing the behavior, as compared to

addiction where reference is to resuming an undesirable

behavior. Dishman, Ickes, & Morgan (1980), discussing a

similar observation, speculate that similar mechanisms may







operate across many behavior change problems. As put in a

related study:

the remarkable correspondence between dropout
patterns in exercise programs and programs of
psychotherapy, as well as drug, alcohol, and smoking
treatment, and hypertension control suggests
that similar influences may operate across many
health care settings. This similarity at least
implicates characteristics of the participant as
potential adherence predictors. (Dishman & Gettman,
1980, p. 296)

Activity in exercise research has begun to address

the problem of attrition from exercise programs, examining

the phenomenon in an attempt to identify factors affecting

the successful adoption of an exercise regimen (Martin &

Dubbert, 1982; Dishman, 1982; Gale, Eckhoff, Mogel, &

Rodnick, 1984). In a comprehensive review of these factors

Dishman (1982) organized them into areas that take into

account all the variables likely to have an impact on the

outcome of an exercise adoption attempt. The main areas

named include 1) psychological features of the exerciser;

2) biological features of the exerciser, including health

status; 3) demographic features of the exerciser;

4) situational characteristics of the exercise setting;

5) strategies/clinical interventions used to encourage

adoption of exercise habits; and 6) aspects of the

person-setting interface, including ways the interaction

between the person and the setting affects subsequent

decision-making and behavior. Such a summary is not unique

to the particular challenges posed in the area of exercise

behavior; similar findings are noted in an analysis of








adherence factors affecting the outcome of treatment

regimens prescribed by health care providers (Meichenbaum

& Turk, 1987).

Most research on exercise has addressed the social,

environmental, and behavioral aspects of the exercise

adoption process. Typical of research in the area of

exercise adherence is the comprehensive series of studies

performed by Martin et al. (1984). In these studies, a

decidedly behavioral focus yielded much valuable data

about the effects of social support, cognitive strategies

to accompany the exercise, relapse prevention training,

attendance lotteries, personalized feedback, and the

structure of the goal-setting for the individual's

exercise program. Using this example in light of the

Dishman categories cited above, one can see the emphasis

on 4) situational characteristics of the exercise setting;

5) strategies/clinical interventions used to encourage

adoption of exercise habits; and 6) aspects of the

person-setting interface.

In an already-quoted review that presents a summary

of much of the research on exercise adoption, Martin and

Dubbert (1982) make the puzzling observation that one's

attitude toward exercise does not appear to predict

participation or later adherence to a program of exercise.

Given the established links between attitudes and behavior

(Ajzen & Fishbein, 1977; Cooper & Croyle, 1984) and







specific studies establishing the relationship in the case

of other behaviors (Becker, Haefner, Kasl, Kirscht,

Maiman, & Rosenstock, 1977), such an observation cannot be

accepted as a given without supporting research. The

research necessary to determine the presence of such a

relationship has only recently commenced (Sonstroem,

1988).

The Health Belief Model and Its Utility
in Exercise Adoption Research

As a tool for comprehensive measurement of

psychological process, the Health Belief Model has shown

consistency and robustness, having value for health

practitioners and researchers addressing many varied kinds

of behavior (Janz & Becker, 1984). It enables a

comprehensive view of many beliefs that influence a

person's predisposition to act in a certain way, with the

exact mechanism of that influence still under study.

A belief is considered the cognitive part of an

attitude toward an object. A belief represents the

information an individual has about an object, as compared

to the attitude, which represents the individual's overall

evaluation of that object. The belief links the object to

a quality in the person's mind. Some have postulated a

belief to have an emotional component modifying the

overall response to an object or action (Sonstroem, 1982).

That is, the person's feeling about the outcome of the

action in question becomes part of their beliefs about







that action, affecting the valence of their specific and

general attitudes, beliefs, and behavioral intention.

The relationship between attitudes and behavior has

been a well-documented phenomenon, especially when many

elements of the attitude-behavior pair correspond (Ajzen &

Fishbein, 1977). Theorists in the area of

attitude-behavior relations note the importance of

comparable levels of specificity in the attitude and the

behavior (Cooper & Croyle, 1984). A general attitude will

predict a multiple-act criterion better than a single-act

criterion, while a specific attitude works conversely,

predicting the single-act criterion better than the

multiple-act criterion. The need, as detailed by Godin and

Shepard (1986), is for appropriate measures of attitude to

be employed in the particular area of exercise behavior.

There has been a long-standing interest in

documenting the relationship between attitudes or beliefs

and behavior. The Health Belief Model has been one of the

most widely utilized of theories that have been formulated

to determine the nature and impact of beliefs in the area

of health protective behavior. What started as an attempt

to identify the factors underlying health behaviors has

evolved into a well-documented model with utility in a

variety of settings.

The Health Belief Model was developed in an attempt

to understand why people did not practice health

protective behaviors, first in regard to asymptomatic








diseases, later in an expanding number of conditions and

venues. Use of the model was later expanded to investigate

factors contributing to compliance with medical regimens,

(Becker, Maiman, Kirscht, Haefner, & Drachman, 1977;

Becker, Drachman, & Kirscht, 1974) with recent

investigations broadening its application to preventive

health behaviors (Riddle, 1980; Slenker, Price, Roberts, &

Jurs, 1984; O'Connell, Price, Roberts, Jurs, & McKinley,

1985).

An early overview of research employing the model

included a statement detailing its utility for health care

providers: "by knowing which Health Belief Model

components are below a level presumed necessary for

behavior to occur, the health worker might be able to

tailor intervention to suit the particular needs of the

target group or population" (Becker, Haefner, et al.,

1977, p. 30). Other investigations into the efficacy of

interventions designed to affect peoples' health beliefs

and thus subsequent behavior have shown them to be

successful (Becker, Maiman, Kirscht, Haefner, & Drachman,

1977; Kirscht, 1974).

The components of the Health Belief Model were

posited to identify cognitions and perceptions making up

the beliefs that early developers of the model found to

have the most impact on health behaviors (Kirscht,

Haefner, Kegeles, & Rosenstock, 1966). They include the







individual's subjective estimate of their susceptibility

to disease states; the perceived severity of the

conditions the individual feels vulnerable to contracting

or suffering; perceived benefits of the health protective

behavior being researched; and the perceived barriers to

performing that behavior. Added later to the Health Belief

Model was a construct addressing health motivation, which

was seen as a necessary part of the model when examining

behaviors with a more preventive or health-enhancing

nature (Becker & Maiman, 1975). Finally, having an impact

within the framework of the model are cues to action which

trigger the individual to act.

The Health Belief Model was described by

theoreticians associated with early work in its

development as measuring specifically elements of two

variables essential to the prediction of behavior: 1) the

value placed by an individual on a particular goal (i.e.

health or the avoidance of a disease); and 2) the

individual's estimate of the likelihood that a given

action will result in that goal (Maiman & Becker, 1974). A

summation offered by the framers of the model who

participated in its refinement includes all the elements:

the Health Belief Model hypothesized that persons
will generally not seek preventive care or health
screening unless they possess minimal levels of
relevant health motivation and knowledge, view
themselves as potentially vulnerable and the
condition as threatening, are convinced of the
efficacy of intervention, and see few difficulties in
undertaking the recommended action. (Becker, Haefner,
et al., 1977, p. 29)








Investigations employing the Health Belief Model have

been successful in their aim of predicting or explaining

the level of non-exercise preventive health behaviors. Two

evaluations of Health Belief Model research found it to

have significance in the degree of association of its

principal components with almost every specific behavior

under study. The appraisals covered 46 different studies

that utilized the Health Belief Model. The pattern of

significance held when the type of behavior being

investigated was sick role behavior as well as with

preventive health behavior, and for earlier as well as

more recent studies (Becker, Haefner, et al., 1977; Janz &

Becker, 1984). The level of significance for the

components was also consistent in both retrospective

(n=28) and prospective (n=18) studies. The model appears

to have potential as a useful tool for the investigation

of factors shaping exercise behavior, one of the most

global forms of health-related behavior.

The Role of an Attitude/Beliefs Study
in Exercise Adoption Research

The relatively new area of research into exercise

adoption has been yielding specific data about the factors

that influence successful adoption and maintenance of an

exercise habit, particularly from the point of view of the

practitioner working with beginning exercisers. Behavior

modification approaches, as detailed by Knapp (1988),

Martin et al. (1984), and Franklin (1978), have shown








effectiveness at increasing adherence rates. Such

approaches now include relapse prevention strategies,

integrating newly gained knowledge about habit change. The

attractiveness of the exercise itself for the beginning

exerciser has been shown to be an important factor

(Franklin, 1978; Gale, Eckhoff, Mogel, & Rodnick, 1984),

along with the approach used by the instructor in an

exercise program.

The term exercise adoption was intentionally used for

the current study to help provide emphasis on the dynamics

whereby an individual actively seeks to adopt an exercise

program as a part of his/her daily behavior. The adoption

process is illustrated in a stage theory of change

detailed by Prochaska and DiClemente (1983). The process

begins with a precontemplation stage, with movement

proceeding to a contemplation stage. Actual behavior

change begins in the action stage, which becomes the

maintenance stage if the change is long-standing and

durable. Failure to maintain the change moves the person

into a relapse category. Such a schema helps to capture

more of the phenomenon of behavior change than just the

actual presence or absence of behavior.

The thoughts and feelings of the exerciser have been

relatively neglected in research on the exercise adoption

process, as compared to examination of the appropriate

techniques. An example of one such conceptualization of







personal cognition/self perception is self-efficacy theory

(Knapp, 1988; Bandura, 1982). While indications are that

exercise self-efficacy plays a role in the subsequent

outcome of an attempt to begin an exercise program,

results are not conclusive (Sonstroem, 1988). Discussions

of psychological characteristics having an impact on habit

change outcomes usually mention this construct, but it has

not been operationalized for the exercise adoption

problem.

The need for such socio-psychological correlates of

exercise behavior has been asserted by those conducting

cognitive-behavioral programs for change in exercise

adherence studies (Martin et al., 1984). The personal

characteristics and, occasionally, beliefs that influence

decision-making and subsequent behavior have been well

documented in the case of other behaviors, even other

health-related behaviors, but exercise behavior remains

largely unexplored in regard to beliefs.

The Health Belief Model method of assessment has

proven validity and reliability in determining individual

beliefs, and has become established as a tool for

predicting health behavior (Janz & Becker, 1984). The

first applications of the model in the area of exercise

behavior have proven encouraging, with limited

generalizability to all forms of exercise (Riddle, 1980;

Sonstroem, 1987; Slenker, Price, Roberts, & Jurs, 1984).









Dishman (1982) states the need to "determine the

effectiveness of various potential adherence strategies

. Consider the relative effectiveness of manipulating

abstract, conceptual beliefs" (p. 261). To date little

activity has focused on the development of interventions

to effect changed beliefs in those seeking to adopt

exercise behavior as part of their lifestyle. The primary

focus with the Health Belief Model up to now has been an

individual's participation in medical or

disease-prevention strategies. The current study was

proposed to provide a basis for a structured intervention

to increase the success rates for exercise adoption

efforts. With the capability to reliably assess beliefs

about health and exercise, the efficacy of such

interventions may be evaluated.

