COMBATING THE FRESHMAN 15: A FEASIBILITY ANALYSIS
by
Linn Enger Caroleo
M.S., California State University, San Marcos, 1999
B.A., University of California, San Diego, 1997
A dissertation submitted to the Division of Curriculum and Instruction, Administrative Studies College of Professional Studies The University of West Florida In partial fulfillment of the requirements of the degree of Doctor of Education
2005
The dissertation of Linn Enger Caroleo is approved:
______Eula M. Largue, Committee Member Date
______Joyce C. Nichols, Committee Member Date
______Stephen F. Philipp, Committee Member Date
______Petra B. Schuler, Committee Member Date
______Frank Andrasik, Committee Chair Date
Accepted for the Department/Division:
______Joseph M. Peters, Associate Dean Date
Accepted for the College:
______Janet K. Pilcher, Dean Date
Accepted for the University:
______Carl A. Backman, Associate Vice President Date Academic Affairs
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ACKNOWLEDGMENTS
I passionately poured my time, creativity, eagerness, energy, and love into
this project. I sincerely hope that my research will in some way help freshmen in
the future.
I wish to give tribute to special people in my life that made it possible for
me to complete this dissertation and reach my goal. My husband, Wayne, who
allowed me to spend hours of “us time” in the office, and who encouraged me
through the peaks and valleys. Dr. Frank Andrasik, my mentor and guide through
this process, who willingly donated his time and patience. My entire committee,
who often under extreme time pressure completed the task and had wonderful suggestions. Uncle Per, who inspired me to obtain yet another degree and whom
I admire. My mom, Babben, who often called and asked me with great enthusiasm how things where going and offered her undying support. My father,
Larry, for asking the right question when I was stuck. My brother, Lars, for calling
when I most needed it, and for his willingness to help. My sister, Ingri, for
becoming my friend anew. My friend, Melissa, who was my panic button,
cocreator and savior. My cousin, Ellen, and my grandmother, Laura, thank you for being my cheering section; Nancy — we miss you. To Lucy and Daisy for their doggy licks. My appreciation goes to Dr. Cavanaugh, who allowed me to
use the UWF campus. iii
TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS ...... iii
LIST OF TABLES ...... vii
LIST OF FIGURES ...... ix
ABSTRACT ...... xii
CHAPTER I. INTRODUCTION ...... 1 A. The Freshman 15 ...... 2 1. Food-Related Issues...... 2 2. Lack of Exercise ...... 3 B. Basis for the Study ...... 5 1. Outcome Expectations...... 6 2. Self-Efficacy...... 6 C. Theoretical Foundation ...... 7 1. Stages and Processes of Change ...... 8 2. Point-of-Decision Posters ...... 8 D. Feasibility and Research Questions...... 9 E. Definitions...... 10 F. Summary ...... 13
CHAPTER II. REVIEW OF THE LITERATURE ...... 15 A. The Freshman 15 ...... 15 1. Food Issues ...... 16 2. Obesity...... 17 3. Stress...... 18 4. Lack of Exercise ...... 19 5. Health Locus of Control ...... 20 B. The Transtheoretical Model...... 22 1. Motivational Readiness for Change ...... 23 2. Processes of Change...... 26 3. Decisional Balance ...... 30
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C. Self-Efficacy, Attitudes, and Outcome Expectation…...... 31 1. Self-Efficacy...... 31 2. Attitudes...... 33 3. Outcome Expectation...... 35 D. Proexercise Interventions...... 37 1. Mass Media Campaigns ...... 37 2. Behaviorism and Learning Theories ...... 38 3. Behavioral Choice Theory...... 39 4. Ecological Model...... 40 5. Relapse Prevention Model...... 40 6. How It All Fits Together...... 41 E. Research on Intervention Methods Proposed For Use In This Study ...... 42 1. Point-of-Decision Posters ...... 42 2. Tailored and Stage-Matched Interventions ...... 44 3. Computer-Based Intervention ...... 45 F. Summary ...... 46
CHAPTER III. METHOD...... 48 A. Sample ...... 48 B. Procedure...... 49 1. Web Site ...... 50 2. Point-of-Decision Posters...... 54 3. Print-Based Materials...... 55 C. Instruments...... 57 D. Research Design...... 59 E. Issues Addressed ...... 60 F. Statistical Analysis ...... 61 1. Point-Biserial Correlation Coefficient ...... 63 2. Likert Scale Responses and t Testing...... 64 3. Frequencies ...... 66 G. Confounding Variables...... 67 H. Delimitations...... 69
CHAPTER IV. RESULTS ...... 71 A. Characteristics of the Sample...... 72 B. Point-Biserial Coefficient Of Correlation ...... 75 C. Intervention Surveys ...... 75 1. The Confidence Survey ...... 77 2. t Test for Correlated Means of Pre- and Postintervention Confidence Levels...... 78 3. Outcome Expectation Questionnaire ...... 79 4. t Test for Correlated Means of Pre- and Postintervention Outcome Expectation Responses ...... 80 5. Processes of Change Survey ...... 80
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6. t Test for Correlated Means of Pre- and Postintervention Processes of Change Levels...... 81 D. Stages of Exercise Change...... 84 E. Favored Intervention Method...... 88 F. Auxiliary Data ...... 92
CHAPTER V. DISCUSSION...... 95 A. Feasibility Questions ...... 95 B. Theoretically Based Research Questions...... 99 C. Further Reflection...... 106 D. Limitations...... 107 E. Finale ...... 110
REFERENCES...... 113
APPENDIXES...... 135 A. Demographic Data and Chi-Square Testing Set-Up...... 136 B. Physical Activity Readiness Questionnaire ...... 139 C. Release Form for Initiating Physical Activity...... 141 D. What Stage Are You In? Quiz...... 143 E. Outcome Expectations for Exercise Quiz ...... 145 F. Confidence (Self-Efficacy) Questionnaire...... 148 G. Processes of Change Usage Questionnaire ...... 150 H. Shift in Answer Trends on Confidence Survey Questions 1 Through 5 ...... 153 I. Shift in Answer Trends on Expectation Survey Questions 1 Through 9 ...... 157 J. Frequencies of Participant Responses on Processes of Change Quiz Questions 1 Through 20 ...... 163
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LIST OF TABLES
Table Page
1. Point-Biserial Coefficients of Correlation of the Demographic Data...... 76
2. Chi-Square Analysis of Levels of Confidence Pre- and Postintervention .. 78
3. t Test for Correlated Means of Pre- and Postintervention Confidence Quiz Responses...... 80
4. t Test for Correlated Means of Pre- and Postintervention Outcome Expectation Responses...... 82
5. t Test for Correlated Means of Pre- and Postintervention Processes of Change Responses ...... 84
6. One-Sample t Test Between Stage of Change Membership in Pre- and Postintervention Period...... 86
7. Chi-Square Analysis to Measure Significant Change in Exercise Stage Membership...... 87
8. Percent of Stage-of-Exercise Change Membership by Gender Postintervention Period ...... 88
9. 3x3 Chi-Square Test for Significance of Favored Intervention Method...... 90
10. Percent Favoring Intervention Method by Gender Postintervention Period ...... 91
11. Percent Favoring Intervention Method by Stage of Change Postintervention Period ...... 92
12. Percent of Female Smokers Versus Nonsmokers in Corresponding Stages of Exercise Change, Postintervention Period ...... 93
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A1. Demographic Breakdown of Sample Population by Percent...... 137
A2. Set-Up of Chi-Square Test For Confidence Quiz Questions ...... 138
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LIST OF FIGURES
Figure Page
1. The processes of change in relation to the five stages of change...... 29
2. Flow chart of the planned interventions, a time-line...... 56
3. Percent weight gain in freshmen population, from self-reported weight ... 72
4. Comparison of high school and preintervention exercise habits in college freshmen...... 74
5. Comparison of stages of exercise change in percent, pre- and postintervention ...... 85
6. Headcounts of freshman utilization of the respective interventions ...... 90
H1. Shift in answer trends on confidence survey Question 1 ...... 154
H2. Shift in answer trends on confidence survey Question 2 ...... 154
H3. Shift in answer trends on confidence survey Question 3 ...... 155
H4. Shift in answer trends on confidence survey Question 4 ...... 155
H5. Shift in answer trends on confidence survey Question 5 ...... 156
I1. Shift in answer trends on expectation survey Question 1 ...... 158
I2. Shift in answer trends on expectation survey Question 2 ...... 158
I3. Shift in answer trends on expectation survey Question 3 ...... 159
I4. Shift in answer trends on expectation survey Question 4 ...... 159
I5. Shift in answer trends on expectation survey Question 5 ...... 160
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I6. Shift in answer trends on expectation survey Question 6 ...... 160
I7. Shift in answer trends on expectation survey Question 7 ...... 161
I8. Shift in answer trends on expectation survey Question 8 ...... 161
I9. Shift in answer trends on expectation survey Question 9 ...... 162
J1. Frequencies of participant responses on processes of change quiz Question 1...... 164
J2. Frequencies of participant responses on processes of change quiz Question 2...... 164
J3. Frequencies of participant responses on processes of change quiz Question 3...... 165
J4. Frequencies of participant responses on processes of change quiz Question 4...... 165
J5. Frequencies of participant responses on processes of change quiz Question 5...... 166
J6. Frequencies of participant responses on processes of change quiz Question 6...... 166
J7. Frequencies of participant responses on processes of change quiz Question 7...... 167
J8. Frequencies of participant responses on processes of change quiz Question 8...... 167
J9. Frequencies of participant responses on processes of change quiz Question 9...... 168
J10. Frequencies of participant responses on processes of change quiz Question 10...... 168
J11. Frequencies of participant responses on processes of change quiz Question 11...... 169
J12. Frequencies of participant responses on processes of change quiz Question 12...... 169
x
J13. Frequencies of participant responses on processes of change quiz Question 13...... 170
J14. Frequencies of participant responses on processes of change quiz Question 14...... 170
J15. Frequencies of participant responses on processes of change quiz Question 15...... 171
J16. Frequencies of participant responses on processes of change quiz Question 16...... 171
J17. Frequencies of participant responses on processes of change quiz Question 17...... 172
J18. Frequencies of participant responses on processes of change quiz Question 18...... 172
J19. Frequencies of participant responses on processes of change quiz Question 19...... 173
J20. Frequencies of participant responses on processes of change quiz Question 20...... 173
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ABSTRACT
COMBATING THE FRESHMAN 15: A FEASIBILITY ANALYSIS
Linn Enger Caroleo
Well over half of the nation’s freshmen attending universities today are
afflicted by “the freshman 15,” which means gaining 15 pounds during the 1st
year of college. By this study an attempt was made to motivate freshmen to draw on exercise as a means to decrease this phenomenon. Three types of interventions based on the transtheoretical model were used: a uniquely designed Web site, point-of-decision posters, and preprinted pamphlets. The freshman’s confidence to perform exercises, outcome expectations in favor of exercise, and processes of change usage was measured. The favored intervention method was the point-of-decision posters. Progression from nonaction to action stages was statistically significant. Eighty-one percent of the
participants reported staying the same weight or losing weight in the spring
semester. Confidence scores, outcome expectations, and utilization of the
processes of change all increased significantly postintervention, indicating an
increase in time spent exercising.
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CHAPTER 1
INTRODUCTION
The initial interest for this study was cultivated after a lengthy discussion with several doctoral students about gaining weight in college. Most of the students agreed that weight gain was inevitable during the 4-year period of schooling; however, the reasons for the weight gain were unclear. Some blamed it on improper food choices, others on lack of exercise; a few said it was due to a steady consumption of alcohol, while others simply did not know. The term “the freshman 15” came up repeatedly during the discussion. Although no one could clearly define the phrase, everyone knew it pertained to weight gain during the freshman year in college. In this study, I attempted to clarify some of the reasons why freshmen gain weight, why they do not exercise sufficiently, what guides their attitudes about exercise as a method for preventing this weight gain, and how their attitudes affect their subsequent choices.
The self-efficacy of participating freshmen about exercise, outcome expectations concerning exercising, and readiness to start exercising were measured in an attempt to learn a little about current attitudes regarding exercise. Next, the freshmen were exposed to three types of pro exercise interventions, after which they were asked which type of intervention they
1 2
favored. The data that was collected about what intervention the participating
freshmen favored may aid policy makers and university administrators in the
future when creating interventions that are tailored to the freshmen’s fancies.
This knowledge may also assist future campus recreation program planners to promote healthier lifestyles for freshmen.