Aerobic Exercise and Health Beliefs

Extending the Health Belief Model mode of research to

the area of aerobic exercise behavior is a step indicated

by other prior studies that have explored the role of

health beliefs in preventive health behavior, including

specific forms of exercise. The present study was designed

to show that a reliable and valid mechanism of measurement

of beliefs regarding exercise can be developed, including

a demonstration of predictive validity of the instrument

in reference to self-reported aerobic exercise adoption

stages and levels of aerobic exercise.








Individual tailoring of programs to each person

seeking to begin an aerobic exercise program (whether

self-motivated or prescribed) has been recommended for

greater success achieving lasting change and implementing

the goal of an exercise regimen (Gale, Eckhoff, Mogel, &

Rodnick, 1984). Circumstances for a prescribed aerobic

exercise program may be weight reduction or cardiovascular

rehabilitation, while many reasons have been cited by

people undertaking exercise programs voluntarily, from

appearance to preparation for participation in a sport. A

specific, comprehensive beliefs measure would provide for

identification of personal beliefs relevant to entry into

an aerobic exercise program.

Martin and his fellow researchers have identified

many of the program strategies and interpersonal

approaches that enable the fitting of an exercise adoption

approach to the needs of the person starting a program of

exercise (Martin et al., 1984; Martin & Dubbert, 1982).

Missing from the daily practice of health care workers who

address the exercise adoption challenge is a consideration

of the individual's attitudes and beliefs about the

undertaking. Such an omission is, in part, due to lack of

a means with which to assess a person's beliefs about

health and exercise.

An historical drawback in Health Belief Model

research is that measures employed to assess belief







constellations for the behavior under study have been

idiosyncratic to each particular investigation.

Surprisingly, no one procedure of instrumentation has

emerged as a standard in any area covered by the dozens of

studies utilizing the Health Belief Model. In one attempt

to organize and verify the reliability and validity of

constructs within the Health Belief Model, the researchers

comment on the limitations imposed by the lack of such

work:

The absence of reliable and valid measures not only
limits the practical utility of the theoretical
formulation, but also reduces the potential for
developing a reliable body of knowledge on which to
design intervention strategies to change personal
health behavior. (Jette, Cummings, Brock, Phelps, &
Naessens, 1981, p. 83)

No attempt has been made to develop a standard instrument

to be employed as an adjunct for aerobic exercise adoption

situations, whether for research purposes or for use as a

treatment component.

Applying the Health Belief Model to
Aerobic Exercise Behavior

In studies where interventions utilizing Health

Belief Model components have been performed, successful

changes in targeted preventive health behaviors were

effected (Beck & Lund, 1981; Becker, Maiman, Kirscht,

Haefner, & Drachman, 1977). Behaviors included oral

hygiene care and mothers' successful follow-through on

treatment for their children' obesity. The technique of

beliefs modification has favorable potential as a method







for influencing the process of behavior change,

specifically the adoption of aerobic exercise behavior.

No definite relationship has been established between

the Health Belief Model components and aerobic exercise as

a dependent variable. The purpose of the present study was

to test for a link between the belief variables of the

Health Belief Model and aerobic exercise, using a

methodology paralleling prior, successful preventive

health behavior investigations. In these earlier studies,

the use of beliefs assessment instruments has provided for

successful prediction of a variety of targeted preventive

health behaviors (Tirrell & Hart, 1980; Chen & Tatsuoka,

1984; O'Connell, Price, Roberts, Jurs, & McKinley, 1985).

Previous studies have shown the Health Belief Model to

have similar potential in the successful measurement of

relevant beliefs and the prediction of aerobic exercise

behavior (Riddle, 1980; Slenker, Price, Roberts, & Jurs,

1984).

A valid instrument for assessing beliefs in reference

to aerobic exercise will provide a basis for successful

employment of belief component manipulations in public

health, recreation, and counseling settings, toward the

end of positive improvements in the adoption of aerobic

exercise behaviors. Belief manipulations can range from

personalized, one-on-one discussions to mass media

campaigns that involve an entire community. Such regimens

have been proven effective even on a very large scale. An








example of one such intervention often cited is the

Stanford Five-City Project, where significant reductions

in cardiovascular risk factors occurred over a thirty

month period following an ongoing public health

information campaign (Thoresen & Eagleston, 1985).

The method proposed parallels that used in successful

applications of the Health Belief Model to explain and

predict other preventive health behavior, as well as that

used in earlier applications of the model in the example

of illness avoidance/sickness reduction. As has been

noted, correlations of model components with target

behaviors that were obtained in past investigations have

been significant, with some variation in the degree of

significance. Initial exploration of the constellation of

health beliefs for exercisers has yielded encouraging

results. These findings have provided a foundation for an

effort to develop an instrument for determining Health

Belief Model beliefs in reference to aerobic exercise

(Sonstroem, 1987; Slenker, Price, Roberts, & Jurs, 1984;

Riddle, 1980). Such an instrument would provide the basis

for measurement that would enable assessment of any

subsequent manipulation of beliefs, in that change could

then be reliably measured.

Posing the Health Belief Model constructs in the

context of a standard definition of aerobic exercise

(American College of Sports Medicine, 1978) allows for








corroborative research and provides a basis for

comparisons to be made on the basis of a general

consideration of aerobic exercise, not just one particular

form. The College guidelines specify exercise quantity and

quality: 1) Frequency of training 3-5 days per week; 2)

Intensity of training 60%-90% of maximum heart rate

reserve; 3) Duration of training 15-60 minutes of

continuous aerobic activity, with duration dependent on

intensity; and 4) A mode of activity that involves large

muscle groups, that can be maintained continuously, and is

rhythmical and aerobic in nature (American College of

Sports Medicine, 1978, p. vii). The structure of the

current investigation was intended to provide a meaningful

foundation for future intervention studies to be

attempted, as well as other prospective studies that

monitor behavior change given an initial constellation of

beliefs.

In the following chapter, a more detailed examination

of the literature in the areas of exercise and exercise

adoption will be presented, including theory and practice

in exercise adoption, adherence, and compliance contexts.

A close inspection of factors affecting the exercise

adoption process will follow, including cognitive,

behavioral, and interpersonal elements. The Health Belief

Model and its application in other studies will then be

presented, along with investigations documenting the

suitability of the Model for aerobic exercise adoption








research and practice. Particular issues affecting the

development and use of an instrument to measure beliefs

about aerobic exercise will also be examined. Chapters 3

and 4 will describe the development, evaluation, and

testing of the beliefs/exercise assessment instrument. In

Chapter 5, specific findings and the implications of the

results for future investigations utilizing Health Belief

Model theory will be discussed, as well as indications for

the area of exercise adoption research in general.













CHAPTER 2
REVIEW OF THE LITERATURE

The following review will examine the literature on

exercise, exercise adoption, adherence to exercise

programs and the factors affecting adherence. Also to be

examined is the Health Belief Model and its use as an

explanatory tool in research on peoples' health-related

decision-making and behavior. Finally, research relevant

to the decision to apply the Health Belief Model in the

exercise adoption context will be reviewed.

The Benefits of Exercise

The benefits of regular exercise seem almost without

question; the findings, however, are not as unqualified as

the casual observer might expect. Many different kinds of

studies have been performed in an effort to ascertain

exercise effects along a continuum ranging from very

narrow, specific questions to very broad, inclusive ones.

An example of the former is a study by Sohn and Micheli

(1984) that investigates the effect of running on the

development of a specific form of arthritis, an example of

the latter is Folkins & Sime's (1981) analysis of exercise

effects on mental health. Their review was a critical

examination of the results of over 39 studies








investigating the impact of exercise on psychological

states.

Research studies on exercise also vary according to

type of exercise, length of exercise, the method of

monitoring adherence to an exercise program, and the

various groups of subjects studied. The following review

will focus on research that utilizes a more general,

inclusive definition of aerobic exercise, that is exercise

that produces an elevated heart rate for extended periods.

Another factor assumed and sought as an element of the

research cited is regular, versus episodic, participation

in programs of exercise. Factors utilized in the selection

follow from American College of Sports Medicine (1978)

recommendations about the quantity and quality of exercise

needed for "developing and maintaining cardiorespiratory

fitness and body composition in the healthy adult"

(American College of Sports Medicine, 1978, p. vii). The

effects "bias" in selecting research on benefits is toward

psychological results.

Stern and Cleary (1981) citing Naughton (1974) list a

summary of the clinically observable physiological

benefits of exercise, illustrating the pattern of changes

that accompany improved fitness. They include

1) significant reduction of heart rate and systolic blood

pressure, at rest and at work; 2) significant increases in

peak oxygen uptake; 3) significant decreases in myocardial







(heart muscle) work at rest and at work; 4) changes in

body composition, including reduced fat and increased

muscle mass; and 5) changes in circulation to patterns

observed in healthy, physically active subjects. This

pattern is noted in many studies as the training effect,

and various of the features are often used to test for

fitness levels, as they were in the Stern and Cleary

(1981) study on changes in a population of exercisers who

had suffered myocardial infarct.

In a chapter examining the effect of exercise on

coronary heart disease (CHD) rate and risk, Paffenbarger

and Hyde (1988) found significant differences in

longitudinal studies of two very different populations.

For a group of 3,686 San Francisco longshoremen, those in

the group who had the highest levels of physical activity

as part of their jobs were found to have significantly

less risk of CHD than their counterparts who did not work

as hard. This effect held for all age groups, and was

strongest for the youngest age group. The groups were

studied over a 21-year period, with the work level of

8,500 kilocalories per week used as the cutoff between

low- and high-energy-output groups. In an impressive

finding, the degree of increased CHD risk was greater for

those who were in a low energy output group (versus a high

output group) than the increased risk that accrued for

being a heavy cigarette smoker (greater than one pack a








day) or for having high blood pressure (greater than or

equal to the mean level for the age cohort)!

A parallel study, involving 16,936 Harvard alumni,

found similar results. Alumni engaging in strenuous

activity plus a minimum of 1000 kilocalories a week of

other light activities had less than half the CHD

incidence of their nonathletic, sedentary classmates

(Paffenbarger & Hyde, 1988). Exercise was found to be the

second most influential factor affecting mortality from

CHD causes, preceded by smoking and followed by

hypertension. Exercise was second only to parental history

of hypertension in its impact on whether the alumni

developed hypertension themselves.

Recent results demonstrate some of the likely

mechanisms by which regular exercise may contribute to

lower CHD mortality. A study investigating the impact of

exercise on blood cholesterol levels found that "good"

cholesterol (HDL or high density lipoprotein) began

increasing while "bad" cholesterol (LDL/VLDL or low/very

low density lipoprotein) began decreasing after a seven

week exercise program, a fairly rapid effect of exercise.

The program consisted of four sessions per week of

treadmill running for twenty minutes per session to 80%

predicted maximum heart rate. Subjects ate a controlled

diet and underwent frequent blood testing to assess

lipoprotein and other blood element levels. A parallel







finding was a significant decrease in postprandial levels

of lipoproteins, showing a faster uptake of cholesterol

(Weintraub, Rosen, Otto, Eisenberg, & Breslow, 1989).

Exercise was demonstrated to have a positive effect

on the coping responses to a stressor when trained and

untrained subjects were compared. Heavy aerobic exercisers

were assigned to the trained group, while non-exercisers

comprised the untrained group. In addition to a standard

"training effect", (Higher maximal oxygen uptake, lower

blood pressure) subjects showed a faster adaptive

biochemical response when subjected to a psychosocial

stressor (Sinyor, Schwartz, Peronnet, Brisson, and

Serganian, 1983). Catecholamine levels peaked earlier, and

at higher levels, for the trained subjects. This effect

was described by the authors as a more efficient coping

arousal. Additionally, heart rate returned to normal more

quickly in the trained group of subjects, reflecting a

recovery from the experience of the stressor that was

faster than in the untrained group.

Stern and Cleary (1981), in the above-noted study on

a male post-infarct population of exercisers, noted an

increased work capacity for the exercisers as measured in

testing on a motorized treadmill. Their program of

low-level exercise consisted of two to three sessions per

week for six weeks for an average of 15 minutes of

exercise per session. This program produced an average ten









percent increase in the work capacity of subjects over the

course of the study.

Wilfey and Kunce (1986) found the magnitude of

training benefit to be greater for subjects with lower

initial fitness levels, in both physiological and

psychological measures. For low fitness/high stress

subjects the overall changes were the greatest, as might

be projected for people of the group with the most to gain

from completing a two month long comprehensive exercise

training program. Heart rate decreases were greatest for

the low fitness/high stress group, followed in order by

the low fitness/low stress group, the high fitness/high

stress group, and the high fitness/low stress group. A

similar pattern obtained in measuring gains on a fitness

test, with the high fitness/low stress and high

fitness/high stress groups exchanging ranks. The finding

that persons of lower fitness gain more from training than

those at higher fitness levels may seem obvious, but it

also illustrates the linear nature of the physiological

gains obtainable through an exercise training program.

Many psychological benefits have been documented as a

product of regular exercise, with findings consistent

through many studies. The positive effects can be

identified with a high degree of certainty as associated

with the exercise itself and not with other variables.

Well-controlled studies do vary in the specific effects








noted, often as a result of their initial focus or

particular changes identified as the target of the

investigation.

In a review of his own and others' work on the short

and long term effects of exercise, Morgan (1981) found

some consistent indications that regular exercise,

performed for a minimum of twelve weeks, results in lower

scores on anxiety and depression scales, while measures of

well-being increased. This pattern held across different

measures and different periods of exercise beyond the

twelve week minimum. Morgan concludes that exercise is

clearly associated with changes in the three areas, with

an additional observation that causality is harder to

prove.

A related study found reduced levels of anxiety in

physically trained subjects following exposure to a

psychosocial stressor when compared to untrained subjects

(Sinyor, Schwartz, Peronnet, Brisson, & Serganian, 1983).

Aerobic points earned and physiological response measures

were used to differentiate trained from untrained

subjects. The anxiety measure was the Spielberger State

Anxiety Inventory, administered prior to and following

different stressor tasks. Following the tasks, trained

subjects had significantly lower SSAI scores, showing

faster recovery from induced anxiety.







One of the largest, most complete studies was

conducted on a population of 651 subjects that had

experienced a myocardial infarct less than three years

prior to their involvement in the research. Stern and

Cleary (1981) investigated the psychosocial effects of a

low level exercise program on participants, finding a

decrease in the percentage of depressed subjects and in

depression scores as measured by the MMPI depression

subscale. On a group of twelve clinical symptoms,

persisters in the exercise program improved on ten of the

twelve as rated by spouses. Differences were found to be

significant between the initial and followup evaluations,

which were administered six weeks apart. Although the

authors see the exercise group as benefiting more than a

non-exercise group, they qualify the finding as not being

wholly attributable to the exercise component.

One of the most thorough evaluations of the impact of

exercise on mental health was a review of research

conducted by Taylor, Sallis, and Needle (1985). They found

positive effects in many of the studies they examined

where exercise was used as a treatment modality for

clinical conditions, many with a significant degree of

change. Mild to moderate depression was cited as showing

the most promise for change, with many studies documenting

positive effects. The hypothesized mechanisms of change in

exercise programs used to treat depression, while not








certain, were increased neurotransmission of

catecholamines, endogenous opiates, or both; diversion,

social reinforcement, and improved self-efficacy.

Taylor et al. (1985) found both state and trait

anxiety to be effectively reduced by varying levels of

exercise, with a greater effect noted in subjects whose

initial anxiety levels were higher. Effects were more

conclusive for state anxiety than for trait anxiety, with

both types showing a positive benefit in most studies

examined. The primary effective mechanisms here were

described as diversion, social reinforcement, experience

of mastery and an improved response to stress. Taylor et

al. (1985) also noted that improved self-confidence,

cognitive function, and sense of well-being were

associated with exercise and physical activity.

Perhaps the most complete of the major studies

reviewing the impact of exercise on mental health is the

massive compilation by Folkins and Sime (1981). Their

critical review is often cited in other studies as a

significant overall finding of the beneficial effects of

exercise on human psychological function. Often omitted in

a citation of their work is the observation that most of

the research on exercise effects that they reviewed were

not true experimental designs. They note a preponderance

of pre-experimental or quasi-experimental designs, a

drawback that is particularly limiting in longitudinal










studies. Even within the true experimental research,

however, a pattern of positive effects is cited.

Folkins and Sime (1981) found fitness to be related

to the following aspects of mental health: 1) improved

work patterns, including reduced absenteeism, fewer

errors, and improved output; 2) improvement in mood state,

particularly for distressed or initially unfit

individuals; 3) improved self-concept and body image; 4)

reduced levels of depression where exercise is used for

treatment of depression; and 5) improved cognitive

function. The authors caution that in some instances the

results obtained in a study were not significant; overall

they were convinced of the utility of exercise in

producing improved psychological states. They single out

self-concept and depression as areas where the results are

less equivocal.

In a carefully controlled study, Bahrke and Morgan

(1978) compared exercise, meditation, and quiet rest to

determine their relative efficacy at inducing relaxation

for experimental subjects. Each "treatment" was employed

for twenty minute periods, with the exercise condition

being treadmill walking to seventy percent of age-specific

maximal heart rate. Relaxation was measured using a state

anxiety scale that was employed preceding, immediately

following and ten minutes following the experimental







conditions. All three treatments were effective in

reducing anxiety, causing decrements that differed

significantly from the initial measurement. Interestingly,

the three treatments did not differ significantly from

each other in their effects. The authors found the

findings striking in that the mechanism of exercise

(physiological arousal) is so different from that of

either quiet rest or meditation in the quality of its

effects. They also found the exercise effects corroborated

earlier investigations into the impact of exercise on

anxiety levels. It must be noted that "lack of anxiety"

may not be a universal criterion for relaxation; given the

arousal aftereffects on physiological measures it was the

choice for this study.

Morgan and O'Conner (1988) have summarized some

limitations in the studies which document the positive

effects of various forms of exercise on mental health.

They note a unanimity among researchers that the higher

the level of fitness, the more desirable the level of

mental health. Next is noted the elusive nature of

evidence allowing clear statements of causality. Finally,

the lack of controlled studies with true experimental

designs, as noted above in the review by Folkins and Sime

(1981), precludes clear statements about cause and effect.

This point holds even in longitudinal studies that would









support the hypothesis that vigorous exercise leads to

beneficial mental health effects.

Citing a NIMH workshop that used a strictly limited

criterion for selection of statements about exercise

effects, Morgan and O'Conner (1988), list findings about

the influence of exercise on mental health. These findings

use carefully stated points to summarize what can be

stated about the positive effects to be gained from

exercise/fitness training:

1. Physical fitness is positively associated with
mental health and with well-being.
2. Exercise is associated with the reduction of
stress emotions such as state anxiety.
3. Anxiety and depression are common symptoms of
failure to cope with mental stress, and exercise has
been associated with a decreased level of mild to
moderate depression and anxiety.
4. Long-term exercise is usually associated with
reductions in traits such as neuroticism and anxiety.
5. Severe depression usually requires professional
treatment, which may include medication,
electroconvulsive therapy, and/or psychotherapy, with
exercise as an adjunct.
6. Appropriate exercise results in reductions in
various stress indices such as neuromuscular tension,
resting heart rate, and some stress hormones.
7. Current clinical opinion holds that exercise has
beneficial emotional effects across all ages in both
sexes.
8. Physically healthy people who require psychotropic
medication may safely exercise when exercise and
medications are titrated under close medical
supervision. (p. 95)

The exercise effect is thus shown to be dependable,

applicable to a wide variety of persons, and amenable to

use at the same time as other forms of treatment.

Peoples' perceptions about the benefits of a regular

program of exercise are equally as important as the








documented benefits. As will be seen in the discussion of

the components of the Health Belief Model, perceptions are

an important aspect of beliefs. In a study in which people

were polled about various forms of behavior they performed

to "protect, promote, or maintain health", Harris

and Guten, (1979) found that exercise behavior was cited

the third most often--behind nutrition and sleep--as one

of the "three most important things that you do to protect

your health." (p. 21). The important distinction here was

that the researchers recorded what behaviors the

respondents considered important for health protection,

versus a list of behaviors that clinicians perform or

would recommend. The level of utilization of health

protective behaviors held even when health condition of

the respondent varied from good to poor, with the emphasis

shifting from self-initiated lifestyle choices like diet

and exercise to utilization of the health care system.

Exercise Adoption

The phenomenon of exercise adoption may be patterned

after an area of research that provides a basis for

measurement and interpreting observations. Prochaska and

DiClemente (1983) have developed a theory of behavior

change which describes a person's movement through a

series of psychological/behavioral stages, resulting in

several different outcomes. In their work developing this

stage theory, Prochaska and DiClemente (1983) have focused








primarily on the cessation of undesirable behaviors, such

as smoking cigarettes.

As specified in their schema, a person's initial step

in the change process is from an immotive or

precontemplation stage to a contemplation stage. Using

cognitive/affective reevaluation of their situation and

behavior, the person is compelled to move to an action

stage, changing actual behavior. Should the target

behavior change be long term and durable, with

accompanying cognitive and behavioral changes to support

the target behavior, the stage entered into is that of

maintenance, where the behavior is ongoing and maintained

at a stable level. If behavior drops below the minimum

specified level of change, the person drops into the

relapse category, wherein the attempted behavior change is

abandoned for a period of time. The period may be brief or

extended, depending on the determination and resources of

the changer toward renewing the effort at change. As will

be detailed below, the relapse outcome is fairly common in

behavior change projects.

Employing the Prochaska and DiClemente (1983) schema

in the context of exercise underscores the need for

differentiation of adoption from adherence, which, as

generally employed by exercise researchers, includes only

the maintenance stage of the process. This stance excludes

other important and universal features of human attempts

to change behavior that are noted in a broader view of









change. The stage process as used in early studies applies

whether the change is self-initiated or prescribed by

other parties. At present the terms adoption and adherence

are often used interchangeably to refer to success or

failure to adhere to a program of exercise begun for any

reason, with many of the cognitive factors and much

personal history not taken into account.