The Freshman 15
Food-Related Issues
Weight gained by students in their freshman year has become so
prevalent it has been labeled “the freshman 15.” Gaining weight during the first
year of college can lead to a lifetime of health problems. Much like the obesity
epidemic happening in this country today, the freshman 15 does not affect a
specific gender. Weight gain can occur in both females and males, with the
consequences for both genders being severe (Cook, 2003). Researchers have
identified being in a new environment and having more freedom to decide when,
what, and how much to eat as one explanation for freshman weight gain (Neale,
2004). Dining at all-you-can-eat buffets in the campus cafeterias or in restaurants
close to campus has been found to lead to bingeing or overeating, because portion sizes are not controlled and students are often attempting to get their money’s worth of food (Cook, 2003; Liao, 2002). Snacking, when used as a strategy to cope with stress, frustration, depression, or loneliness, can result in excessive weight gain with possible lasting health consequences (Berkowitz,
2001).
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Researchers have reported that inadequate diets (those high in fat and sodium) and the sedentary lifestyle shaped while in college can increase the risk for many chronic diseases later in life (Blair, Dunn, Marcus, Carpenter, & Jaret,
2001; Evans & Sawyer-Morse, 2002). College students often complain of replication in their meals due to the fact that they frequently eat all their meals in the same dining hall or fast-food restaurant (Ho, 2004). A college campus environment has been shown to be unfavorable in its effect on the development and maintenance of a healthful diet (Cullen et al., 1999). This study did not focus on eating habits, food intake, or disordered eating; however, these factors have been seen as being related to freshman weight gain. Subsequently they must be mentioned.
Lack of Exercise
Many freshmen are very active in high school, but when they arrive at their respective universities, they begin to lead a more sedentary, less active lifestyle that can cause weight gain (Wallace, Buckworth, & Kirby, 2000). Approximately
70% of high school seniors exercise on a regular basis or are on a varsity sports team (Sax, Lindholm, Astin, Korn, & Mahoney, 2002); however, Rosen (2000) discovered that 74% of a large sample of college students did not exercise on a regular basis. Within the African-American college population, the situation is even worse where researchers have found that 82% of females and 53% of males are not exercising regularly (Kelley, Lowing, & Kelley, 1998). Lack of time is a reason commonly used by freshmen to disengage from regular physical activity (Pinto, Cherico, Szymanski, & Marcus, 1998).
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Encouragement from parents has been seen as a significant force in
influencing a college student to exercise when compared with the effect of
encouragement given by a counselor, coach, or teacher (DeVoe, Kennedy, &
Peña, 1998). However, male and female students view social support coming
from parents versus from peers very differently. Henderson (2001) found that
females prefer to receive their social support in favor of exercising from their
parents, siblings, and close relatives; males prefer to obtain their social support
in favor of exercising from peers and friends, making a college campus an ideal
place for males to start exercising. Based on these findings, it becomes clear that
females are at a disadvantage when making the move away from home to
college, because their support system in favor of exercise is gone. As a result,
lack of exercise, more so for females than males, has become the norm, not the exception, on many college campuses today.
Regardless of where or when it starts, the growing evidence that the freshman 15 exists should be a wake-up call to school administrators. If weight gain on campus is possibly the beginning of adult onset obesity, then it should be imperative to find ways to help students prevent or at least minimize the freshman 15 (Levitsky, 2003). Most colleges and universities today are aware of the prevalence of the freshman 15, and although many institutions offer ways for their students to tackle the problem, the effort put forth by school administrations appears incomplete.
The purpose of this study was to help determine the most productive method that would motivate freshmen to use exercise to prevent or minimize the freshman 15. Achieving this goal will hopefully be of value to university
5
administrators, health and wellness educators, and the freshmen themselves. In addition to being exposed to three exercise interventions based on the transtheoretical model (TTM) developed by Prochaska and DiClemente (1983), the freshmen’s self-efficacy levels, amount of motivation to change, and outcome expectations in relation to exercise were measured to determine possible underlying factors for their sedentary behavior.
Basis for the Study
Exercise is commonly suggested as an effective and inexpensive method for preventing weight gain (U.S. Department of Health and Human Services
[USDHHS], 2000a). Colleges and universities often have large, modern, clean fitness facilities, offering memberships to the students at no extra charge, offering extended hours of operation, and making it relatively easy for students to start or
maintain an exercise program. In this study, a variety of intervention methods
(three) were presented to college freshmen in an attempt to motivate them to
exercise. The purpose was to determine the relative effectiveness of each
method and to isolate which type was preferred.
The three types of intervention methods were point-of-decision posters, a
special Web site created by the researcher based on the TTM, and printed
pamphlets (also based on the TTM). Other studies have used each of these
intervention methods separately and have been successful at increasing activity levels in other populations by as much as 75% (Kahn et al., 2002; Marcus &
Forsyth, 2003; Pinto, Lynn, Marcus, DePue, & Goldstein, 2001; Russell,
Dzewaltowski, & Ryan, 1999). If insight could be gleaned by determining which
6
method the freshmen preferred, this might aid university administrators in directing resources in a more constructive manner by utilizing the intervention that most appeals to the students.
Outcome Expectations
Outcome expectations and exercise self-efficacy are important when considering if or how an individual is becoming motivated to start an exercise plan. Outcome expectations are beliefs a person has regarding the end result of an action. For example, if a person engages in regular exercise (3 or more times per week, 30 minutes or more each time), it is likely that person trusts that continuing to exercise will lead to a desired outcome or effect, like weight loss, toning, strengthening, stamina, and so forth (Marcus & Forsyth, 2003). Once an individual learns that a particular behavior leads to a certain response or outcome and that the response or outcome is favorable, then that behavior will likely continue. In several studies, it has been found that people who have higher outcome expectations for exercise are more likely to continue exercising regularly and that they will then spend more time being active (Baranowski,
Perry, & Parcel, 2002; Dunn & Marcus, 2001).
Self-Efficacy
Bandura (1977) was the first to construct the self-efficacy theory, which relates to the confidence a human has in his or her ability to perform and complete a task. Before change can occur, an individual must believe he or she has the ability to change and that the person can sustain the change without a
7 relapse. Bandura (1984) argued that because a person’s belief about his or her personal competence "touches, at least to some extent, most everything that person does" (p. 251), this implies that a person’s beliefs will drive his or her decision to change. Because self-efficacy beliefs control a large part of the effect of other influences on a person’s behavior, when these determinants are controlled, self-efficacy is an excellent predictor of choice and direction of behavior. When relating Bandura’s constructs to amounts of exercise a person participates in, correlated with that individual’s self-efficacy level, with respect to exercise, it can be seen that the higher a person’s self-efficacy level the more probable it is that he or she exercises.
Theoretical Foundation
The theoretical foundation for this dissertation is the TTM. Prochaska and
DiClemente formulated the TTM for behavioral change in the early 1980s, and it has been used to explain a variety of behaviors. They discovered that behavioral change happens over time and progresses through a series of six stages
(Prochaska & DiClemente, 1983). Progression through the stages happens in a cyclical pattern, causing the person going through the change to constantly have to go back to a previous stage to reassess or relapse, then start over in order to work toward permanently altering that behavior (like smoking cessation, eating disorders, exercise).
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Stages and Processes of Change
The six stages of change (SOC) are (a) precontemplation, (b)
contemplation, (c) preparation, (d) action, (e) maintenance, and (f) termination.
(Note: Termination will not be included in this study, as this requires a person to
have started and sustained exercise for more than 2 years, which is not feasible
in the time frame of this study.)
The more inconspicuous elements involved with the stages of change are
the 10 processes of change (POCs). In order to successfully progress from one stage to another in the course of behavior change, a person will use one or more
of the POCs; each POC can be used alone or in conjunction with others
(Prochaska, Johnson, & Lee, 2002). The 10 POCs are (a) consciousness raising,
(b) dramatic relief, (c) self-reevaluation, (d) environmental reevaluation, (e) self-
liberation, (f) social liberation, (g) counterconditioning, (h) stimulus control, (i)
reinforcement, and (j) helping relationships. The POCs are broken into two
categories–cognitive and behavioral. In the earlier stages (1, 2, and 3), an
individual will use the cognitive POCs to a greater extent, while in the latter
stages (4 and 5) that person will rely more on the behavioral POCs.
Point-of-Decision Posters
Posters or placards positioned near elevators or escalators, urging people
to “take the stairs instead of the elevator” or placed near an exit urging citizens
“to walk instead of taking the bus,” are called point-of-decision prompts (or
posters). In this study, point-of-decision posters were displayed by the elevator,
near the lavatories, and near the entry and exit doors of the freshman dormitory.
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These posters were designed to encourage both stair use and increased walking because most students prefer to take the shuttle bus rather than walk to class.
Additionally, they urged freshmen to cut 100 calories from their daily diet to lose weight or dance more (“shake that booty”) to burn calories.
Feasibility and Research Questions
The freshmen were exposed to three types of proexercise interventions
(Web site, point-of-decision posters, printed pamphlets). After the intervention period, they were questioned about which intervention most appealed to them, which one they actually used, and which one they would prefer to see in the future. It was the intent of the researcher to provide appropriate and physically feasible intervention messages in order to motivate the freshmen to exercise.
The comparison of the three intervention methods was the basis for the following feasibility questions:
1. Which type of proexercise intervention did the freshmen prefer?
2. Which intervention method worked best?
3. Was there a significant difference between preferred intervention type and
gender?
4. Was there a parallel between the freshmen’s preferred intervention type
and the freshmen’s stage of exercise change?
The theoretical basis for this study and the corresponding POCs helped create the following research questions:
1. Was there an association between gender and a specific stage of exercise
change?
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2. Was there a connection between smoking and a specific stage of exercise
change?
3. Was there a relationship between previous level of exercise (in high
school) and amount of fall weight gain?
4. Was there a significant difference in stage of exercise change
membership pre- and postintervention period?
5. Was there a difference in weight gain after fall semester, then following
spring semester?
6. What was the primary mechanism that motivated freshmen to exercise
during spring semester?
7. Was there a significant difference in confidence and outcome expectation
levels pre- and postinterventions?
8. Was there a significant difference in levels of POC use pre- and
postintervention period?
In order to answer these questions that will aid administrators in the
creation of an effective health promotion plan to help freshmen prevent the
freshman 15 in the future, this researcher sought to uncover what may facilitate
students in the future to choose a healthier lifestyle.
Definitions
Attitudes. Global judgments about behavior; the behavior can be positive
or negative (King et al., 2002). An attitude is directed toward an object, such as a person, an issue, an inanimate thing, and so forth; attitudes may consist of
11
feelings, judgments, beliefs, physiological reactions, and behavioral tendencies about an object (Insko, 1967). For example, if my attitude about exercising is positive, I will perceive the act of exercising as positive.
Decision making. The process a person engages in when evaluating his or her pros and cons for a particular behavior (like exercise). If that person’s cons outweigh the pros, the decision to engage in the activity will have a negative outcome (i.e., deciding not to exercise). If the pros outweigh the cons, the decision will be positive (i.e., deciding to exercise) and behavior change takes place.
Regular exercise. Exercising moderately or vigorously 3 or more times per week, for a total duration of 30 minutes or more each session.
Moderate exercise. Performing an activity for no less than 30 minutes, 5 times per week. Moderate exercise is not an especially large amount of physical exertion, simply an increase in movement (as opposed to sitting on the couch).
Vigorous exercise. Harder physical exertion, for at least 20 continuous minutes, 3 or more times per week. During vigorous exercise an individual will break a sweat and become short of breath.
Intentions. The most proximal determinants of behavior that are proposed to be functions of people’s attitudes toward the behavior and their subjective norms (Benisovich, Rossi, Norman, & Nigg, 1998). In other words, you may have intentions of doing something, but if your attitude is negative or the pressures from those around you dictate that you not do it, you most likely won’t.
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Mediator. Representative of the identifiable factors that change based on the intervention’s consequence. A mediator can predict a person’s ability to change, such as self-efficacy, decision-making processes, social support and outcome expectations (Marcus & Forsyth, 2003). For example, receiving group support (exercising together) can improve the likelihood of a person continuing with that exercise, by increasing that person’s pros for exercise and decreasing the cons against exercise.
Moderator. That which establishes which individuals might gain the most from a specific kind of intervention. A person’s stage of change, gender, age, or socioeconomic status are all examples of moderators. Moderators can be used
to divide subjects into groups, which in turn will be given specific interventions
that match common inhibiting issues (Marcus & Forsyth, 2003). For example,
certain exercises may be more practical or feasible for women than for men.
Here gender acts as a moderator and must be addressed in the intervention
design.
Overweight. Maintaining 120-139% of one’s recommended (normal) body
weight, while obese is defined as being between 140-200% over recommended
body weight, leaving morbidly obese as a label for those over 200% of their
normal body weight (Aniol, 1998).
Subjective norms. Judgments about what others, who are important to a
person, think the person should do (Blair et al., 2001).