Dishman (1988) notes the confusions inherent in the

current terms being used in behavioral science to describe

the exercise adoption process. He observes that compliance

and adherence are often used to describe the same

phenomena, yet are not generally recognized in catalogues

of psychological literature by definitions that conform to

their current utilization. He proposes employing the term

adherence as a general descriptor in the area of exercise,

to include the area of compliance. This comes closer to

meeting current needs and recognizing the entirety of the

exercise adoption process, yet the early stages of a

self-initiated change can be omitted by this term as well.

Too, other researchers explicitly link the terms

compliance and adherence (e.g. Oldridge, 1981), serving

their own needs in investigating exercise treatment

programs, but excluding important population groups of

exercisers and parts of their experience in entering into

an exercise program.







The research on compliance to exercise programs

addresses situations that are primarily prescribed

behaviors in response to a stimulus situation like obesity

or high blood pressure. The focus of compliance research

has been on practitioner behavior and characteristics of

the setting, with the interaction between client and

health care provider the main interest (Becker & Maiman,

1980; Janz & Becker, 1984). Research in compliance

assuredly does include individual characteristics,

providing the overlap and confusion of terms alluded to

above.

Examination of the research findings shows by

illustration some of the phenomena to be anticipated in

research on exercise adoption. A finding that has results

useful for the issue of self-change of habits is the

comprehensive study carried out by Perri and Richards

(1980). The study compared people who had carried out

successful self-change programs with those who had

attempted unsuccessful ones, in an attempt to determine

what personal characteristics or strategies differentiated

the two outcomes. Important indicators emerged for those

undertaking self-change programs or working with those who

do. Successful self-changers appear to be intuitively

skilled at behavioral technique, employing

self-reinforcement and persisting far longer in their

attempts than did unsuccessful changers. Of note for the

present study was the recommendation that persons









undertaking self-change programs insure that their program

is comprehensive in nature and should involve a number of

individually tailored procedures.

Some research (Sonstroem, 1987; Ward & Morgan, 1984)

has been performed using the stage schema applied to

exercise. Ward and Morgan appear to be the first to apply

the stage theory of change to exercise, finding that

adherence at 10, 20, and 32 weeks in an exercise program

was predicted by different sets of variables. Using the

Theory of Reasoned Action (Ajzen & Fishbein, 1977) as a

basis for a beliefs investigation, Sonstroem related the

belief constellation to a reduced number of the Prochaska

and DiClemente stages. He termed the process exercise

adoption, although without providing a rationale for the

use of that term versus the others available. The main

body of work cited in his review of the theoretical bases

for his research, he notes, does include subjects who were

seeking to change on their own. As the term "exercise

adoption" is rarely used, the more widely held "adherence"

term will apply through most of this review.

Factors in Adherence to Exercise

Exercise adherence is examined from many different

perspectives, with each providing information to compose a

picture of someone in the exercise adoption process. Some

studies examine the factors associated with dropout, where

others test for personal characteristics associated with a







successful, continued exercise program. Perhaps one of the

most complete recent studies on exercise adherence was the

collection of researches reported by Martin et al. (1984).

The series was designed in an attempt to isolate factors

that affect the outcome of exercise adoption attempts by

sedentary adults. The investigators' main interest was in

determining the efficacy of various cognitive-behavioral

procedures in support of exercise programs begun by people

attending a community exercise program. Dividing 143

subjects into six treatment conditions allowed the

researchers to test for the effectiveness of different

elements of behavioral techniques.

Each treatment group that began a running program

received differing combinations of cognitive-behavioral

strategies for the three months of the program, apart from

a common structure utilized by all groups. For each group

an "ideal" strategy was included, with the ideal based on

the past observed efficacy of each element. In Group 1,

the ideal was personalized feedback, distance goals (for

running), and fixed goals. Each group provided varying

combinations, allowing the researchers to compare group

and personalized feedback; time and distance goals;

flexible and fixed goals; distal (long range) and proximal

(short range) goals; and associative versus dissociative

cognitive strategies.

Analyses of variance and t-tests were used to test

for significant differences between conditions within








groups. Many of the variables investigated proved a

positive influence on the ultimate adherence of the

subjects beginning exercise programs. In particular,

social support, personal feedback/praise, flexibility in

goal setting, and distraction-based cognitive strategies

proved most effective in increasing rates of adherence. No

advantage was seen for time versus distance goals.

Impressively, overall adherence at the end of the three

months, for all subjects in the study, varied from 80-85

percent. This was considerably better than the 55 percent

adherence usually observed for this time period in an

exercise adoption group program (Martin et al., 1984). Of

interest here is the fact that 49% of the subjects in the

study had previously attempted an exercise program. No

differentiation of these "relapsers" from the subjects

beginning exercise for the first time was attempted.

Martin et al. (1984) also found class attendance and

self-report of exercise participation to correlate

significantly with "post" measures of fitness.

Another study illustrating recent methods used to

scrutinize exercise adherence is one by Dishman and

Gettman (1980) that examines many different psychobiologic

influences on ultimate adherence. The study used

physiological measures such as weight and percent body fat

along with psychological measures designed to measure

attitudes toward and valuing of exercise. A prospective







study with 66 subjects, it used subjects that were

beginning exercise programs for the first time, combining

healthy exercisers with coronary heart disease

rehabilitation subjects. The outcome of the entry into an

exercise program was labeled as either adherence or

dropout, with anyone not participating at the end of the

20 week period of the study labeled a dropout.

Using stepwise multiple regression, three variables

of the ones measured were found to significantly enhance

the prediction equation for adherence: 1) body fat

percentage; 2) a measure of self-motivation; and 3) body

weight. Taken together, these three variables accounted

for 45 percent of the overall variance and provided for

predicting adherence/dropout category in 79 percent of all

cases examined. The authors chose only one other

independent measure in addition to their own on

self-motivation, that of the health locus of control

(Wallston, Wallston, Kaplan, & Maides, 1976). The other

scales were subscales of the Attitude Toward Physical

Activity scale or the Physical Estimation and Attraction

scale. The ability of these subscales to contribute to a

prediction of subsequent exercise status may have been

compromised by their application within this study as

stand-alone variables.

In a study examining the long-term rates of adherence

for a population of male and female victims of myocardial

infarction, the investigators found only 18.7% remained at








the end of a forty month period (Carmody, Senner, Malinow,

& Matarazzo, 1980). Two hundred and six subjects were

followed up at four month intervals to see which remained

active in a prescribed exercise program. In the initial

four month period dropout was 30%, with the subsequent

rate of dropout reduced in each followup after the initial

period. This pattern duplicates the typical finding for

relapse/dropout in habit-change studies (e.g. Dishman,

1988), with the dropout rate somewhat greater than that of

a general population. Studies of this duration are rare,

so comparison is difficult. This is nonetheless a

surprising finding, given the explicit urgency attached to

the successful adoption of the exercise prescription for

this group.

Summarizing findings in a chapter reviewing studies

on adherence to post-myocardial infarction exercise

regimens, Oldridge (1981) identified some common

characteristics that tended to be associated with dropout.

The research reviewed focused primarily on the

characteristics of the enrollees, omitting formal measures

of their psychological or physical states. A profile

constructed using characteristics that recurred across

studies shows that a dropout is likely to be a blue collar

worker, to be inactive physically in his leisure time, to

be a smoker, and to have had more than one previous

myocardial infarction. The mechanisms whereby these







characteristics contributed to the outcome of dropping out

were described by Oldridge as being unclear. Some of the

subjects' negative evaluations of the programs in which

they were participating included statements like

"difficult to perform," "dislike physical training," or

"aversion to the hospital".

Franklin (1978) investigated the factors affecting

exercise adherence in fitness programs for both healthy

adults and patients in rehabilitation programs. Although

the analysis focused primarily on individual physical

characteristics, fitness level, and behavioral regimens,

motivation was mentioned as a main personal factor to be

addressed. Franklin's suggested solutions to motivational

deficits focused on the structure and form of the exercise

itself rather than directly on psychological factors.

Program features associated with dropout were lack of

encouragement for clients, client injuries incurred while

participating, individual participation versus group

programs, inadequate instruction, and absence of regular

updating of clients on progress made. Other client

features cited as factors were presence of support from

spouse or peers and a convenient time schedule for

involvement in exercise.

A prospective study that followed 106 subjects for a

total of six months was conducted by Gale, Eckhoff, Mogel,

and Rodnick (1984) to determine factors that could be

associated with exercise adherence. Many measures were








taken of physiological characteristics, self-motivation,

demographic descriptors, health related behaviors, and

previous involvement in exercise. Subjects were healthy

adult men and women; 18% dropped out before attending 10%

of the classes, 40% attended between 10 and 40% of the

classes, and 42% attended more than half the classes.

Factors were examined for correlation to adherence.

Findings were disappointing given the array of

related factors that were examined. Only one of the

factors (marital status) was significantly correlated with

adherence to the program of exercise, and the two factors

with the highest predictive value were the number of years

in present occupation and number of years at present

address. Indicators of less stability of overall life were

associated with early dropout; features such as being

single or being only a couple of years at present address

or job. The other variables that distinguished between

categories were self-motivation and number of children.

Discussing the puzzling results, the authors speculate

that the dropouts in their study may have continued to

exercise away from the program, or that they may have not

found the program to be engaging or challenging enough.

Investigations attempting to identify specific

personal factors affecting adherence to exercise sometimes

yield results in unexpected directions. An example is

research cited above by Dishman, Ickes, and Morgan, (1980)







to verify the concept of self-motivation as an explanatory

mechanism for differential outcomes for people beginning

exercise regimens. Their findings found their construct of

self-motivation to be significantly associated with

adherence to an exercise program; it also found the most

important factor affecting adherence to be percentage of

body fat. The higher the percentage of fat (and the

greater the weight) the more likely the person was to drop

out of the exercise program. Although self-motivation was

one of the three factors that reached significance in

distinguishing between adherers and dropouts, this finding

illustrates the way in which many different--and sometimes

unexpectedly prominent--biopsychosocial variables affect

behavior.

As an aside in surveying factors affecting

adherence/compliance, Dishman (1982) notes the importance

of taking into account those who may drop out of the

formal exercise program under study, but continue to

exercise on their own or in another program. Dishman also

cautions against losing research information by

dichotomizing the population into adherers and dropouts,

to the exclusion of the large class that does succeed in

participating in an alternative pattern of exercise.

In the above pair of studies Dishman, Ickes, and

Morgan, (1980) and Dishman and Gettman (1980) advanced the

concept of self-motivation as an explanation for

differential outcomes in people beginning exercise








regimens. They dismiss the role of attitudes or beliefs,

positing a weak or absent relationship. Godin and Shepard

(1986) have responded with the observation that the

problem may lie with the method. They reply to Dishman and

Gettman (1980) with the assertion that the need is for

theory-driven research to test models, versus the

"shotgun" approach of associating variables with outcomes

and claiming some degree of relationship. For them the

questions to ask are "when" and "how": when is there a

relationship between attitude and behavior, and how is the

effect of an attitude on behavior mediated? Sonstroem

(1982), acknowledges the utility of self motivation, but

notes that its classification as a trait places it outside

the area targeted by research into modifiable

psychological factors. As will be seen below, many

theorists working with the Health Belief Model believe

motivation is determined by the constellation of beliefs

held by persons in relation to certain pivotal areas of

their lives.

Powell (1988) summarizes factors affecting exercise

adoption in table form, collecting together potential

"determinants of physical activity" as an illustration of

the scope of the problem facing those seeking to identify

the specific factors having an impact on adherence to

exercise. The determinants come from a compilation of past

research done to identify the most important and most







salient influences on an exercise adoption effort.

Although research results in the exercise adoption area

are far from conclusive, the list of factors is

instructive:

Personal characteristics--Past program participation;
past extraprogram activity; school athletics, 1
sport; school athletics, >1 sport; blue collar
occupation; smoking; overweight; high risk of
coronary heart disease; type A behavior; health,
exercise knowledge; attitudes; enjoyment of activity;
perceived health; mood disturbance; education; age;
expect personal health benefit; self-efficacy for
exercise; intention to adhere; perceived physical
competence; self-motivation; evaluating costs and
benefit; behavioral skills.
Environmental characteristics--Spouse support;
perceived available time; access to facilities;
disruptions in routine; social reinforcement (staff,
exercise partner); family influence; peer influence;
physical influences; cost; medical screening;
climate; incentives.
Activity characteristics--Activity intensity;
perceived discomfort. (Powell, 1988, p. 27)

Powell's list bears some striking similarities to a

similar group of factors identified as having an impact on

treatment adherence behavior (Meichenbaum & Turk, 1987).

Many of the above findings on adherence to exercise may

also be found in their assemblage of factors affecting

compliance with treatment regimens. Powell's list is a

good tool for guiding research on exercise adoption, in

that it reminds the researcher of potential limitations to

the conclusions drawn from research on any one variable.

Given this caveat, another finding that may be noted is

the number of items on the list that will have








representation in some form in a Health Belief Model

investigation targeted on exercise behavior.

The Health Belief Model and Its Role
in Behavioral Research

The Health Belief Model was developed in the early

1950s in an attempt to understand individual differences

in the practice of preventive health behaviors, first in

regard to asymptomatic diseases, later in an expanding

number of disease states, venues, and situations. The

roots of the Health Belief Model lie in social psychology,

specifically the work of Lewin (1935). Rosenstock (1974a)

identifies the main orientation of the early researchers

as phenomenological, centered on the world of the

perceiver as opposed to the actual physical world. It was

this foundation that led to the formulation of a model

detailing different personal "fields" that were believed

to affect subsequent motivation and thus behavior.

In an explication of the function of personal fields,

Rosenstock (1974a) puts the origin of motivation as toward

positive fields and away from negative ones. Persons

operating within these fields would thus move away from

those areas of their lives that were perceived as negative

and toward those parts that were valued as positive. The

components of the model represent a conceptualization of

the fields likely to be identified as affecting decisions

about behavior having an impact on health.








In one of the earlier theoretical writings detailing

the roots of the Health Belief Model, Suchman (1970)

elaborated on the role of perception and interpretation in

the etiology of illness. He notes, "People do not perceive

the world as it actually is but as they have become

accustomed to perceive it" (p. 107). In his

conceptualization of the motivation to change behavior,

the facts matter less than one's perceptions in making

choices.

Three levels of influence guide the perceptual

process in Suchman's view of individual and social

behavior: the anthropological/cultural, the

sociological/group, and the psychological/individual. Each

level shapes the resultant attitudes and beliefs, thus the

behavior. "Motivation to change one's health practices

depends, to a large extent, upon the individual's feelings

of personal vulnerability and the seriousness with which

he views the health hazard." (Suchman, 1970, p. 109-110).

It is thus possible to see the scope of the challenge if

one thinks in terms of behavior change interventions, as

the focus is not just factual information but the

particular beliefs the individual has about the world.

Becker, Maiman, Kirscht, Haefner, & Drachman (1977)

argue that the Health Belief Model is based on a

"value-expectancy" approach, wherein behavior is

predictable if one knows an individual's valuation of an







outcome and their expectation that a specific action will

result in that outcome. Characteristics the authors deem

relevant to the formulation of a model utilizing health

beliefs include 1) the motivation to avoid illness or to

get well; 2) the amount of desire for a specific level of

health; 3) the belief that specific actions will prevent

or moderate illness or disease conditions. The alignment

of components detailed on pages 13 and 14 of Chapter 1 is

the grouping commonly studied in Health Belief Model

research, and were devised to assess the presence and

strength of the above characteristics.

In Ajzen and Fishbein's theory of reasoned action,

(Ajzen & Fishbein, 1977) beliefs are considered the

cognitive component of the attitude. Kirscht (1974)

defines a belief as "any proposition or hypothesis held by

a person, relating any two or more psychological elements

or objects" (p. 456), while attitudes are posited as

collections of beliefs in which there is an evaluative

component. Highlighted more within Health Belief Model

theory is the evaluative, positive-negative association

that the individual has at the belief level. A parallel

can be discerned between the process described in the

Health Belief Model and attitude-behavior relations, with

the outcome, behavior, dependent on collections of

attitudes, in turn made up of beliefs.

The attitude-behavior link has received much

discussion in social psychology, with lack of consensus








about the role of attitudes in determining behavior

(Cooper & Croyle, 1984). Generally accepted are the

assertions by Ajzen and Fishbein, (1977) that the

specificity of correspondence between attitudes and

behavior has a lot to do with the degree of the

relationship between the two. That is, a general attitude

will predict a multiple-act criterion better than a

single-act one, while a specific attitude will predict a

single-act criterion better than a multiple-act one. An

illustration is the comparison between a general attitude

toward health with its resultant health-protective

behaviors and a specific attitude about tooth-brushing and

subsequent brushing behavior. Recent findings bear out

these assertions, with a study using a measure of general

attitudes and multiple acts showing a high degree of

correspondence between the two (Turk, Rudy, & Salovey,

1984).

Rosenstock (1974b) documents the first application of

the Health Belief Model as a study by Hochbaum in 1952

that attempted to identify factors underlying the decision

to obtain a chest X-ray for the detection of tuberculosis.

This study assessed specific beliefs about the disease of

tuberculosis and related them to the decision to seek an

X-ray as a mechanism for detection of the disease. Two

specific beliefs were measured, one detailing the

respondent's belief that they were susceptible to







tuberculosis, the other their belief in the overall

benefits of early detection. Those having both beliefs

were four times as likely to have received a chest X-ray

during a specified period as those who had neither belief.

These findings spurred much subsequent research and the

delineation of a full model for the organization and

identification of individual beliefs.

It was not until the mid-seventies that the structure

of the Health Belief Model had stabilized into the form

that it has retained to the present. By then it had gained

currency as a tool for explaining health behavior, with a

review of applications of the model finding a durable

pattern to the results of initial investigations (Becker &

Maiman, 1975). Examining the testing of the Health Belief

Model components, the authors found that the relevant

beliefs reliably correlated with behavior. The perceived

level of susceptibility was found to correlate positively

with the performance of health behavior, which is defined

as any action taken by an individual who perceives himself

to be healthy in order to prevent the occurrence of

disease or detect it in and asymptomatic stage (Kasl &

Cobb, 1966). Behaviors ranged from cancer screening to

obtaining immunizations to dental visits.

The perceived severity of the conditions to which the

individual feels vulnerable was found to have a weak

relationship in early reviews of research (Kirscht, 1974;

Becker & Maiman, 1975), with some studies finding that a








higher degree of perceived severity predicts participation

in dental care, responding to disease symptoms, and

working to prevent accidents. No significant correlation

of perceived severity with target behaviors was found in

many of the other studies, but the authors of the main

review (Becker & Maiman, 1975) saw the component as

contributing valuable information to the overall

predictive value of the model.

The elements of the model found to have the greatest

correlation with behavior in these early reviews were the

perceived benefits of the health protective behavior being

researched and the perceived barriers to or costs of

performing that behavior. For the benefits construct,

positive, statistically significant correlations were

usually found between perceived efficacy of a preventive

health action and the performance of that action,

including obtaining immunizations, getting screening for

cancer and tuberculosis, and seeking prophylactic dental

visits (Becker & Maiman, 1975). Similarly, barriers/costs

were found to be inversely associated with involvement in

preventive behaviors. Barriers identified as likely to

interfere with carrying out behaviors were monetary cost,

complexity of the regimen, side effects, degree of change

needed, and accessibility of facilities. The health

motivation component of the Health Belief Model was








proposed in 1975 (Becker & Maiman, 1975); results of later

investigations will be reported below.

A survey of research utilizing the Health Belief

Model found sufficient evidence to uphold the components

as distinct, separate areas of beliefs and as having

significant correlation to many differing areas of

behavior (Becker, Haefner, et al., 1977). This survey

systematically examined each study for evidence of

significant associations between qualities assessed by the

components and subsequent behavior in both the preventive

and sick-role realms. Both the preventive behavior studies

and the sick-role studies used prospective and

retrospective designs.

A total of twelve preventive behavior studies were

evaluated. The behaviors being examined included seeking

dental visits, getting Pap tests, getting polio

vaccinations, getting examinations for a number of

different potentially harmful conditions, and getting

screened for Tay-Sachs disease. The authors noted the

number of studies that reported results for each component

of the model, allowing construction of a "significance

ratio". This ratio compared the number of times a

significant correlation of beliefs with behavior was found

with the number of times it was tested, with significance

set at the .05 level. For perceived susceptibility, the

ratio was 9 out of 10; perceived severity, 6 out of 8.








With the constructs of perceived benefits and barriers,

the ratios were 6 out of 9 and 3 out of 4, respectively.

Seven sick-role studies were charted in the same

manner, showing that each reported result achieved

significance for the four components. The behavior focus

in these studies was primarily penicillin prophylaxis or

regimens recommended as a result of findings of disease,

with one study investigating use of followup care after a

negative health finding. Perceived susceptibility was

examined in three of the studies, with perceived severity

targeted in four. For perceived benefits the number was

four, and perceived barriers, one (Becker, Haefner, et

al., 1977).

A research team performed a study assessing Health

Belief Model component beliefs specific to compliance

issues, in an attempt to explain the different responses

of low income mothers of children with otitis media

(Becker, Drachman, & Kirscht, 1974) Their work was

successful in differentiating compliers with medical

regimens from non-compliers, as measured by a complex

behavioral protocol. The study was intended as an initial

step in a program to improve compliance through changing

health beliefs. While the composite model was found to be

a better predictor, their conclusions stated the aim of

such research in behavioral change "Thus, by knowing which

model components are below a level presumed necessary for







compliance, the health worker may be able to tailor

intervention to suit the needs of the individual."

(Becker, Drachman, & Kirscht, 1974, p. 215). Although the

focus in the current study is on self-initiated changes as

opposed to compliance, the mechanism of action of beliefs

upon behavior was expected to be the same.

Cues to action, a belief construct that was part of

the original formulation of the Health Belief Model, has

proven to be difficult to research. Cues are hypothesized

as stimuli or events that trigger the individual to act

once the other model components have provided the

motivation and direction of the action. Cues may be

internal, such as perceptions of bodily state, or

external, encompassing many different kinds of messages

from media or significant others. Health Belief Model

researchers had early general agreement about their

importance to the outcome of a behavioral intention.