Tailored intervention. Intervention that is customized to each member at a
specific stage. Each person answers questions about issues related to changing
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his or her behavior, then those answers are used to deliver messages that are
personally relevant. Tailored messages are believed to be more effective at
increasing the likelihood that individuals actually read and process the information given to them, initiating behavior change (Marcus, Nigg, Riebe, &
Forsyth, 2000). This study had five possible stages of exercise change that the students could be placed into. In each stage the participating freshmen received
messages tailored to their particular stage of exercise change.
Targeted intervention. Defining clusters within a certain population that
share a specific attribute, then delivering the program best suited to this attribute
(Marcus et al., 1998). A targeted method assumes that the members of the
defined group are similar enough for one message to effectively target all
members of that group. In this study, college freshmen were targeted.
Summary
In this study, the favored intervention method freshmen might use to avoid
gaining weight the first year of college was explored. In an attempt to learn why
(as a rule) freshmen choose not to use exercise to prevent weight gain, the
participants’ self-efficacy levels, outcome expectations, and POC use was
measured (pre- and postintervention). The freshmen were exposed to three
types of exercise interventions (in an attempt to get them to exercise). After the
intervention period, the freshmen were polled regarding which type of
intervention they preferred and whether they had indeed changed regarding their
readiness to exercise on a regular basis. This information hopefully will be
14
instrumental in changing, shaping, and creating more effective health and fitness guidelines for future freshmen.
CHAPTER II
REVIEW OF THE LITERATURE
The purpose of this chapter is to review existing literature associated with
the four major subject areas relating to this study. These areas are: (a) the
freshman 15, (b) the transtheoretical model (TTM), (c) self-efficacy and outcome
expectation, and (d) proexercise interventions.
The Freshman 15
The dreaded freshman 15 occurs during a college student’s first year away from home; 15 refers to the estimated pounds (6.8kg) that nearly two thirds of all freshmen gain (Cook, 2003; Levinsky, 2003). Whether it is the starchy cafeteria food, the binge drinking, the late-night pizza cravings, or the all-you-
can-eat buffets, many college freshmen are destined to gain weight (Neale,
2004). This weight gain is becoming a serious issue for the students, their
parents, and the institutions.
Campuses around the country are becoming more aware of this situation,
and many have decided it is time to do something. A brief Google search
(conducted on August 22, 2003) of the key words freshman 15 returned over 90
colleges and universities currently offering their students some suggestions and
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support in tackling this issue. The weight gain problem is typically dealt with by creating Web sites containing tips on how to avoid or remedy the freshman 15, in addition to offering free diet and nutritional counseling, free personal training, or extensive wellness education. Having an awareness of the problem is not enough; it is important to consider why this is occurring. Understanding the reasons for such weight gain, particularly in college freshmen, may be very helpful when planning suitable interventions to encourage exercise.
Food Issues
University students’ diets lack nutritional balance. The failure to eat healthfully may be partially due to lack of proper understanding and knowledge of what constitutes a wholesome and nourishing diet (Browder, 2001). A 4-year study conducted at Tufts University found that 70% of college students eat less than the recommended amounts of fruits and vegetables per day (five servings); eighty-five percent do not eat the minimum levels of recommended dietary fiber; and the majority of students (80%) are not getting sufficient amounts of vitamins or minerals, in particular calcium (Economos, 2002). Other studies have addressed the fact that many college students ingest elevated amounts of saturated fat daily, primarily due to frequent visits to fast food restaurants and a lack of cuisine variation (Brevard & Ricketts 1996; Johnson, Solomon, & Corte,
1998). Few schools offer training in what constitutes healthful eating or appropriate diets for their students, unless nutrition happens to be a student’s chosen major. However, some schools do require completion of an entry level
17
nutrition class for graduation (Economos, 2002). Educating college students
about what constitutes a healthy diet should be given more emphasis by policy
makers.
Healthy People 2010 (USDHHS, 2000a) addresses the health and lifestyle
behaviors of college students. One goal of this national campaign is to
encourage good physical conditioning and reduce chronic diseases associated
with diet and weight (USDHHS, 2000a). Tossed salad has been shown to be the
only non starch vegetable college students eat; potatoes (fried, baked, or mashed) and sweet corn are more likely ingested (Cook, 2003). A concern of this researcher is the close proximity of fast food restaurants and all-you-can-eat
buffets on the university campus of this study. Unlike many campuses nationally,
this college does not offer a wide variety of foods in its dining hall or extended
hours of operation, thus the students are forced to go off campus to eat during
the evenings and weekends (most likely choosing fast food restaurants, strictly
due to their convenient location and economical menu).
Obesity
Overweight and obesity have become the fastest growing epidemics
affecting Americans today. According to the 1999-2000 National Health and
Nutrition Examination Survey, approximately two thirds of all American adults
suffer from overweight or obesity. Obesity and overweight are linked to the
nation’s number one killer—heart disease—as well as diabetes and other chronic
conditions. In 2000, the prevalence of obesity among U.S. adults was 19.8%,
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which reflects a 61% increase since 1991 (Mokdad et al., 2003). One in every 50 people is said to be more than 100 lbs overweight (USDHHS, 2000b). Medical conditions associated with obesity are becoming progressively more costly to society (Bhargava & Guthrie, 2002; Frazao, 1999).
Overweight and physical inactivity are estimated to be the cause of more than 300,000 premature deaths each year in the United States. This is second only to tobacco-related deaths (USDHHS, 2000b). Courtenay, McCreary and
Merighi (2002) estimated that half of all deaths in the U.S. each year could likely be prevented through improved diet, altered substance abuse, healthier lifestyles, and preventive care, such as exercise. This nation is acquiring an increasingly wider girth, and it is starting with our freshmen in college. This researcher purports that helping freshmen assume a healthier lifestyle is likely to reduce costly complications later in their lives, if that lifestyle can be maintained.
Stress
Higher education is a stressful part of someone’s life. Complete with pressures about grades and performance, school stress is likely a factor in freshman weight gain. Why? Students generally respond to stress in one of two ways: either they lose weight because they lose interest in food and cannot eat, or they use food for comfort, and they overeat on all the foods that they are fond of, which often are high in fat and sugar (Browder, 2001). Stress, manifested in constant snacking, has repeatedly been suggested as a reason for weight gain during the freshman year (Blair et al., 2001; Wallace et al., 2000). Staying
19
healthy in college has been shown to affect physical and psychological health,
which in turn influences academic success and contentment with the overall
college experience (Neale, 2004). Unhealthy lifestyle behaviors that are initiated
in college can set the foundation for possible future health problems. For
example, risk factors for osteoporosis, pertinent to college students who have not
yet reached peak bone mass, include inadequate calcium and vitamin D intake,
use of tobacco, alcohol, or steroids, and lack of physical activity (Leslie & St.
Pierre, 1999). A sedentary lifestyle coupled with rapid weight gain can lay the
foundation for serious health problems later. Unless college students take more interest in their health, they are risking their futures.
Lack of Exercise
Another reason for freshman weight gain is lack of exercise; in fact over
half of any college population is sedentary or exercises too infrequently to benefit from it (Kilpatrick, 2001; Suminski, Petosa, & Utter, 2002). Time management is an important part of everyone’s life and finding time to exercise regularly is vital if an exercise program is to be beneficial. Lack of time or lack of energy are generally the most common excuses not to engage in regular exercise (Pinto et al., 1998). Academic success in college entails more time and effort than it did in high school. When combining the added pressures of college studies with a freshman’s needs for socializing, working, sleeping, studying, and going to class, there simply is no time for exercise (Neale, 2004).
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It has been speculated that involvement in regular exercise may not be a
priority for members of certain ethnic groups because of conventional traditions
and cultural group norms (Bull, Eyler, King, & Brownson, 2001; Kelley et al.,
1998). These group norms, particularly the sedentary lifestyle, may reflect a
group’s socioeconomic status (SES) or other ensuing characteristics, such as
unsafe neighborhoods, cracked sidewalks, pollution, or lack of money (Eyler et
al., 1998). Another explanation for the disparity of activity levels in the ethnic
minorities versus whites may be their lack of education about health and exercise
as well as insufficient role modeling during early adolescence (Masse, 2000). It is hypothesized that minorities generally do not have sufficient exposure to health
education or proper exercise facts. The literature reflects a genuine concern for
the apparent lack of knowledge many ethnic minorities demonstrate regarding
what constitutes leading a healthy lifestyle (DeBate, Topping, & Sargent, 2001). It
is believed that having low SES and people with cultures that are considered
different from average American, are those who do not consider regular exercise
necessary. Therefore, the exercises that were given to the students in this study
were carefully designed to be applicable to all freshmen, regardless of SES or
ethnic group membership.
Health Locus of Control
According to Rotter (1966), locus of control is a personality construct
referring to an individual’s perception of the locus (center) of activity as
determined internally by his or her own behavior (internal locus of control) versus
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fate, luck, or external circumstances (external locus of control). A person’s
perceived control has been found to affect how that person copes with adverse
work environments, illness, SES, stress, surgical interventions and tolerance of
pain (Lachman & Weaver, 1998). Possessing a health locus of control is the
degree to which an individual believes that his or her health is controlled by
internal or external factors (Wallston, K. A., Wallston B. S., & DeVellis, 1978).
College students have been shown to be more likely to exercise if they
have ample social support, have participated in sports previously, have an
internal locus of control, and are extraverted (Henderson, 2001). Similarly,
Steptoe and Wardle (2001) stated that the likelihood of employing a healthy
lifestyle is usually 40-70% better for individuals with an internal health locus of
control. Other researchers have indicated that exercising for health reasons is
positively associated with self-esteem, while exercising for appearance or weight
control is linked to greater body image dissatisfaction and eating disturbance, principally in women (Burger & Dolny, 2002). In a comparison between weight training and aerobic dance, weight training was found to be the most effective in elevating psychological well being in college students, explained as likely being due to the fact that with weight training a person often feels a greater sense of control (Bass, Enouchs, & DiBrezzo, 2002). A college setting carries with it a multitude of pressures to succeed. Having a sense of control over one’s destiny is important to all humans. The intervention in this investigation suggested to the freshmen that they take control of their health.
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The Transtheoretical Model
U.S. psychologists Jim Prochaska and Carlo DiClemente created the transtheoretical model (TTM) for behavior change (Prochaska & DiClemente,
1983). These investigators were interested in how self-changers were able to alter or stop their own addictive behaviors. It was well known that people could change their addiction with or without professional help (Shapiro, Skinner,
Kessler, Cottler, & Regier, 1984), but little was known about how they did so. By building upon the early work by Horn and Waingrow (1966), Cashdan (1973), and Egan (1975), Prochaska and DiClemente recognized that individuals generally pass through stages of change in a rather predictable (linear) manner, which they labeled “the four stages of change” (DiClemente, 1991; Prochaska &
DiClemente, 1983). Over time, this model has progressively changed and today it is believed that a person will progress through the stages of change, then probably relapse or digress back to an earlier stage, and then have to start anew
(Prochaska & DiClemente, 1992a). Such relapses are to be expected, making change a dynamic process, as opposed to an “abrupt event of sudden change”; this gives us a spiral pattern of change (Prochaska & DiClemente, 1992a;
Prochaska & Norcross, 1994). For example, a person may start an exercise program, sustain an injury, then relapse back to an earlier stage and have to start again. When in relapse, the person will plan the next change attempt, at the same time gaining wisdom from his or her last endeavor (Prochaska &
DiClemente, 1992b).
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The health, leisure, and exercise communities have adopted the TTM and
use it in a variety of experiments and interventions. For example, the TTM has
been used to predict exercise relapse in college students (Sullum, Clark, & King,
2000), and to measure African-American college students’ readiness to be
physically active (Kelley et al., 1998). Pinto et al. (1998) utilized the TTM on college freshmen and sophomores to motivate the students to exercise and were able to increase the students to go from non activity stages to activity stages.
The most common application of the TTM involves tailored communications, which match intervention messages to an individual’s current stage (Kreuter,
Strecher, & Glassman, 1999; Skinner, Campbell, Rimer, Curry, & Prochaska,
1999). The TTM served as the foundation for two of the three interventions
planned in this study.
Motivational Readiness for Change
A person’s motivational readiness for change can be determined by
looking at that person’s current stage of change (Marcus & Forsyth, 2003).
Currently there are six well-defined stages in the TTM (adapted from Prochaska,
Johnson, & Lee, 2002):
1. Precontemplation, where individuals will, in general, process less
information about their problems, spend less time and energy reassessing
themselves, have fewer emotional responses about their bad habits, and
be less open with others about their behavior (Prochaska & DiClemente,
1992b). Currently their cons outweigh their pros with respect to their
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actions (Janis & Mann, 1977). In order to move up to the next stage,
precontemplators must recognize the negative consequences of their
current behavior.
2. Contemplation, where individuals want to learn more. They will seem very
knowledgeable and aware of their problem and are able to discuss their
bad habits endlessly. They devour any and all material on the subject (fact
gathering) in an attempt to increase their knowledge and awareness
(Prochaska, DiClemente, & Norcross, 1992). They are capable of thinking
objectively about their problem. To move from contemplation to the next
stage, these individuals must be willing to try the new behavior; they must
actually start “doing” something.