After some attempts to identify salient cues in

investigations of Health Belief Model factors, the

conclusion reached by one of the originators of the

component was that most settings preclude obtaining an

adequate measure of the contribution of this variable to

behavioral outcomes (Rosenstock, 1974a). Without some way

of recording the cues as they occur in the life of each

subject, (e.g. chest pain, or a public health poster about

the need to seek vaccinations) too much is lost when

asking for recall of relevant, possibly related cues. This









construct quickly faded from the Health Belief Model

research method. With the development of new tools and

methods for adequate measurement of cues in future

researches, the variable may well be revived as a relevant

part of the Health Belief Model.

When Health Belief Model components were compared to

other explanatory models of health behavior, many of the

common elements among the models turned out be wholly or

in greater part contained within Health Belief Model

factors (Cummings, Becker, & Maile, 1980). The six

subsuming factors found to be organizing elements for the

theories examined in the study were: 1) accessibility to

health care, 2) evaluation of health care, 3) perception

of symptoms and threat of disease, 4) social network

characteristics, 5) knowledge about disease, and 6)

demographic characteristics. Thus the Health Belief Model

has links with the breadth of health behavior research,

with the only major omission of the model being a part

that explicitly addresses social network characteristics.

In that category, it appears that descriptors of such

characteristics would fit in the benefits component of the

model.

Studies incorporating the Health Belief Model have

proliferated following the initial evaluative research of

the seventies (e.g. Cummings, Jette, & Rosenstock, 1978)

with many different applications developed and







investigated. Although the methods used became more

sophisticated, the tendency for each researcher to use

instruments specific to their own studies continued. This

practice resulted in refinement of statistical technique

to be applied in this kind of research, but made

comparative conclusions difficult because of the

differences between instruments or constructs. This trend

has been bemoaned by researchers centrally involved with

the Health Belief Model, (Janz & Becker, 1984) but the

pattern continues even in the most recent research.

A major shift has occurred in the area of application

of the Health Belief Model, toward investigating

preventive behaviors and with a corresponding lessening of

concern with sick-role behaviors. The first use of the

methodology in connection with exercise was in 1980

(Riddle, 1980), with most intervention studies using the

Health Belief Model having been performed primarily in the

past decade. A close examination of them follows.

Illustrating the durability and continued utility of

the Health Belief Model methodology is a study by Chen and

Tatsuoka (1984) that measured the impact of beliefs on

preventive dental behavior. Preventive dental behavior

includes dental visits, brushing, and flossing of teeth.

Patterned after early, similar research, the study used

canonical correlation, a measure of association especially

appropriate for evaluating the degree of contribution the

Health Belief Model components make in predicting








different preventive dental behaviors. Conducted using 685

married Caucasian women as subjects, the study assessed

beliefs and behavior simultaneously in a cross-sectional

design, using a questionnaire format. Overall success or

failure to engage in preventive dental health behavior was

significantly related to health beliefs (rc=0.436,

P < 0.001). Among the separate Health Belief Model

components, the ones having the greatest predictive value

with preventive dental behavior, as measured by structure

coefficients, were perception of barriers and perception

of benefits. Another element highly predictive of behavior

was a construct examined in the study by Chen and Tatsuoka

(1984), perception of salience of beliefs. Much lower

coefficients were obtained for perception of

susceptibility and perception of severity.

The study by Chen and Tatsuoka (1984) is

representative of the method and general findings in

modern Health Belief Model research. The perceived

barriers component appears to be the construct of the

Health Belief Model holding the strongest association with

preventive behavior, as measured by findings of

significance in Health Belief Model investigations (Janz &

Becker, 1984). General findings differ from the dental

study in that perceived susceptibility was the second

strongest association overall, with perceived benefits

third.









One of the limitations of the Health Belief Model has

been that a causal relationship between beliefs and

subsequent behavior has been difficult to establish

(Cummings, Becker, & Maile 1980). This difficulty arises

from the need to apply the theory using knowledge about

the population, about the setting, and about the specific

behavior under investigation. Isolating the relationship

of a particular personal feature such as beliefs to a

behavioral outcome is made difficult by natural limits on

the amount of information obtainable about

person-environment interactions. Thus, statements about

the variables examined in Health Belief Model

investigations have typically been couched in terms of

correlations and coefficients, with some few studies able

to draw limited conclusions about causality based on

controlled interventions.

The most comprehensive assessment of Health Belief

Model research that has been performed since the model was

organized as a foundation for investigating health

behavior was that of Janz and Becker (1984). The authors

note many empirical findings supporting the ability of all

the model components to achieve significance as

explanatory and predictive mechanisms. Even the component

of the model found to be suspect in its utility in earlier

reviews, that of perceived severity, was upheld as a valid

and reliable measure throughout its many contexts of








application. As a model, the Health Belief Model has shown

more activity and corroboration than any other model

addressing health-related behavior. Within this framework,

assessing the role of beliefs in mediating or determining

health behavior has been a primarily retrospective,

cross-sectional undertaking.

Researchers' limited resources continue to hinder

studies thorough enough to enable firmly ruling out

competing or confounding explanations with some of the

model components, but a solid base for ongoing research

and applications within the health professions has been

established. Longitudinal studies that would allow firmer

statements about causality are costly, with few occurring

in such beliefs research. Prospective studies that have

been performed have shown levels of significance

comparable to retrospective studies, showing promise for

this method of research on the Health Belief Model (Janz &

Becker, 1984).

Experimental studies based on the Health Belief Model

have shown the impact of health beliefs on behavior to be

a useful, potent phenomenon in behavior change

manipulations. Interventions using Health Belief Model

components as a basis for determining the degree of change

in beliefs have met with success. Using beliefs change as

the mechanism to change certain target health behaviors,









researchers have documented subsequent differences in the

level of the target behavior.

In a study investigating the effect of health threat

communications on preventive dental behavior, Beck and

Lund (1981), assigned subjects to four groups. Each group

got an educational slide show about peridontal gum disease

with a stated level of susceptibility to the disease (high

or low) and the alleged severity of the disease if it were

to occur (again high or low). This assignment process

formed four cells of different combinations of

communications, allowing the experimenters to assess the

impact on subsequent beliefs, flossing intentions, and

flossing behavior. Patients who had a higher level of

perceived seriousness of gum disease as a result of

viewing the communication subsequently increased in their

intention to floss as well as their actual frequency of

flossing, showing significant differences from the low

perceived seriousness group. Patients with high

susceptibility were more likely to floss more often,

though the differences were not significant.

Other investigations have demonstrated the efficacy

of interventions designed to affect peoples' health

beliefs and thus behavior. A major review study about

research on the modification of beliefs and thus behaviors

(Kirscht, 1974) found many efforts to utilize the

situational and behavioral specificity of the Health








Belief Model in devising experimental regimens. Most of

the studies reviewed used communications to heighten

threat or arouse fear on the part of the recipient, based

on the premise that the resulting higher degree of

perceived severity or perceived susceptibility would

result in a greater likelihood that the behavior would

change as a result. Results were complex, as might be

expected in a multivariate model, but generally supported

both the Health Belief Model and the effectiveness of the

change regimens. Important mediating effects found to have

an impact on the results were the presence of a response

option perceived as effective in reducing the threat and

other beliefs about the new behavior.

In a test of the effects of interventions targeted on

behavior change, Becker, Maiman, Kirscht, Haefner, and

Drachman (1977) performed a study in which mothers of

overweight children were exposed to fear-arousing

communications based on Health Belief Model dimensions.

Measures of subsequent appointment-keeping and children'

weight loss showed both significant independent effects of

the fear-arousing messages and significant correlations of

the Health Belief Model variables with the behaviors. This

experiment demonstrated the usefulness of the Health

Belief Model as a whole through several multiple

regressions, along with demonstrating that the influence









of the fear-arousing messages was independent of the

impact of beliefs.

Kirscht (1983) reports mixed results later from

Health Belief Model investigations utilizing belief-change

interventions. An outcome of adoption of the target

behavior depended, generally, on the simultaneous presence

of perceived susceptibility and severity, and on the

behavior in question being perceived as beneficial and

with few accompanying barriers or costs. Thus, the

employment of the Health Belief Model in devising

strategies for behavior change through persuasive

communications requires the recognition that all the

components play a role in the final outcome. A narrow

focus utilizing only one component is susceptible to

misapplication and misinterpretation of the results. When

correctly utilized and with an appreciation for

uncontrolled variables, interventions based on the

components of the model appear effective in altering

behavior. Kirscht (1983) cautions that too few studies

exist that have examined long-term changes in behavior for

definitive conclusions to be possible.

Applying the Health Belief Model
to the Exercise Adoption Problem

The Health Belief Model has proven to be a successful

tool for predicting the likelihood and frequency of many

different kinds of preventive health behaviors. Another

potential application receiving increasing research








attention has been in evaluating the effectiveness of

model-based interventions designed to positively affect

personal behavior patterns. A tool for explaining,

predicting, and changing health-related behaviors offers

potential utility in the specific case of aerobic

exercise. The need for mechanisms to support exercise

adoption is easily documented. In a review of exercise

participation, Powell (1988) found that only 9% of the

population in the U.S. exercises at the level necessary to

derive the benefits exercise has to offer.

Current patterns in exercise research show widespread

use of the findings of the American College of Sports

Medicine (1978) on the minimum level of exercise necessary

to develop and maintain fitness. These guidelines specify

the following parameters for exercise quantity and

quality: 1) frequency of training 3-5 days per week, 2)

intensity of training 60%-90% of maximum heart rate

reserve, 3) duration of training 15-60 minutes of

continuous aerobic activity, with duration dependent on

intensity, and 4) a mode of activity that involves large

muscle groups, that can be maintained continuously, and is

rhythmical and aerobic in nature (American College of

Sports Medicine, 1978, p. vii). Given the almost universal

employment of all or parts of these guidelines in fitness

programs and in evaluative research, the current study was

formulated to examine the association of Health Belief







Model variables with exercise conforming to the American

College of Sports Medicine parameters.

With a 50% dropout from aerobic exercise programs at

six months (Dishman & Gettman, 1980), clearly a reliable

regimen for assisting exercise adoption would play a

useful role in such programs. The utility of such a

program would apply whether the target was an individual

or a group, whether the exercise adoption goal was

self-motivated or prescribed. The development of such a

regimen is dependent on adequate knowledge of what changes

are being attempted. Dishman (1988) has observed, "one

barrier to implementing public health promotions of

exercise as well as uniform interventions in exercise

programs is the absence of a consensus over the methods

that might be effectively employed and the exercise

determinants to be targeted" (p. 2). Research on exercise

adoption must contain attempts to identify the key

determinants and begin to apply them in experimental

trials to determine their utility in effecting change.

Hughes (1984) cites the need for more research to

identify relevant characteristics of individual exercisers

and to identify the best method to prescribe exercise as

treatment. Such a base of knowledge is needed to develop

the method for prescribing exercise as well as the best

ways of insuring positive outcomes once the program has

been undertaken. The need to take into account individual

factors affecting exercise adoption, and the challenge









therein, was cited in discussion of a recent attempt to

isolate factors influencing exercise adherence (Gale,

Eckhoff, Mogel, & Rodnick, 1984). The authors noted the

complexity and the difficulty in distinguishing different

individual characteristics while controlling for other

factors, observing that the phenomenon of adherence is

likely the product of interaction between personal and

program characteristics. Along with many other writers in

the exercise adoption area, they cite the need for much

more research in this area before a reliable program for

change can be developed.