3. Preparation, where the person’s readiness to change is primed and the
willingness to try something new is present. The individual at this point has
researched, learned about, and decided against continuing with the old
behavior. These individuals have a plan of action (Prochaska, Redding, &
Evers, 2002), which they must alter and personalize to fit their needs (like
finding specific exercises that are doable). These persons will now try out
the new activity (albeit sporadically), attempting to become comfortable
with the change. In order to move to the next stage, the new actions must
become a routine.
4. Action, where specific behavior change is observable. Action is being
taken to move away from the old bad habits and toward a healthier
lifestyle. Reaching this stage means the individual has moved toward
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greater self-efficacy (Bandura, 1977), increased self-confidence, and a
feeling of greater self-worth (Prochaska, & Goldstein, 1991). The new and
healthier habit has been in use for less than 6 months at this stage. If the
person keeps up with the new behavior, he or she will automatically move
to the next stage (after 6 months).
5. Maintenance, where the new behavior has been in use regularly for over 6
months. People at this stage are less tempted to relapse and more
confident that they can continue with the changed behavior (Forsyth et al.,
2002). Success in the maintenance stage requires continuous use of all
aforementioned techniques. Just because one has made it to the
maintenance stage does not mean the struggle is over. Constant
reminders and reevaluation are needed to avoid a relapse.
6. Termination, where people have total self-efficacy, and they are sure they
will not return to their old unhealthy habits no matter what temptations they
may face (Prochaska, Johnson, et al., 2002). Because termination may
not be practical or a reality for a majority of people, it has not been given
much emphasis in TTM research (Prochaska, Redding, et al., 2002). The
termination stage is more appropriate when discussing behavior change
that involves “bad” habits that a person wishes to terminate (for example
smoking or drinking). In this dissertation, this stage will not be included
because no person should ever terminate exercising (never stop including
regular exercise in their lives).
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The stage-of-change model (as the TTM is also called) is founded on the idea that people differ in their levels of readiness to change their behaviors. A stage- of-change questionnaire effectively measures a person’s intentions as well as his or her tangible actions (Dunn et al., 1997). Tailored programs need to use differing strategies and techniques to bring about desired behavior change; program goals should differ based on the individual’s level of motivation for change (Marcus, Bock, Pinto, Napolitano, & Clark, 2002).
Processes of Change
Within each stage of change, certain processes of change (POCs) are employed by all human beings (consciously or not). There are currently ten recognizable POCs. Being subjected to a particular intervention can initiate utilization of one or more of the POCs. The customary intervention style for each process of change is added in italics by the author (the following was adapted from Glanz, Rimer, & Lewis, 2002).
1. Consciousness raising involves increasing awareness about the causes,
consequences, and cures for a particular problem behavior.
Confrontations, bibliotherapy, media campaigns.
2. Dramatic relief must have an emotional impact, such as the death of a
friend or relative who had the same habit (like smoking, drinking, morbid
obesity, etc.); the current behavior could carry a severe punishment or
involve an illegal consequence (smoking dope is illegal). Role playing,
grieving, personal testimonies.
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3. Self-reevaluation means rethinking one’s behavior, considering the
consequences of continuing the behavior, coupled with imagining oneself
without the bad habit. In addition, self-reevaluation requires that a person
assess the pros versus cons for changing the current behavior. Healthy
role models, imagery, value clarification.
4. Environmental reevaluation requires a personal assessment of how the
presence or absence of the bad habit affects one’s social environment
(other people). How does the current behavior make one look in the eyes
of others? Family interventions, empathy training, documentaries.
5. Counterconditioning represents training oneself to use a healthier activity
in place of the bad habit (substitution). Relaxation, positive self-
statements, assertion.
6. Helping relationships calls for a blending of trust, honesty, and acceptance
in support of healthy behavior change; this happens through distinctive
associations with others who are willing to give support during the change
process. Buddy system, counselor calling, rapport building.
7. Self-liberation is the belief that success is achieved by one’s own actions.
Active effort must be exerted in order to maintain control over one’s
behavior and successfully change. New Year’s resolutions, multiplicity of
choices, public testimonies.
8. Reinforcement implies providing rewards or punishments for oneself when
one has taken steps in a positive and constructive direction. Rewards are
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emphasized here. Prizes or gifts to self, group recognition, contingency
contracts.
9. Stimulus control requires the removal of cues for unhealthy habits and
adding prompts for healthier alternatives. Avoidance, self-help groups,
posted notes or written reminders.
10. Social liberation indicates an increase in social opportunities for those who
are depressed or oppressed. Advocacy, empowerment, smoke-free
zones.
Prochaska, DiClemente, and Norcross (1992) identified a definite relationship between the stages of change and the ten processes of change. The
POCs are divided into two categories: cognitive (including thoughts, consciousness, and attitude) and behavioral (including achievement, performance, and doing). People in Stage 1 or 2 use cognitive processes the most. Stage 3 is a transition stage, when cognitive and behavioral processes are used nearly equally, while people in Stages 4 or 5 use behavioral processes more (Prochaska, Johnson, et al., 2002). The continuum presented in Figure 1 is a simple way of viewing the superimposed processes onto the various stages.
Some processes overlap from one stage to another, while others are specific to a certain stage of change.
Stimulus control
Reinforcement
Helping relationships
Counterconditioning
e g Self-liberation
Self-reevaluation
Processes of Chan
Environmental reevaluation
Dramatic relief
Consciousness raising
Precontemplation Contemplation Preparation Action Maintenance
Stages of Change
Figure 1. The processes of change in relation to the five stages of change.
From “The transtheoretical model and stages of change,” by Prochaska, Redding, and Evers, (2002). In Glanz, K., Rimer, B. K., & Lewis, F. M. (Eds.), Health behavior and health education: Theory, research, and practice (3rd ed., pp.41-133). San Fransisco: Jossey-Bass.
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Several researchers (Marcus & Forsyth, 2003; Marcus, Rossi, Selby,
Niaura, & Abrams, 1992) have found that the most effective behavioral processes (for long-term behavior change) are (a) substituting alternatives (doing
something active or going outside, rather than watching TV or lounging indoors),
(b) reminding oneself (like placing running shoes, workout clothes, or a gym bag
by the door the night before), (c) rewarding oneself (buying oneself a small prize
or gift as an incentive to continue), (d) committing oneself (making a commitment
in writing to oneself or a contract with another person), and (e) enlisting social
support (calling a friend or relative for affirmations, or a buddy to keep fit with).
The freshmen participating in this study were questioned pre- and
postintervention period to see whether any of the interventions increased the use
of POCs, thus effectively moving the respective participants from one stage of
exercise change to another (higher stage).
Decisional Balance
Decisional balance is the ratio of perceived benefits to one’s imaginary barriers (pros versus cons) for change (Janis & Mann, 1977). Some people view physical activity in a positive light, while others focus more on the barriers or negative aspects of exercise. Researchers have revealed that the cons against exercising are more evident in people who are in the precontemplation and
contemplation stages; in the preparation stage the pros are in equilibrium with, or
beginning to surpass, the cons (Marcus & Simkin, 1994). People in the
precontemplation stage perceive the existence of more obstacles than the
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advantages toward exercise, while in the action stage people, have increased
their pros and surpassed the number of cons in relation to exercise (Pinto et al.,
2001). Certain barriers can be environmental, such as inclement weather, lack of a safe place to walk or bike, or the cost of joining a gym; other barriers are personal, like fear of failure, lack of social support, fear of becoming injured, or lack of time (Marcus & Forsyth, 2003).
For example, if a person discovers that he or she has high cholesterol, that person may want to start dieting or doing more exercises immediately.
However, this will usually lead to a setback (relapse) because that person has
not made a conscious decision to make all proper and necessary modifications to
both health and diet. Thus, when that person encounters obstacles (barriers) he
or she will not have the commitment to overcome them (Junno, 2003). Such a
setback will cause that person to define his or her inability in overcoming barriers
as a failure, which will likely lead to the belief that the necessary changes cannot
be made and the person gives up. The interventions in this study encouraged
permanent and lasting changes to the freshmen’s activity choices.
Self-Efficacy, Attitudes, and Outcome Expectation
Self-Efficacy
Social cognitive theory (Bandura, 1986) has been effectively adapted to
correspond with certain psychological phenomena that occur with exercise
behavior change. This theory states that a person’s interactions with the
environment, personal issues, reinforcements, and characteristics of the
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exercises themselves all interact to effect change (Blair et al., 2001; Wallace et
al., 2000). Self-efficacy is the most important mediator of behavior change and it refers to the confidence a person has in his or her ability to perform certain activities in particular settings (Bandura, 1986).
Bandura (1997) states that individuals possess a self-system that enables them to employ a measure of control over their thoughts, feelings, and actions, which results from the interaction between their self-system and external sources of influence. This self-system houses a person’s cognitive and affective structures and includes the abilities to symbolize, learn from others, plan
alternative strategies, regulate one’s own behavior, and engage in self-reflection.
Bandura (1993) further asserts that what self-efficacy and other expectancy
beliefs have in common is that they are beliefs about one’s perceived capability;
they differ in that self-efficacy is defined in terms of the individual’s perceived
capability to carry out particular performances and achieve specific results. Self-
efficacy has been shown to be one of the “strongest, mutable predictors of
exercise behavior” (Clark & Nothwehr, 1999, p.538).
A key to boosting exercise self-efficacy is providing opportunities for
exercise in attractive, clean, easily accessible, and nonthreatening settings
(Grabmeier, 2000). Most college campuses today offer free and often new (or
newly renovated) exercise facilities for their students. The university targeted for
this study is currently building a multi-million-dollar gym complex that will have all
new equipment and was set to open by Fall 2004; it was, however, damaged
severely in Hurricane Ivan, thus making opening day undetermined.
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Self-efficacy and confidence levels intensify as a person advances
through the stages of change; people will vary in their self-efficacy for different
types of physical activity (Sullum et al., 2000). For example, a person may feel
comfortable walking in his or her own neighborhood; however, this person is
unable to continue with the daily walking routine while on vacation because the
surroundings at the new location are unfamiliar. Other individuals may feel more comfortable swimming because they were swimmers in the past or they may have an old injury that makes it difficult for them to maintain a walking or running program. Measuring a person’s self-efficacy is an important part of any physical
activity intervention (Benisovich et al., 1998; Dunn & Marcus, 2001).
As previously predicted by the stages of change theory, exercise self-
efficacy in college students has been found to be linearly associated with a
student’s exercise stage (Leenders, Silver, White, Buckworth, & Sherman,
2002). The interventions planned for this study offered a variety of exercises
(some achievable even in the confines of a dorm room) that were different at
each stage of exercise change. Free personal training sessions were offered to
any of the participants who wished to learn how to use the gym and receive
personalized assistance. Personal training is normally $25 per hour at the
University of West Florida’s gymnasium.
Attitudes
The idea that attitudes affect behavior seemed so logical that, for a long
time, it was assumed to be true. Method upon method was created in order to
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find the necessary attitude-behavior relationship in order to prove this claim
(Fazio & Zanna, 1981). LaPiere (1934) challenged the current status quo by
stating that there was no relationship between attitudes and behaviors. This
radical conclusion did not find much support until researchers in the late 1960s
(Wicker, 1969) concurred that they could find little relation between attitudes and
behaviors. By the 1970s, researchers began to question not only the assumed
relationship between attitudes and behaviors, but also why and when specific
relationships are observed.
As indicated by Snyder and Tanke (1976), there are two factors that will
increase the probability of an attitude correlating with a behavior: attitude
availability and attitude relevance. If an attitude is available (in recent memory),
accessible (remembered), relevant (to the situation), and active (current), then it
is more likely to drive behavior (Snyder & Tanke, 1976). A few of the possible
reasons we do not see the expected relationship between the two are (a)
situational constraints on behavior, such as multidetermined behaviors or an
error in measurement of attitude (Snyder, 1982), (b) behavioral intentions, such
as a difference in the level of specificity of attitude or a behavior measurement
error (Ajzen & Fishbein, 1977), or (c) reference group or group-norm influences
and individual differences in attitude-behavior consistency (Godin & Kok, 1996).
The information in this section of the literature review relates to the current study
in the following way: If we consider that freshmen are very influenced by peers
and roommates, then the influence others have on a freshman’s behavior is
important to take into account when planning an intervention to change health
35
and exercise behavior. Thus, introducing this information (about attitudes and behavior) is an important endeavor.