As regards exercise and other forms of preventive

health behavior, calls for more research on social and

psychological predictors of health-related behavior have

appeared in different quarters, emphasizing the paucity of

experimental research that could provide the foundation

for programs of change (McAlister, Farquhar, Thoresen, &

Maccoby, 1976; Becker, Haefner, et al. 1977). For the

example of aerobic exercise, additional steps are needed

to identify specific beliefs (and the degree to which each

are held) that are associated with successful and

unsuccessful attempts at exercise adoption. A reliable

method for determining relevant beliefs would provide for

the development of effective psycho-educational and belief

change regimens to augment the known precursors of

behavioral change.









An antecedent of the current interest in the possible

contributions of the Health Belief Model to the

explanation of and support of exercise adoption behavior

was contained in an earlier discussion of the mechanisms

of the model:

Surely, the exercise and dietary mania observed
over the last decade represent behaviors that could
be regarded as striving toward improved health, but
it is just as easy to explain them (insofar as they
are health related at all) as behavior undertaken to
avoid a deleterious situation. Again, there are
individuals who exercise and engage in other health
actions having health implications but who do so for
reasons quite unrelated to health, perhaps for
aesthetic reasons or for the sheer exhilaration felt
by many by the performance of physical work. Again,
the question of whether the avoidance orientation in
the Health Belief Model is adequate to account for
the so-called positive health actions taken by people
remains unresolved.
(Rosenstock, 1974a, p. 335)

Although written some time ago, the uncertainty voiced in

the discussion remains today, with only a few exploratory

efforts having been undertaken to answer the questions

raised. Such research serves as the foundation and

guidance for specifying elements of the present study.

Reviewers of recent research have verified the

relationship of beliefs and attitudes to intentions to

exercise and the exercise behavior itself (Godin &

Shepard, 1986). In examining research up to now in the

area of exercise behavior, Godin and Shepard support the

theory of Ajzen and Fishbein (1977), noting that recent

attitude-behavior research has already proceeded from "is"

questions (Is there an effect?) to "when" and "how"








questions. The second brace of questions, when answered,

will provide information about when there is a relation

between attitude and behavior plus how the effect of

attitudes on behavior is mediated. Godin and Shepard

(1986) lobby for the application of theory to this problem

as opposed to the "shotgun" approach of trying out

variables in varying combinations.

The authors who have stimulated much of the recent

interest and activity in attitude-behavior work did so by

distilling and thematizing much of the research that had

occurred up to the time of their extensive review (Ajzen &

Fishbein, 1977). Of particular interest was the finding,

cited above (pp. 53-54), about the patterns of

correspondence between attitudes and behavior. The result

has been studies that test the relationship in specific,

particular instances of behavior as well as the more

global, broad questions. Exercise provides the opportunity

for both kinds of research, from the likelihood of doing a

particular form of exercise at a particular time to

general adherence over time.

Riddle (1980) devised a test of attitude-behavior

relations for a particular form of exercise--jogging--and

utilizing one of the main models of the relationship

between attitudes and behavior. Choosing Fishbein's

Behavioral Intention Model, she developed a beliefs

measure using an elicitation technique that resulted in a







68 item measure. With the criterion behavior identified as

regular jogging, the survey assessed behavioral intention,

attitude toward behavior, attitude toward the object,

subjective norms for behavior, motivation to comply,

consequences of behavior, and evaluation of the

consequences. The focus of the study was on testing the

validity of the Behavioral Intention Model, but clearly

the Health Belief Model methodology served as a guide in

the construction of the beliefs items on the survey. The

survey was administered to 369 men and women of age 30 and

over, with 296 usable surveys received. Joggers numbered

149, non-exercisers totalled 147.

Results of the research, confirmatory of the

Behavioral Intention Model, also showed marked belief

differences between joggers and non-exercisers. Riddle

(1980) documented differences between joggers and

non-exercisers on beliefs corresponding to two Health

Belief Model dimensions, perceived benefits and perceived

barriers. On 17 of the 19 belief scales, differences

between joggers and non-exercisers on the

benefits/barriers items were significant at the p < .001

level. The items were structured as follows: "Taking part

in regular jogging in the next two weeks would...".

Examples of the items showing significant differences are:

"make me feel too tired," "take too much time," "make me

feel good mentally," "make me have a fatal heart

attack/stroke." Beliefs about the consequences of exercise








in the form of regular jogging accounted for much more of

the variance than did evaluation of the consequences.

Joggers had strong beliefs about the positive consequences

of jogging, while nonexercisers had neutral beliefs about

the positive and negative consequences. Joggers thought

regular jogging would benefit their physical and mental

health, while non-exercisers thought it would require too

much time and discipline and make them too tired.

In another study utilizing techniques suggested by

Fishbein's Behavioral Intention Model, Slenker, Price,

Roberts, and Jurs (1984) established a promising

precedent for the employment of the Health Belief Model

with regard to predicting aerobic exercise adoption. Their

investigation applied the model in a specific exercise

situation, that of jogging. An instrument was developed

and validated for purposes of measurement of beliefs

specific to expectations about jogging, for the five

customary belief areas examined in Health Belief Model

research: perceived benefits, perceived barriers,

perceived susceptibility to disease, perceived severity of

possible disease conditions, and general health

motivation. Other variables under investigation were also

part of the instrument, including knowledge about jogging,

complexity of jogging, cues, and health locus of control.

The completed instrument was administered to 40 joggers

and 39 nonexercisers.








A composite regression analysis of Health Belief

Model variables that included one other variable accounted

for 56% of the variance in jogging behavior. The Health

Belief Model variables of perceived benefits, perceived

barriers, and general health motivation comprised a

multiple R of .707, or 50% of the total variance. The

single variable perceived barriers accounted for 40% of

the variance. The composite figure was a strong

performance of the Health Belief Model variables in

explaining exercise behavior. Given the careful instrument

development and sound statistical analysis, the finding is

one of the most impressive performances of a Health Belief

Model-based instrument for any study examined. Using a

discriminant analysis procedure, 92 percent of the

subjects were correctly assigned to their proper category

of jogger or nonexerciser based on the independent Health

Belief Model variables assessed.

Similar methods with an adolescent population yielded

more equivocal results. The predictive measures produced

more modest percentages of correct classification and the

amount of variance accounted for by the measure employed

for the study was also less (O'Connell, Price, Roberts,

Jurs, & McKinley, 1985). Performed on a sample of 69 obese

and 100 nonobese high school freshmen and sophomores, the

study used the beliefs measures to predict status of obese

or nonobese and to predict membership as an exerciser or a







nonexerciser. The beliefs assessed differed from the study

performed by Slenker, Price, Roberts, and Jurs (1984) in

that measures of social approval for dieting and exercise

were added, along with cues for the behavior in question

(dieting or exercise). General health motivation was not

assessed, while the other Health Belief Model

variables--susceptibility, severity, barriers, and

benefits--remained. Each of the four variables also

obtained a measure of each of the subject's beliefs about

the behaviors of diet and exercise.

For obesity, the independent variables employed in

the study correctly classified 69% of the subjects as

obese or nonobese in a discriminant analysis procedure.

The authors observe that obesity is not a behavior,

identifying a likely reason for the relatively poor

performance of their predictors. When employed to classify

dieters versus nondieters, 83% of the subjects were

correctly classified. When the discriminant analysis

procedure was applied to exercisers versus nonexercisers,

75% of the overall classifications were correct.

The amount of variance accounted for by the

independent variables in the case of dieting behavior for

obese and nonobese adolescents was 23% and 19%,

respectively. For exercise behavior, 14% of the variance

was explained for obese subjects, while none of the

variables emerged as significant in predicting exercise

behavior for the nonobese subjects. These weak findings in








the application of the Health Belief Model to diet and

exercise behavior are noted by the authors as an indicator

that age may be an important factor in assessing health

behaviors using the Health Belief Model. Such an

observation is supported by Weinstein (1984), who found

that college students have an unrealistically low

assessment of their susceptibility to health problems and

accidents.

A study undertaken to determine the relationship of

Health Belief Model components to compliance with an

exercise prescription found that the beliefs of coronary

bypass patients played a role in subsequent adherence to a

walking exercise regimen (Tirrell & Hart, 1980). Five

standard Health Belief Model components were assessed,

perceived benefits, perceived barriers, perceived

susceptibility, perceived severity, and general health

motivation. Using a somewhat abbreviated measure

consisting of 19 items, the researchers found that two of

the components had significant correlations with compliant

behavior, perceived barriers and perceived susceptibility.

The correlation of the barriers measure with participation

in the "heart walk" regimen was 0.64; with the

susceptibility component the correlation was 0.35. The

highest degree of significance was achieved with the

perceived barriers component, which was significant at the








p < .001 level; perceived susceptibility was significant

at the p < .05 level of significance.

In a study designed to relate two theories of

behavior change, Sonstroem (1987) provides more

verification of the role of beliefs in behavior change.

Based on Ajzen and Fishbein's Theory of Reasoned Action

(1977), the study examined belief statements of subjects

with the aim of differentiating between various stages of

change as detailed by Prochaska and DiClemente (1983).

While the study did not explicitly base the beliefs survey

utilized on the Health Belief Model, the categories of

beliefs that emerged from the analysis were coincident

with the categories utilized in most Health Belief Model

studies.

A background questionnaire determined the exercise

status of each subject, allowing them to be assigned a

category precontemplationn, contemplation, action,

maintenance, relapse) in the Prochaska and DiClemente

stage schema. Two hundred fourteen respondents were asked

to react to belief statements that had been supplied by

exercise leaders at various exercise programs. Likert

items providing a graded response accompanied each belief

statement. Each statement had the root "My participation

in a regular program of exercise would:" followed by the

statement. Examples of the belief statements are: "help me

in controlling my weight"; "increase my cardiovascular







endurance"; "be boring". Principal component analysis on

the resulting responses yielded seven usable components,

labeled Benefits, Barriers, Novelty Outlet, Social Outlet,

Fear, Appearance, and Psychological Gain.

A stepwise discriminant function analysis utilizing

the belief findings as a base was constructed to classify

the expected Prochaska and DiClemente category for the

precontemplation, contemplation, action, and maintenance

stages. Mean item responses were computed for each subject

for each component, which were then standardized to mean

of 50 with a standard deviation of 10. Two functions which

accounted for 99.99% of the total Eigen values resulted.

The three components which entered the equation were

Barriers, Benefits, and Psychological Gain. For the two

functions constructed, 60% and 55% of the categories were

correctly identified when compared to the subjects' actual

status. For research of this type, the percentage of

subjects correctly assigned was relatively low. Sonstroem

(1987) cites a small sample size in some of the stage

categories as a limitation, along with limitations in

instrument development.

A survey of research investigating the utility of the

Health Belief Model quickly reveals that almost as many

different instruments exist as do studies! While there are

many idiosyncratic measures that have been employed in

beliefs research, there are many parallels between

studies, and a consensual choice of method. A consistent








call in reviews of Health Belief Model research, however,

is for a standardization of instruments and, where

possible, in methods. Little Health Belief Model research

is designed to replicate or refine earlier findings, nor

are the positive findings that result later employed to

design interventions that may provide for support of

individuals attempting behavior change programs.