According to the rational choice theory (Weber, 1968; Homans, 1961), feelings of insignificance and limited efficacy are factors that may decrease the level of attitude-behavior consistency. In parallel to rational choice theory, resource mobilization theory (Zald & McCarthy, 1987) emphasizes that the need for something (like exercise) must be coupled with access to an exercise facility
(for example), in addition to that person having the ability to find the time (to exercise), as well as having the financial and cognitive resources to complete an exercise routine; all this must be present in order for individuals to act effectively on their attitudes. This in turn implies, according to Morris & Mueller (1992), that
“individuals who are faced with limited resources must make rational decisions based on maximum utility” (p.22). These two theories, rational choice and resource mobilization, can be used in tandem to provide a model or some explanation for why people will act on certain attitudes and not on others (Scott,
2000).
Outcome Expectation
Outcome expectation is closely related to self-efficacy. Bandura’s (1997) conceptualization of self-efficacy actually involves two components: (a) efficacy expectations and (b) outcome expectations. Efficacy expectations refer to an individual’s conviction that he or she can successfully produce the behavior that will lead to a desired outcome, while outcome expectations refer to an
36
individual’s belief that a particular course of action will produce a certain outcome
(Bandura, 1997). Outcome expectations have an effect on a person’s choice of surroundings, behaviors, and level of persistence. Outcome expectations for exercise have been found to be related to exercise actions, causing researchers to conclude that interventions should be implemented to help people strengthen their outcome expectations, which may subsequently improve exercise behavior
(Resnick, Zimmerman, Orwig, Furstenberg, & Magaziner, 2000).
Persistence in producing a particular behavior is also affected by efficacy expectations. Individuals who have high levels of efficacy expectations will be more likely to persist with behaviors they can execute successfully, which will, in turn, increase their efficacy expectations (Bandura, 1998). On the other hand, individuals with low levels of efficacy expectations will be more likely to cease persistence of certain behaviors once those behaviors become difficult, which will, in turn, reinforce their already low efficacy expectations (Strauser, Waldrop,
Hamsley & Jenkins, 1998). The concept of self-efficacy and outcome expectation is situation-specific, meaning that one will have a range of both high and low self- efficacy expectations at one time depending on a specific situation, task, or behavior (Strauser, Ketz, & Keim, 2002).
This study explored college freshmen’s levels of self-efficacy and outcome expectation in support of regular exercise. It was conjectured by this researcher that these levels would be remarkably low, thus explaining why exercise is not the primary method by which freshmen prevent weight gain.
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Proexercise Interventions
The multitude of factors that have a bearing on whether a person chooses to be physically active or not are most commonly (a) self-efficacy, (b) self- confidence, (c) belief that there is some benefit to be gleaned from the activity,
(d) enjoyment, (e) social support, and (f) safety. There are a multitude of psychological theories or models that can help explain some of these factors and shed some light onto why people choose an active way of life. These explanations helped to shape the creation of proexercise messages passed on to the freshmen participating in this study via a Web site, point-of-decision poster, and printed pamphlets.
Mass Media Campaigns
The most common prohealth interventions today are mass media campaigns. Mass media campaigns are designed to increase knowledge, influence attitudes or beliefs, and change behaviors through newspapers, fliers, billboards, radio, or TV. Such campaigns have been found effective at increasing peoples activity levels (typically short term), as well as expanding knowledge and changing widespread opinion about health and exercise (Kahn, 2002; Nicolino,
Martz, & Curtin, 2001). Media and ad campaigns often assume presenting individuals with information or shock therapy, such as ads depicting the consequences of a certain behavior, is enough to convince them to change
(Marcus & Forsyth, 2003). Media-based methods, particularly print-based materials, are likely more effective than face-to-face campaigns because they
38
allow the participants more flexibility and choice in how they decide to use the
information presented (Dishman & Buckworth, 1996).
Behaviorism and Learning Theories
Behaviorism and learning theories (Skinner, 1953) have been applied to
people who change their lifestyle from sedentary to active. This school of thought
(Glanz et al., 2002) maintains that an individual is more apt to exercise if
conditions are in place that allows the person to initiate an activity easily, like a
park nearby, user-friendly exercise equipment and safe surroundings.
Additionally, there needs to be an outcome from that activity that is perceived as pleasing and provides the person with a sense of accomplishment. Learning theory also points out that it is important to shape the desired activity by starting small and gradually increasing the time spent exercising, the distance or the difficulty of the activity. Similarly, building in regular incentives and satisfying rewards has been shown to work (King et al., 1992).
Rewards and incentives are frequently used to motivate people to exercise. Many see exercise as punishing, tiring, or difficult to complete and the returns are often delayed, because losing weight or becoming healthier takes time. Interventions that offered rewards and prizes for partaking have increased by as much as 75% the number of participants who started exercising on a regular basis (King et al., 1992; Marcus, Selby, Niaura, & Rossi, 1992). Even though it is crucial that people eventually engage in regular exercise based on intrinsic values, using reminders and rewards is a good way to begin a lifestyle
39
transformation. Reminders, such as signs posted near the elevator, notes to self, and setting out exercise attire the day before, are proven techniques that increase the probability that a person will continue to exercise (Glanz et al., 2002;
Marcus & Simkin, 1993).
Behavioral Choice Theory
Behavioral choice theory incorporates ideas from learning, planning, and economics, while being based on decision-making theory (Epstein, 1998).
According to Epstein, people can choose to participate in regular exercise or be sedentary. What they do is impacted by (a) ease of use of equipment or location of exercise facilities, (b) believed barriers versus benefits to exercising, (c) reinforcements, and (d) the level of effort required. The choice to be active and the anticipated enjoyment of an activity is influenced by the options that exist to the person; to feel that exercise is rewarding an individual must feel that he or she chose to exercise without fear or favor (Saelens & Epstein, 1998). If people think they are being forced to do something rather than choosing to do it (freely), they will likely not continue that activity (Saelens & Epstein, 1999). The benefits of regular exercise are often slow in surfacing (delayed gains, such as weight- loss, decreased risk for heart disease, improved health); therefore, the choice to become more physically active should be rewarded early and often in the beginning, allowing long-term benefits to surface later (Forsyth et al., 2002).
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Ecological Model
The ecological model dissects behavior change by analyzing sociocultural
and environmental relationships (McLeroy, Bibeau, Steckler, & Glanz, 1988).
This model suggests that when the environment is not conducive to participating
in regular physical activity by having any of the following, unsafe neighborhoods,
lack of green spaces or bike paths, pollution, inability to purchase gym
membership, and more, causing the person to remain sedentary (Sallis, Bauman,
& Pratt, 1998).
Relapse Prevention Model
The relapse prevention model is especially geared toward helping
individuals continue with a new activity in the long term, which is vital to physical activity behavior change, because the benefits are slow in materializing (Forsyth
et al., 2002). Researchers have found that men who were active in college and
stopped were no better off physically then those who had never been in shape
(Paffenberger, Hyde, Wing, & Hsieh, 1986). The relapse prevention model helps
participants understand the difference between a relapse and a lapse in a regular
exercise routine. A relapse is a longer period of no exercise, like for several
weeks, and a lapse is a short pause in regular exercise activity, only for a few
days. Lapses in any exercise program are normal; it is important to make people
understand this so that a lapse does not turn into a return to a sedentary lifestyle
(Marcus & Forsyth, 2003).
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How It All Fits Together
Behavioral processes, such as rewarding oneself and being committed to changing, stem from learning theory, social cognitive theory, and the behavioral choice model (Marcus & Forsyth, 2003). Recognizing the benefits of regular exercise comes from the behavioral choice model, decision-making theory, and social cognitive theory (Forsyth et al., 2002). Increasing one’s healthy opportunities is related to the ecological model, while the relapse prevention model extends from the processes of change (Glanz et al., 2002). Decisional balance and self-efficacy are predictive of a person’s motivational readiness for physical activity implementation (Marcus, Rakowski, & Rossi, 1992; Marcus,
Selby, et al., 1992).
As can be seen by all the information presented above, changing one’s behavior or starting a new lifestyle is not as easy as simply making up one’s mind to do so. There are cognitive and behavioral processes involved, which must all be taken into account when planning a variety of interventions for college freshmen. Most of the information presented comes from other studies that were conducted on older populations. Students are not only away from home (possibly for the first time), learning to manage their time, trying to fit in, and feeling pressured by tests and schoolwork, the majority are also gaining weight (which brings with it more stress). In this study, the researcher intended to take into account as many factors as possible to create proexercise interventions that will motivate the freshmen to exercise. Exercise is often a stress reliever as well as a healthy leisure activity and will help reduce the amount of weight the freshmen
42
gain. Although it was unclear which of the interventions would have the greatest
impact, because each intervention has been shown to raise levels of activity in
other populations, this researcher was confident one or more of the interventions
would be successful.
Obstacles that can negatively affect a student’s best-laid plans to start exercising are abundant. For example, if a student is worried that his or her grades will drop due to an increase in time spent being physically active, then this becomes an issue that should be addressed. Hootman, Macera, and
Ainsworth (2002) stated that fear of sustaining an injury or stopping activity because of an injury are major constraints with respect to starting and maintaining an exercise program. In order to overcome any barriers, it is important that the pros outweigh the cons for exercise (Janis & Mann, 1977). In this study, measuring self-efficacy, outcome expectations, and motivational readiness for change was a crucial step in determining the freshman’s readiness to start exercising.
Research On Intervention Methods Proposed For Use In This Study
Point-Of-Decision Posters
Point-of-decision posters are signs placed in specific locations in order to cue or prompt a desired behavior. To increase exercise levels, signs are typically placed by an elevator or escalator urging people to take the stairs (instead of the more inactive elevator or escalator ride). Point-of-decision posters have been
43
used to increase stair use in malls, libraries, apartment buildings, banks, and
work places (Boutelle, Jeffery, Murray, & Schmitz, 2001; Coleman & Gonzales,
2001; Kerr, Eves, & Carroll, 2000, 2001a, 2001b; Russell & Hutchinson 2000;
Titze, Martin, Seiler, & Marti, 2001). Health promotion messages, such as “keep
your heart healthy, use the stairs” or “you can do it! For the life of your family, use
the stairs,” although increasing stair-use significantly, were less effective than
messages such as “please limit escalator use to staff and those unable to use
the stairs” or “elevator broken, please take stairs” (Coleman & Gonzales, 2001;
Russell et al., 1999).
Baseline level of stair use varies substantially in different environments.
For example, stair use is least likely in airports and bus terminals, but more likely
in shopping malls, libraries and some offices (Kerr, Eves, & Carroll, 2001a).
Researchers have found that occupants living on the third floor or below are
more likely to use the stairs because the average person is only willing to climb
up an average of 3.5 flights (Kerr, Eves, & Carroll, 2001b). Women have been
found to be more prone to take the stairs, and increased stair use takes place more frequently in the descent direction (as opposed to climbing the stairs)
(Boutelle et al., 2001). Point-of-decision posters are meant as reminders and
qualify as a process of change (reminding oneself) intervention component.
Point-of-decision posters were used as an intervention method in this study.
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Tailored and Stage-Matched Interventions
To be effective, TTM interventions should be tailored, stage-specific and personalized (King et al., 2002; Marcus et al., 2002). Messages that match a person’s actual stage of change have been shown to be more successful at actually changing someone’s behavior (DiClemente, Crosby, & Kegler, 2002).
Matching a message to a group’s identity, such as gender or sexual orientation, has also been shown to be effective (Flemming & Petty, 2000). Print-based, stage-targeted physical activity programs have been successful at helping sedentary adults become more active (Rimer, 2002). Fitting the intervention message to a person’s social class or level of education, or making an emotional plea rather than a rational or cognitive appeal, have worked in some cases
(Fabrigar & Petty, 1999).
Behavior change occurs only when a person is motivated to change.
Studies have shown that when disparity exists between a person’s motivational readiness to change and the intervention approach, that person will likely regress back to the old behavior (Dunn & Marcus, 2001; Marcus et al., 2002). Setting specific exercise goals is helpful, because goals are measurable (Marcus et al.,
2000). Goal setting is also closely related to confidence building; if the individual reaches a goal that has been set, his or her self-confidence will grow
(Baranowski, Anderson, & Carmack, 1998). Additionally, it is important to increase a person’s self-efficacy concerning his or her ability to start exercising and staying physically active (Bandura, 1997). Receiving tailored interventions, enhancing self-efficacy, employing the 10 behavioral processes for change, and
45
identifying benefits (as opposed to focusing on barriers) to exercise are all
techniques that have been proven to increase activity amounts in a variety of age
groups (Forsyth et al., 2002; Marcus et al., 1998; Pinto et al., 2001).
Researchers have indicated that matching health messages to different
characteristics of a person’s personality can increase the effectiveness of the
communication, especially with respect to altering mind sets and behavior
(Kreuter, Farrell, Olevitch, & Brennan, 2000). Humans want to establish a link to
themselves; therefore, when a message is coordinated correctly, it acts as a
catalyst and associates the ideas presented with the person’s sense of self
(DiClemente et al., 2002; Petty, Wheeler, & Bizer, 2000). In this study, tailored and stage-matched interventions were thought to provide the greatest impact, because they were tailored to a specific shared characteristic of the group (i.e., being freshmen) and were stage specific for those participants who are at the same level of motivation (i.e., same stage of exercise change).
Computer-Based Intervention
Computer technologies show enormous potential in supplying new ways to develop and deliver health behavior change initiatives (Owen, Fotheringham,
& Marcus, 2002). Studies utilizing computer tailoring have employed ideas from the TTM to plan the method and contents of interventions (Clark et al., 2002).
Computer technology allows for numerous options for each modified intervention component because the components can be accessed via tailoring algorithms, which are prompted by the participant’s responses (Science Panel on Interactive
46
Communication and Health, 1999). In interactive applications, users can access the information or program as often as they wish, which is of great benefit to
those with busy schedules who cannot commit to regular or timed activities (Tate,
Wing, & Winett, 2001).
Participants might, for example, access visual or audiovisual presentations
of particular human models of their own age, ethnicity or gender, performing
certain exercises, which they may be interested in mimicking (Marcus & Forsyth,
2003). The use of visual and auditory interfaces can catch the interest of those
who are easily distracted or uninterested (Robinson, Patrick, Eng, & Gustafson,
1998). The use of online role play can prevent some of the self-consciousness or
insecurities that may be intrinsic for those starting out with unfamiliar exercises
(Baranowski et al., 2002).
It must be mentioned that reliance completely on a Web-based delivery
method, with no use of printed materials, might limit the effectiveness of the
intervention (Wright, 2000). A blended approach is more sensible (Eng, 2001).
This study employed three methods of delivering the intervention information to
the freshmen, namely (a) a Web site, (b) point-of decision posters, and (c) stage-
specific printed pamphlets.
Summary
In this dissertation, I attempted to answer the call for further research to
improve the use of the TTM’s constructs at the college venue (Suminski &
Petosa, 2002). A further aim of this study was to measure the interaction
47
between self-efficacy and outcome expectation with a freshman’s level of motivation to change (stage). Three interventions were directed at the freshmen
and their preferences were assessed. The potential for at least one of the three
intervention methods to have an effect on some of the freshmen’s exercise levels seemed reasonable, because if one intervention did not have an appeal, another one may. Once some insight has been gleaned with respect to the freshmen’s level of motivation, self-efficacy, outcome expectation, and their favored intervention method, it will be easier for school administrators to decide on future health and leisure concerns with respect to the freshman 15. In this study, I aimed to shed light on solutions that university policymakers may offer to the freshmen who endure this epidemic. The discovery of no less than one freshman
15 preventive measure was the goal of this researcher.
CHAPTER III
METHOD
Sample
All participants were traditional college freshmen. In other words, they
were first-time students attending college directly after completion of high school.
They all attended a university in northwest Florida. The total number of
participants was 121. Sixty-one percent of the participants were female and 39%
were male. Forty-seven percent of the freshmen were smokers, with 64% of
those smokers being female. The racial make up of this freshman population was
75% White, 9.8% African American, 2.7% Asian, 0.9% Puerto Rican, 7.1% other
Latino, and 4.5% other, which closely reflected the racial makeup of the entire campus. All participants lived in the same strictly freshman dormitory because this study was designed to target only freshmen. Fifty-five percent of the
population did not work outside of school, while 24% had part-time jobs and 14%
had full-time jobs; the remaining 7% worked less then 8 hours per week (see
Table A1 in Appendix A).
This dormitory was chosen for the intervention to minimize any possibility
of cross contamination by upper classmen. Freshmen housed together who are
going through similar experiences in their first year of college were more likely to
48 49 elicit support from one another. This building had three stories and a multitude of hallways (12), which went out from a middle area much like in the shape of a star or spokes on a wheel. A resident assistant (RA) governed each hallway’s residents, and each RA was responsible for between 16 to 25 freshmen. The middle section on each floor included a communal area with a lounge and television room.
The researcher anticipated that the residents would talk among themselves and thus possibly motivate each other to be more active, which is another reason for choosing this dorm and this sample. The dormitory was a dry dormitory, meaning there was absolutely no use of alcohol permitted; no fire of any kind was allowed, like candles or tea lights; and no hallway sports were permitted, like throwing a nerf ball or wrestling. To enter this dormitory, any student must have a key card or be escorted by someone who lived in the building. All visitors had to leave a form of identification at the front desk while in the building. All visitors had to be checked out by 10:00 p.m. The front desk was staffed by RAs and upper classmen and was open 24 hours per day.
Procedure
A combination of three interventions was used in this study to assess the feasibility of each intervention. In addition to the interventions, the freshmen completed three surveys pre- and postintervention to measure (a) self-efficacy,
(b) outcome expectation, and (c) processes of change (POCs). The 1-month period prior to the intervention was considered the recruitment period, where the
50
researcher went to the dormitory and signed up participants by getting them to logon to the Web site (www.freshman15.com) and create an account. At this initial logon time, the participants were asked a series of demographic questions.
One week after the postintervention surveys had been completed, the students were required to fill out a feasibility questionnaire or exit survey. This survey helped determine (a) which intervention was favored, (b) the increase in each student’s time spent exercising per week, (c) the last reported stage of exercise change, and (d) the favorability of the study.
Web Site
The primary intervention method was a Web site created primarily for this study (www.freshman15.com). The Web site was based on the transtheoretical model (TTM) and adapted for exercise behavior change. Upon initial login, each freshman created an account, using a secure password. Personalized procedures were purposely used to ensure each participant’s confidentiality.
To determine whether it was safe for a participant to enroll in this study and increase his or her activity level, the Physical Activity Readiness
Questionnaire (PAR-Q) developed by the Canadian Society for Exercise
Physiology (1998) was used (see Appendix B for entire instrument). The
reliability coefficient, Cronbachs alpha, for this instrument was reported to be in a
range between 0.79 and 0.92; exact reliability for this particular population was
calculated and is reported in the Results section (chapter 4).
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If a freshman answered yes, to one or more of the PAR-Q questions, the student would fail the test because it was designed to pass only those who answered no on every question. This freshman was then given two options, either exit the study, or go and see a physician in order to obtain permission
(clearance) to continue. That freshman could go and see a family doctor or a student health services doctor, free of charge (on campus), to obtain this clearance. A letter for the physician to sign (see Appendix B) to physically clear a failed PAR-Q freshman was drafted. This letter was made available on the Web site. None of the 9 freshmen who failed the PAR-Q pursued getting a physician’s clearance, so they exited the study.
Upon initial login to www.freshman15.com, the freshman was asked to answer a variety of demographic questions. It was important for this researcher to know each participant’s (a) gender, (b) ethnicity, (c) smoking habit, (d) if either of the participant’s respective parents was currently exercising, (e) if the freshman was currently active, (f) if he or she was on a sports team in high school, and (g) how often he or she spoke to a family member (hourly, daily, weekly, or monthly) during fall semester. This information had a potential bearing on this study’s outcome based on other studies in this field.
After answering the demographic questions, each participating freshman would be transferred to a page containing 4 questions. These questions determined into which stage of exercise change that student belonged at that exact moment. The stage of exercise change survey was created by Marcus and
52
Forsyth (2003) and was reprinted by permission. See Appendix C for complete
survey.
Previous researchers have reported that people tend to stay at the same
stage of exercise change for a minimum of 2 weeks (Marcus, Selby, et al., 1992).
A stage of change questionnaire has been reported to measure a person’s exercise goal, as well as his or her recent physical activity (Marcus & Forsyth,
2003). Other researchers have reported that there is a direct correlation between the number of minutes a person spends exercising per week and that person’s stage of motivational readiness to change (Dunn et al., 1997; Marcus & Simkin,
1993). Based on these studies and this researcher’s calculations regarding the outcome for this study, it was decided that every freshman should be quizzed on current stage of exercise change as well as current quantity of exercise per week. This was done pre- and postintervention period.
Once a student’s initial stage of exercise change was determined, the
Web site automatically advanced every participant to the appropriate stage of
change page. The stage of change page contained information that was carefully
matched to that freshman’s present stage of change. For example, if a participant
was placed in the first stage of exercise change (e.g., precontemplation) the
information provided on his or her especially designed Web site was aimed at
increasing that precontemplating freshman’s pros in favor of exercise. This was
done primarily by causing that freshman to evaluate his or her surroundings,
then determine if exercise would make a positive difference in his or her life.
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The information at Stage 1 was very different from the information
presented at, for example, Stage 4. At Stage 4, each participant received positive
motivation in favor of continuing to exercise. A Stage 4 individual has already
started exercising, but there is a high probability that he or she may discontinue
regular exercise so positive ideas and motivation is important at this stage. For
example, at Stage 4, tips about how to add variety into a regular exercise routine
or incorporate cross training (Kahn et al., 2002; Rimer, 2002) have been found to
be of utmost importance.
Many of the exercises presented at each stage were designed to be
achievable within the confines of a dormitory room or within the dormitory
building itself (like walking the stairs). Other exercises that were proffered could
be used with or incorporated into daily activities, such as walking to class.
Considering that time is a common constraint for first year students and used as
an excuse to not exercise regularly (Bardauskis & Brown, 1999), it was important
to make the intervention exercises doable in short time intervals and on a daily
basis.
At each stage there were supplementary Web site links for those who wished to further explore specific types of exercise. These links were made available for those who wished to explore other types of activity. Other Web links went to videos of sample exercises and to instructive picture displays, like how to perform a certain stretch or different strength exercises.
Those freshmen who wished to start a regular exercise program in the
University’s gym were offered free personal training by certified staff at the
54
exercise center. Personal training at this University normally carries with it a fee
of $25 per hour for students. It was speculated that by offering this service for
free, it might motivate participants to start lifting weights. During the sign-up period several residents at Martin Hall showed an interest in learning how to lift weights and use the University’s gym, aiding the belief that free personal training was a good feature for this study to include. Not one freshman used the free personal training.
Stretching exercises were also included on each stage of exercise change page. The researcher wanted to ensure that each participant would use appropriate warm up and cool down procedures, thus the decision to include stretching on the Web site was made. It is unclear if any participants used the stretching exercises presented, because it was not measured individually.
Point-of-Decision Posters
Point-of-decision posters are designed to display short messages that might change the reader’s mind about a certain action, purchase, decision, or choice. Such posters were positioned in various locations inside the targeted dormitory to encourage (a) increased use of stairs, (b) walking to class rather than taking the campus shuttle, (c) cutting 100 calories per day in order to lose weight, and (d) dancing with exuberance in order to burn more calories. The
point-of-decision posters were replaced every 2 weeks during the 7 week intervention period. The posters were printed on fluorescent colored paper and taped near exit doors, stairwells, bathrooms, and by the elevator. The freshmen
55
were surveyed at the end of the intervention period (on the exit survey) if they saw, read, or used the information given on these posters.
Print-Based Materials
Print-based materials, consisting of colorful pamphlets designed to match
any participant’s stage of exercise change, were provided to the freshmen immediately following spring break (March 29, 2003). In order to keep the participating student’s interest in the study, this researcher determined this to be a good time to offer supplementary print-based materials. Health Enhancement
Systems (2003) printed the intervention booklets (phone number 1-800-326-
2317). The contact person was Annette Yott, whose e-mail address is [email protected]. The content of each booklet was created with the help of the American Council on Exercise and Shape Up America! and was based on the TTM. The titles and colors of the five stages of exercise change booklets were as follows:
Stage One, Yellow – Thinking About Getting Fit, 4 pages long.
Stage Two, Orange – The Benefits of Feeling Fit, 8 pages long.
Stage Three, Blue – Preparing to Become Physically Fit, 16 pages long.
Stage Four, Green – Feeling Good About Being Fit, 8 pages long.
Stage Five, Purple – Staying Fit for Good, 8 pages long.
The timeline for this study is presented in Figure 2.
February 9 – March 9, 2004
The researcher entered the target dormitory and introduced the study. Free personal training at the University’s gym was offered, as well as free counseling. The www.freshman15.com website was introduced. Freshmen were urged to log on.
March 9-12, 2004
The first point-of-decision posters went up and the first set of on-line quizzes were initiated. The quizzes measured the freshmen’s self-efficacy, outcome expectations, and POCs usage.
March 29 – April 2, 2004
Print based materials were distributed to all participants, based on their current stage of exercise change. The second round of point-of- decision posters went up.
April 10-16, 2004
Last set of point-of-decision posters went up. The second set of on-line quizzes were taken. The quizzes measured the freshmen’s self-efficacy, outcome expectations, and POCs usage.
April 22-29, 2004
Final testing of each participant’s stage of exercise change takes place. The exit quiz, measuring intervention preference, is completed.
Figure 2. Flow chart of the planned interventions, a time-line. POCs = Processes of change.