Support for the reliability and validity of properly

designed and administered instruments has recently

emerged, documenting that such research tools surpass

minimum requirements for such measures. A number of

studies examining appropriate techniques for constituting

and evaluating measures of health beliefs have validated

the different beliefs posited for the Health Belief Model

as discrete categories that do not overlap. Construct

validity for the commonly researched components of the

model has been consistently demonstrated, with compelling

statistical evidence supporting the independence of the

constructs (Maiman, Becker, Kirscht, Haefner, & Drachman,

1977; Cummings, Jette, & Rosenstock, 1978; Jette,

Cummings, Brock, Phelps, & Naessens, 1981; Given, Given,

Gallin, & Condon, 1983; Champion, 1984). The utility of

the combined components of the model in predicting and

explaining behavior has already been noted above. An

important byproduct of this research activity has been the








development of an item pool where the elements have been

found to be valid and reliable.

The most complete test of a single Health Belief

Model instrument intended for use in the measurement

process was performed by Champion (1984). Designed to

verify the validity of scales for use in predicting breast

self-examination behavior, the investigation subjected

each scale to an internal consistency examination, a

test-retest reliability assessment, a test of exclusivity

for each scale, and an overall measure of construct

validity as demonstrated by the performance of the

instrument in predicting breast self-examination behavior.

The scales examined included perceived benefits of and

barriers to performing breast self-examinations, perceived

susceptibility to disease, perceived severity of possible

disease conditions, and general health motivation. The

final scales used in statistical analysis had between five

and twelve items each. The instrument was administered to

301 women of varied ages, education, ethnicity and

socioeconomic status.

The five scales had internal consistency reliability

coefficients (as determined by computing a Cronbach's

Alpha for each scale) ranging from 0.60 to 0.78. Three of

the scales had coefficients of 0.76 or higher:

susceptibility, severity, and barriers. When test-retest

reliabilities were calculated, all the scales except







benefits exhibited coefficients of 0.76 or higher. The

author observes that the testing process may have

sensitized subjects to the benefits of breast

self-examination, making for lower, but still significant,

test-retest reliability.

A principal component analysis utilizing orthogonal

rotation with a varimax criterion showed the five scales

to be mutually exclusive, with only one of the resulting

factors having items from more than one of the scales. The

severity scale lacked unidimensionality, with distribution

of the items from that scale across three factors

resulting. When scale scores were used to predict breast

self-examination behavior, a multiple R of 0.51 was

obtained, accounting for 26% of the variance. The barriers

scale accounted for the largest portion of the variance,

with health motivation second. The remaining three

variables did not account for a significant portion of the

variance.

Champion (1984) saw the resulting instrument as a

good basis for application with other behaviors,

concluding that the method and the model are of sufficient

validity for application in many areas. The study

represents an important advance in Health Belief Model

methodology, providing a useful framework and point of

departure in developing a standard procedure for beliefs

assessment. Champion assigned importance to the strategy

of utilizing previously researched items as a mechanism








for standardizing research results. Evaluative criteria

generally accepted as standards in test construction but

seldom employed in Health Belief Model investigations are

also important elements of the study.

Other studies using similar tests with instruments of

like construction report results of similar magnitude.

Wagner (1983) found that the Cronbach's alpha reliability

coefficients for her Health Belief Model scales ranged

from 0.65 up to 0.91, with all but one of the scales above

0.76. Her scales employed Health Belief Model components

in ways specific to medical applications that assessed the

psychosomatic elements of beliefs and behaviors. Using a

factor analytic approach to evaluate Health Belief Model

components yielded inconclusive results as to the unitary

dimensionality of the usually robust barriers and benefits

scales. This appears to be due to the inclusion of a wide

range of items representing too many different activities

and symptoms.

Another study that also did an evaluative appraisal

of an instrument development effort found distinct

components and moderate reliabilities (Jette, Cummings,

Brock, Phelps, & Naessens, 1981). These results were

achieved despite the use of only a few items in each

scale. A factor analysis yielded a concordance with

existing Health Belief Model constructs of perceived

barriers, perceived severity of disease, and concern for







health. These results are of interest given that they were

noted in a study that primarily investigated behavior

associated with medical regimens. Even without items

intended to measure the Health Belief Model components,

the factors were identified. Examination of the

methodology of instrument construction and use in Health

Belief Model studies led to the conclusion that

"moderately reliable indices of a wide spectrum of health

beliefs can be constructed and replicated across samples."

(Jette, Cummings, Brock, Phelps, & Naessens, 1981, p. 92).

The authors further note that the obstacles to

replicability of results stem from the lack of

standardization of instruments and of sufficient rigor in

the construction of beliefs measures.

The previously cited study by Slenker, Price,

Roberts, and Jurs (1984) (p. 82) also serves as a good

foundation for the present study. It found the Health

Belief Model to be both valid and reliable in the specific

exercise application of jogging. As with the Champion

(1984) study, measures of internal consistency and

construct validity were applied. The five Health Belief

Model scales of perceived benefits of jogging, perceived

barriers to jogging, perceived susceptibility to disease,

perceived severity of possible disease conditions, and

general health motivation achieved KR-20 reliability

coefficients of 0.83 or greater with the exception of

general health motivation, which has a coefficient of









0.57. Given that the KR-20 procedure is intended for

dichotomous variables, it is unclear what a more

appropriate analysis would yield in evaluating the

components. Factor analysis employing an orthogonal

varimax rotation revealed the five constructs to be

distinct factors.

Of the possible survey/questionnaire mechanisms for

obtaining an accurate measure of an individual's beliefs,

the most frequently used method in Health Belief Model

research has been the Likert scale. The seven-point Likert

method of assessing beliefs has been found to have

convergent validity with interview and multiple choice

methods of assessment, two other popular assessment

strategies. Of the methods compared, the Likert method

showed the greatest validity, with zero method effects as

opposed to 10% for both multiple choice and interview

methods (Cummings, Jette, & Rosenstock, 1978). Likert

items have been the assessment method employed in most

Health Belief Model studies, with consistent results.

Lau, Hartman, and Ware (1986), performed a study

examining the impact of health values on certain health

protective behaviors. In a population of university

students, those with higher valuing of health were more

likely to report doing the behaviors, such as seat belt

use, breast self examination, and exercise. Those with

higher health-as-a-value scores were significantly more







likely to have done the behaviors than those with low

scores. Also, the authors cite an increase in

health-as-a-value scores with increasing age within their

subject pool. These values stabilized as students moved

into adult age ranges, at a level still somewhat lower

than in the adult population.

The finding that age is an important factor to be

taken into account in the measurement of beliefs and their

impact on subsequent behavior corroborates a finding cited

above (O'Connell et al., 1985). To avoid confounds in

developing instruments and interventions utilizing the

Health Belief Model, the use of adults of 25 years of age

or older in preliminary studies appears warranted. Age 25

appears to clear by a safe margin the age range where

detectable changes in beliefs are occurring.

Hypotheses

The Health Belief Model has shown a consistent

capacity for prediction with many different kinds of

health behaviors, as well as an ability to account for

significant amounts of the variance in retrospective and

prospective health behavior investigations (Janz & Becker,

1984). The pattern in the choice and application of

instrumentation has been variable, with different methods

adopted according to the particular perceived needs of

each separate research effort. With the recent spate of

research, particularly studies applying the model to the

area of exercise behavior, study design has begun to








stabilize into a well-documented and proven methodology

with a foundation in accepted assessment practice.

Extending Health Belief Model research into the area

of exercise behavior is a step indicated by many other

sick-role and preventive health behavior studies, and

shows good potential utility for the specific example of

general aerobic exercise. No empirically verified,

replicable link has been established between the major

Health Belief Model components and systematically defined,

general aerobic exercise as a dependent variable. No

prospective studies have examined the ongoing impact of

beliefs in this area. The success of intervention

investigations in the area of aerobic exercise depends on

the existence of a reliable, repeatable measurement

instrument that provides a basis for assessment of

effects.

Interaction between beliefs and behavior precludes

absolute statements of causality, but repeated measures

with a proven instrument provides a basis for first steps

in defining the evolution of individual patterns of

behavior. As was observed early in the first burst of

research activity to use the Health Belief Model, "the

hypothesis that behavior is determined by a particular

constellation of beliefs can only be tested adequately

where the beliefs are known to have existed prior to the

behavior that they are supposed to determine" (Rosenstock,








1974b, p. 362). Such findings hang on the existence of a

tool with known characteristics and validity to as

accurately as possible determine belief constellations

specific to the area being researched.

The present study sought to develop and verify the

attributes of just such an instrument, with regard to a

carefully delineated yet general (many different kinds of

exercise) definition of aerobic exercise. Following the

evaluation of the validity, reliability, and exclusivity

of the constructs, a test of the predictive power of the

overall measure over a time period of one month was

attempted.

The following hypotheses were advanced:

1. The five Health Belief Model constructs of
perceived benefits of aerobic exercise, perceived barriers
to aerobic exercise, perceived susceptibility to disease,
perceived severity of possible disease conditions, and
general health motivation, as operationalized by subscales
of the Personal Beliefs Questionnaire, will be found to be
reliable when evaluated by computed internal reliability
coefficients and test-retest statistics.

2. The five Health Belief Model components, as
measured by the Personal Beliefs Questionnaire, will be
found to be valid, independent constructs when assessed by
measures of intercorrelation and factor analysis
statistics.

3. The refined composite of health belief components,
resulting from item analysis of the Personal Beliefs
Questionnaire and utilizing the five belief components
employed in this study, will account for a significant
portion of the variance in classification of self-assigned
aerobic exercise adoption categories.

4. The refined composite of health belief components
from the Personal Beliefs Questionnaire will account for a
significant portion of the variance determining class of
actual activity/exercise participation as measured by
subjects' self-report.





89


5. The refined composite of health belief components
from the Personal Beliefs Questionnaire will successfully
predict membership in subjects' self-assigned categories
of aerobic exercise adoption.

6. The refined composite of health belief components
from the Personal Beliefs Questionnaire will successfully
predict membership in classifications of actual
activity/exercise participation as measured by subjects'
self-report.

7. The refined composite of health belief components
from the Personal Beliefs Questionnaire will successfully
predict self-reported changes in subjects' exercise status
occurring over the period of one month.













CHAPTER 3
METHOD

Subjects

Participants in the study were male and female adult

faculty at a mid-size college in central New Jersey. The

sample was drawn from a pool of all full-time, on-campus

faculty actively teaching during the Spring, 1990

semester. To avoid confounds from maturation effects noted

in past investigations with younger populations,

(O'Connell et al., 1985; Lau et al., 1986), only

individuals over 25 years of age were utilized in the

study. A convenience sample of 334 faculty at the college

was selected from those in the available pool.

Those faculty members selected were sent a mailing

containing a letter describing the study and requesting

participation, (Appendix A) a reply/consent form (Appendix

B), the "Personal Beliefs Questionnaire" (Gage, 1990;

Appendix C), a survey return envelope, and a reply/consent

form return envelope. One month following receipt of each

subject's response to the first questionnaire, a second

mailing was sent soliciting a second response. It

contained a contact letter, the second form of the

questionnaire (Appendix D), and reply materials. This

response was sought to enable assessment of test-retest




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