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Instruments
The Outcome Expectations for Exercise (OEE) scale (Resnick et al.,
2000) is an effective way to determine a person’s expected benefits from
physical activity (see Appendix D for entire instrument). This assessment asks
both about mental and physical outcomes (9 questions total). Improving a person’s outcome expectations will likely motivate him or her to continue
exercising.
Marcus, Selby, et al. (1992) developed the self-efficacy questionnaire to
measure the major components of self-efficacy that an individual may have in favor of exercising or continuing to exercise on a regular basis (see Appendix E
for complete instrument). Self-efficacy scores have been shown to increase as a
person becomes more active; thus the higher the score, the more confident a
person is that he or she can adopt and maintain an exercise plan.
Utilization of the ten processes of change should increase as a person
becomes more active, so to measure specific usage of each of the ten POCs,
Marcus, Rossi, et al. (1992) developed a questionnaire (see Appendix F for
entire instrument). The strategies and techniques, which people use to change
their behavior or belief regarding exercise, are governed by certain POCs.
In the implementation phase of behavior change, the use of the cognitive
POCs should be greater than the use of behavioral POCs (Blair et al., 2001;
Marcus, Rossi, et al., 1992). Then as time goes on and an upward progression
through the stages takes place, the behavioral POCs take over and the use of
cognitive POCs lessens. Thus a shift from use of cognitive to use of behavioral
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POCs should be evident on a pre- and postintervention quiz about POCs use.
Some studies suggest that it actually is important to increase a participant’s
usage of all POCs in order to continue exercising, regardless of the POCs being
cognitive versus behavioral (Marcus, Rossi, et al., 1992).
This study measured the freshmen’s utilization of all ten POCs, in order to
determine if the freshmen were exercising regularly. By understanding if there
were trends in POC usage by the freshmen, this might make it easier in the
future to alter University health care methodology and thus accommodate the
freshmen’s needs better. Cronbach’s alpha reliability for all three of the
aforementioned surveys was calculated and reported in chapter 4.
All freshmen were asked to self-report what their weight was at the
beginning of the school year, as well as how much weight they thought they had
gained since then. For any participant who may have been struggling with
weight, body image, depression, food or an eating disorder, one-on-one
counseling was made available at no charge. It was understood by the
researcher that the freshman year is a time of turmoil, and some students may
need counseling. The counseling was conducted by the University’s counseling services and coordinated by Dr. J. Pollard and Dr. R. Magerkorth.
At the end of the intervention period, the freshmen were retested for levels of self-efficacy, outcome expectation and daily POC usage. A week after the end of the intervention period, the participants were surveyed through an exit survey
to determine which intervention worked best. The questions on the exit survey
were designed to determine whether the Web site, printed pamphlets, or the
59
point-of-decision posters affected the freshman’s decision to perform any of the suggested exercises. The final stage of exercise change was recorded from each participant’s final entries on the Web site, and this was instrumental in determining the success of this intervention study.
Research Design
First and foremost this was a feasibility study (e.g. exploratory research).
The purpose was to determine which type of intervention freshmen preferred, which meant determining which intervention actually motivated them to exercise.
Simultaneously this study measured how the freshmen felt about exercising, their exercise outcome expectations, and their motivation to change. Informed consent was obtained prior to any freshman logging onto the Web site (see
Appendix G). The researcher met with each participant during the recruitment period in February 2004.
In order to obtain appropriate signatures and permission to access the dormitory to complete this study, the researcher met with the University’s president, the University’s housing authorities, several health and leisure personnel, and the counseling center employees (December, 2003). Those students who were interested in joining the study after the recruitment period, which ended March 9, 2004, were required to contact the researcher via email or phone and arrange to sign the informed consent release form. A special log-on protection was created on the www.freshman15.com Web site, so that any student who had not signed the appropriate consent form would be unable to get
60
onto any of the five stage of exercise change pages by entering the uniform resource locator (URL) at the top of the browser.
Issues Addressed
The following explanations and examples illustrate the results this researcher hoped to see postintervention period. For starters, had any participant shown fulfillment of any or all of the goals or succeeded in fulfilling the stage based requirements? If so, it would prove to the researcher that the interventions had an effect. Recall that the object of the study was to motivate freshmen to use exercise to prevent weight gain, thus (a) utilization of any of the stages of exercise change, (b) any increase in time spent exercising, (c) having a more positive outcome expectation regarding exercise, (d) or utilization of any or all of the POCs would indicate a successful intervention period.
Movement along (up through) the stages. The question being if after the intervention period, have any freshmen gone up, down, or stayed on the same stage of exercise change? It was anticipated that some students would advance one or more stages during the seven-week intervention period.
Time spent exercising. Did the total time a freshman spent exercising per week increase, decrease, or stay the same? Any change in a student’s self- efficacy level indicated (based on previous research) an increase in his or her total time spent exercising per week. Similarly, did a jump or elevation (up) in the freshman’s stage of exercise change take place during the intervention period?
61
If so, this indicated a boost in exercise level without actually needing to measure
each student’s minutes spent exercising. For logistical purposes this study
refrained from directly measuring time spent exercising; however, self-reported
time spent exercising per week was collected. The degree of self-efficacy was
measured pre- and postintervention.
Outcome expectations. The outcome expectations were projected to
increase over the seven-week intervention period. As with self-efficacy, if the
level of outcome expectations increased (from 1 to 5 on a Likert scale), this
indicated that the participant was adhering to an exercise plan and was
increasing weekly total minutes spent exercising.
Processes of change. Processes of change measured both pre- and postintervention, primarily used a measure for the researcher, who was interested in which of the POCs the freshmen utilized the most. A change in
POC usage was of interest and was measured, to determine usage as well as improvement or a shift from utilization in one stage of exercise change versus another. A comparison of the freshman’s most utilized POC with the best practices from previous research may help shape the creation of future interventions. For example, this information could help current policymakers in creating future interventions to motivate freshmen to exercise.
Statistical Analysis
The Statistical Package for the Social Sciences (SPSS) 11.0 was utilized for the statistical analysis portion of this study. Other studies found a positive
62
correlation between levels of self-efficacy and the number of minutes spent exercising (Glanz et al., 2002), thus the Pearson correlation coefficient was also used in this study.
The correlation between two variables reflects the degree to which the variables are related. Pearson’s correlation reflects the degree of linear relationship between two variables, and ranges from –1 to +1. Previous exercise and physical activity studies have reported correlation coefficients ranging from r = 0.56 up to r = 0.94 as acceptable (Borg, 1998; Norman, Kracl, Parker, &
Richter, 2001). Common usage for calculating a Pearson correlation is to find the percentage of the independent variable that can predict the variation of the dependent variable. For example, if we take a Pearson correlation coefficient value of .9177 and square it, we obtain the value of .8422. This implies that the x-values predict approximately 84% of the variation in the y-values.
A correlation coefficient measures the extent of association between two variables, but association does not imply causation. It frequently happens that two variables are highly correlated not because they are related to one another, but because they are both strongly related to a third, oftentimes unknown, variable. In the absence of careful control of all variables and the ability to manipulate values of one variable, it needs to be mentioned that the possibility of an unidentified underlying third variable could be influencing the two variables under investigation (Connor-Linton, 2004).
A person’s expectation in favor of exercise has been found to be correlated with the amount of time that person spends exercising per week
63
(Strauser et al., 2002); therefore, in order to measure whether outcome expectation levels were correlated with gender, time spent exercising, or weight
gain, the Pearson correlation was again utilized.
Furthermore, it was important to measure if there was a connection
between gender and a freshman’s specific stage of exercise change, as well as
gender and favored intervention method. The chi-square test was used to
answer the previously posed research questions, as well as comparing
frequencies, with respect to nonactivity stage membership (1, 2, and 3) versus
activity stage membership (4 and 5), first pre- then postintervention period.
Point-Biserial Correlation Coefficient
The point-biserial correlation coefficient can be used in any research
where one is interested in understanding the degree of relationship between a
naturally occurring nominal scale and an interval (or ratio) scale (Weisstein,
2004). For instance, measuring the statistical significance in the degree of
relationship between (a) being male or female, (b) smoker or nonsmoker, (c)
whether your mom or dad exercises or not, (d) your race, and (e) exercise
outcome expectations or utilization of processes of exercise change as
measured by scores on the quizzes given in this study may be examined by this
analysis.
The dichotomous nature of binary variables allows for the classification of
both the x and y variables into two categories, with separate group sizes (small n,
as opposed to N which is the total group size), means, and variances. The
64
guaranteed fulfillment of the linearity assumption for two groups has considerable
theoretical importance within the framework of the general linear model
(Pedhazur, 1997). Algebraically, a theoretical advantage can be achieved by restricting the variability of the predictor variable by defining it as a variable that defines two categories, signified by 1 and 0; for example, male = 1 and female =
2 (Silver & Hittner, 1997). The coefficient of correlation between a (binary) categorical variable x and a continuous variable y is the point-biserial correlation
coefficient.
The point-biserial correlation is conceptually important, because the
correlations can help the researcher understand how the coefficient of correlation
can be used to measure a difference between two means (Brown, 2000). The
point-biserial statistical test was utilized in this study to measure the correlation
between various dichotomous demographic variables and other multianswer
demographic variables.
Likert Scale Responses and t Testing
For results from questions that have responses to a Likert scale, it is
appropriate to calculate means because the number that is coded can give one a feel for which direction the average answer tends. The standard deviation is also
important as it gives an indication of the average distance from the mean (Hinkle,
Wiersma, & Jurs, 1994).
A low standard deviation would mean that most observations cluster
around the mean. A high standard deviation would mean that there was a lot of
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variation in the answers. A standard deviation of 0 is obtained when all responses to a question are the same.
The t test for correlated samples is especially useful in research involving human or animal subjects because it is very effective in removing the extraneous effects of preexisting individual differences (Lowry, 2004). There are situations where the facts that are of interest are merely obscured by the variability of individual differences, thus the t test is useful. Much of this variability would stem from individual difference, such as motivation for a particular task, anxiety in new situations, ability to motivate oneself to continue exercising when first started, prior adaptation to one or the other type of exercise, and so on. A t test is a strong test, but just for two groups, so the results from these comparisons are not for hard scientific proof, but rather for indications of trends in the data.
The t test is used when the variable under consideration can be measured on a scale such as typical Likert scale ratings (Williamson, 2003). This is the case for rating scales. Participants are asked to rate or assign a value to a service they receive or a feeling they had on a scale of 1 to 5, where 1 is poor, low self-confidence, strongly disagree or never, and 5 is excellent, high self- confidence, strongly agree or often. Because this is a scale, it makes sense to add up all responses and divide by the number of responses to obtain the average, or mean. Because research is generally carried out to answer questions about generalities that exist among the group of respondents, means and averages are very useful (Riley, 2001).
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Technically, the t test is testing the (null) hypothesis that says the averages of the two groups (pre- and postintervention responses) are equal. The distribution of responses to a Likert scale with 5 possible answers is usually only marginally close to a normal probability distribution, which is sufficient for t test usage. This is because the range of answers is discrete, not continuous
(University Computing and Communication, University of New Orleans, 2004).
Any variation in the freshmen’s average answers can likely be explained as developing from two sources. One source is the variability due to sampling.
Whenever survey research is utilized a sample of the total population is used, because doing a census is too costly or not possible. Sampling can introduce variation. The second source of variation is the true differences between the pre- and postintervention responses (e.g., mental state of the freshmen). The question becomes, “have the freshmen really been influenced by the intervention making their answers on the pre- and postintervention quizzes truly different, or are the differences explained by sampling variation?” The t test determines if the difference between the pre- and postintervention responses is statistically significant or not.
Frequencies
Because frequencies and percentages are easy and convenient methods by which to present data, all primary and secondary demographic data (from the log on survey) were presented as such. Furthermore, frequencies (percentages) were used to illustrate pre- and postintervention changes in the answers given on
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the three surveys. Presentation of the data pertaining to shifts in the stages of exercise change was accomplished using bar graphs. Similarly, bar graphs were used to display feasibility data, which shows which of the three intervention was favored.
The test-retest repeatability between the first and second administration of the self-efficacy survey, the outcome measure questionnaire, and POC usage surveys were addressed using Cohen’s kappa coefficient. This measure of repeatability is a ratio between two measures in order to get a handle on which levels of agreement can be attributed to reproducibility rather than to mere chance (Leslie, Johnson-Kozlow, Sallis, Owen, & Bauman, 2003).
Confounding Variables
Previous athletic experience will clearly affect the outcome or the level of motivation it will take to get certain freshmen to exercise. It is highly likely that if a freshman was active in high school, he or she will be easier to inspire and may travel up several stages during the intervention period. Therefore, each participant was asked about his or her previous athletic experience in the initial demographic assessment.
Parental support and parents’ activity levels may have had an effect on the freshman’s decisional balance. Recall that females are more likely to continue participating in sports after high school if their mothers are active in their
(the mothers’) daily lives (Sax, 1997), while males obtain their social support in favor of exercise from peers and friends.
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To address these social support issues, two questions specifying current
parental activity level were added to the initial demographic survey. Family support or the number of times a freshman contacted a family member per month may have had some bearing on that student’s exercise habits.
Possible inequalities, such as gender, socioeconomic status, and age, in
addition to influences of cultural differences may change the expected outcome.
Due to differing cultural beliefs, variations in rearing styles, and dissimilar
knowledge about what constitutes a healthy lifestyle, ethnicity and race may have
affected the outcome of this study.
Validity and reliability of the assessment tools could play a part in the
results. Each instrument was tested for reliability measures (Cronbach’s alpha)
for use on this particular freshman population.
Misclassification, in terms of placing participants in the incorrect stage of
change, has been reported as a potential problem (Bull et al., 2001; Warnecke et
al., 1997). Luckily, the stage determination survey that was included on the
freshman15.com Web site has previously been reported as having the highest
internal and external validity measures, as reported by its creators Marcus and
Forsyth (2003).
Honesty, in relation to (a) what the freshmen self-reported with respect to
the amount of exercise they participated in, (b) what their weight was, or (c) the
amount of fall or spring term weight-gain, was thought to be highly suspect. In the
literature it states “Self-reporting is an acceptable measure within the health and
leisure science community” (DiClemente et al., 2002; Glanz et al., 2002; Perkins,
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Simnett, & Wright, 2001), thus, what the freshmen reported as being their current activity level or their fall weight gain (in pounds) was taken at face value.
Delimitations
The choice of sample was convenient, yet still a cluster sample, because every student in the chosen dormitory had an equal chance of participating.
This intervention took place in the spring semester. It was conceivable that
by the spring (especially after Christmas), some of the freshmen had already
gained some weight, and were consequently more “ready” to participate in the
pro-exercise interventions. However, for every new freshman class there will be a
fall and a spring semester, so timing was probably not that central and, hopefully,
did not affect the outcome.
The number of people having Internet access has in the literature limited the success of Web-based interventions in the past. Students in this sample all had e-mail addresses (automatically by being a student) and most freshmen had
Internet access either in their room or at several easily accessible locations
around the campus, making accessibility to the Web less of an issue.
Although Florida is an ideal state for outdoor activities most of the year,
the weather deserves mentioning. In the winter months, the area near this
northwest Florida university gets cold and, at times, rainy. This could have
restricted the freshmen’s abilities to do exercises and activities outside. There
was a nice-size gymnasium and pool facility on campus; however, these were a
bit of a walk away (approximately 0.8 miles) from the target dormitory. A shuttle
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bus ran around campus and picked students up at various locations every 15 minutes, so very little should have stood in the way of a student who wanted to start exercising (by taking the shuttle to the gym in any weather). Also, free
personal training was offered to the freshmen as a perk to being a participant
in this study.
Due to time limitations, the original creation and idea were altered a
number of times. Unfortunately, some of the planned procedures had to be
omitted and certain reliability and validity procedures had to be changed.
This may or may not have had an affect on the final results.
CHAPTER IV
RESULTS
The results of the analyses used to answer this study’s feasibility and research questions are presented in this chapter. Descriptive statistics and frequencies are listed first in order to describe the demographic information of this sample. A coefficient alpha for each of the surveys with this particular sample is presented, followed by pre- and postintervention survey results. Recall that the pre- and postintervention survey information was gathered to gauge the freshmen’s expectations about exercise and how confident they felt about their ability to complete exercises in the face of certain stressors. There was also a processes of change (POCs) survey given in the pre- and postintervention period. The POCs survey measured the freshmen’s readiness to change and initiate or sustain regular exercise routines. Presentation of data pertaining to shifts or movement up through the stages of exercise change is included, followed by a breakdown of gender, parental exercise habits, and the freshmen’s social support as it pertains to the stages. Finally, the follow-up and feasibility quiz results are introduced. The exit quiz was given 1 week after the intervention period. The exit quiz asked the remaining participants a variety of questions that would help answer the study’s over-arching feasibility question about which intervention worked best. 71 72
Characteristics of the Sample
Consistent with previously reported research on the freshman 15 (Blair et
al., 2001; Cook, 2003; Levinsky, 2003), 59% of this freshman population reported
a weight increase of 5 pounds or more in the fall term. One third of this
population gained over 10 pounds in the first 4 months of college (see Figure 3).
35%
30% 30% 29%
25%
20% 18%
15% 14%
10% 9%
5%
0% Lost Weight Stayed The Same Gained 1-4 lbs Gained 5-10 lbs Gained > 10 lbs
Weight Increase After Fall Semester
Figure 3. Percent weight gain in freshman population, from self-reported weight.
By comparing the answers given in the demographic survey during the recruitment period and answers given on the preintervention survey, certain interesting trends were revealed. For example, those students who had gained more than 10 pounds during the fall semester stated they were predominantly sedentary in high school. However, those who gained between 1 and 10 pounds
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during the fall semester had, for the most part, been on a sports team in high school. This was a somewhat surprising finding (in the eyes of the researcher).
Smokers gained the least amount of weight over the course of the fall term. Actually, nearly one third of the freshmen (32%) who reported being smokers also reported losing weight, in contrast to those who reported “staying the same” or “gaining weight”. Smokers also reported having the least amount of regular contact with a family member on a monthly basis, when compared with the nonsmoking portion of the sample who reported having more frequent contact with family.
Seventy percent of the freshmen had contact with a family member 3 or more times per week. Whereas, one third of the sample acknowledged speaking to a family member more than once daily. Recall that family support is important, especially to female freshmen, in relation to exercising (Henderson, 2001), which was one of the primary reasons for gathering data pertaining to amount of family contact.
As can be seen in Figure 4, 46% of the freshmen were on a sports team in high school, while 28% were basically sedentary. Basically sedentary was defined as exercising less than 3 times per week for 30 minutes or more.
Because there were different totals in the pre- and postintervention participant groups of freshmen (18% attrition rate), it was easier to compare the groups by transforming the frequencies into percentages. The self-reported preintervention
(e.g., after fall semester) levels of exercise revealed that 68% of the freshmen were sedentary, while only 15% exercised on a regular basis (more than 3 times
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per week) or were on a sports team. A near complete reversal seemed to take
place with this sample of freshmen after they completed one semester in college.
50
46 45
40
35 35 33
30
High School 25 After Fall Semester
20 19 17 15 15
11 10 9 8 7
5
0 Did/Do Not Occasionally Exercising > 1 per Exercising > 3 On a Sports Team Exercise week times a week Exercise Habits
Figure 4. Comparison of high school and preintervention exercise habits in college freshmen.
Bear in mind that one of the conjectured causes of freshmen weight gain is a decrease in exercise levels in comparison to when the students were in high school (Rosen, 2000; Sax et al., 2002). The interventions in this study attempted to increase the freshmen’s time spent exercising, while motivating them to draw on exercise to reduce the amount of weight gained during freshman year in college. As mentioned in chapter 3, the discovery of no less than one freshman-
15-preventive measure was the goal of this researcher.
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Point-Biserial Coefficients Of Correlation
The values of the point-biserial coefficient are numerically equivalent to
those that could have been obtained by the product-moment coefficient of
correlation or Pearson's correlation computed from the same data (Silver &
Hittner, 1997). The point-biserial correlation coefficient provides a link between the correlation methods and statistical methods estimating the probability that differences between two or more means are large enough to be statistically significant (Brown, 2000).
Correlation coefficient analyses were conducted between all of the initially collected demographic data. These data were collected based on previous research that stated such demographics could influence a freshman’s choice to exercise. As can be seen in Table 1, some significant correlations did exist.
However, when compared to previously reported correlation levels in the field of health and leisure sciences, these results were considered to be weak correlations. With respect to this study, the findings are well worth highlighting,
since one way of interpreting the r = .69 for gender and weight gain is to square r, which reveals (r2 = .48) that 48% of weight gain is accounted for by knowing
gender.
Intervention Surveys
Three types of questionnaires or surveys were administered to the freshmen during the pre- and postintervention periods. All three surveys were
Likert-type surveys, with five levels. The questions required each participant to
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attach a value or opinion to every question, then answer on a continuum from
strongly disagree to strongly agree; or a similar continuum from never to
repeatedly.
Table 1
Point-Biserial Coefficients of Correlation of the Demographic Data
Demographic data questions with dichotomous response options
Demographic data with Likert scale Mother Father response options Gender Smokea exercises exercises
High school .55* -.20 -.16 .37 exerciseb
Weight gainedc .69** .43 .12 -.38
Family supportd .66** -.47* .31 .30
Freshman’s -.31* -.54* -.28 .08 exercise levele
Workf .35 -.03 .13 -.10
Note. a Smoke — participant smokes or not. Father or Mother exercises implies that the freshman’s father or mother (respectively) exercises on a regular basis (or not). bHigh school exercise asked for each participant’s amount of exercise per week in high school. cWeight gained — amount of weight a freshman gained in the fall semester. dFamily support — how many times per month, week, or day that a participant spoke with a family member. eFreshman exercise level — level or intensity at which a freshman is currently exercising. fWork — does the participant work outside of school; if so, how many hours per week. *p < .05. **p < .01. **p < .001.
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The Confidence Survey
The first of the three pre- and postintervention questionnaires was the
confidence survey. This survey measured a participant’s confidence level with
respect to completing an exercise regime in a certain situation, like having a
headache, inclement weather, being angry, etc. The Cronbach’s alpha reliability
for this survey with this particular population was α = .96.
There were five questions on the confidence survey. The responses on the first confidence question showed no significant shift from low to higher self- assuredness by the freshmen from pre- to postintervention. However the remaining four questions showed a shift from slightly confident (preintervention) to moderately or extremely confident (postintervention).
To determine if the variation in confidence levels (pre- and postintervention) was statistically significant, a 2x5 chi-square test was performed. Research Question 7 in chapter 1 asked about a significant difference in confidence levels pre- and postintervention. As can be seen in Table 2, there was a significant difference between the observed and expected values in all but the first confidence quiz Question. (Note: To see how each 2x5 chi-square test was set up, then repeated 5 times, see Appendix G, Table G2.)
Recall that the literature (chapter 2) showed that increased levels in confidence, in favor of exercising, implied that the participant’s levels of confidence rose during the course of the intervention period. Each individual survey question’s shift is illustrated in Figures H1-H5 in Appendix H.
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Table 2
Chi-Square Analysis of Levels of Confidence Pre- and Postintervention
Confidence survey
question number df χ 2 p
1 4 8.738 .07
2 4 14.929 .01
3 4 10.405 .05
4 4 19.452 .001
5 4 20.881 .001
Because the chi-square analysis is, in this case, tedious to perform due to
the nature of the surveys and the Likert scale on which the responses are given,
the t test for correlated means will be used from now on to show significance.
The purpose of the confidence survey questions was to measure how self-
assured freshmen were that they could overcome barriers that may emerge
when completing a planned exercise routine. Increases in confidence levels imply a greater familiarity (higher self-confidence) with exercising, thus making the individual more likely to continue. Having greater exercise confidence implies more time was spent exercising (Russell et al., 1999).
t Test for Correlated Means of Pre- and Postintervention Confidence Levels
A simple t test was performed on the pre- and postintervention responses to test for significance. This was done to answer Research Question 7. All
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confidence survey responses showed a significant change from pre- to
postintervention. The results are presented in Table 3.
Outcome Expectation Questionnaire
The second pre- and postintervention survey was an outcome expectation
questionnaire, which determined a person’s expectation about the outcome of
completing certain types of exercise. For example, exercise makes me feel
better, helps me feel less tired, is enjoyable, etc. The Cronbach’s alpha reliability
for this survey with this particular population was α = .86.
There were nine questions on this questionnaire. Surprisingly, nearly every expectation question showed a shift from negative or neutral
(preintervention) to agree or strongly agree (postintervention). See Appendix I,
Figures I1-I9, showing these shifts in outcome expectations. Recall that a shift in outcome expectations in favor of exercising has been shown in the literature to imply a higher motivation for exercising and an increase in time spent exercising
(Baranowski et al., 2002; Dunn & Marcus, 2001).
These findings suggest that specific expectations for negative or positive outcomes, like little or no optimism, or positive feelings about exercise
may influence day-to-day exercise-related social cognitions. The finding that
those with low self-efficacy or outcome expectations significantly differed from
those who are positive or more highly motivated supported findings from
previous research (Peterson, 2000).
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Table 3
t Test for Correlated Means of Pre- and Postintervention Confidence Quiz
Responses
Pre Post Confidence quiz question M SD M SD df t
1 2.29 1.37 2.71 1.26 86 19.79***
2 2.57 1.07 2.74 1.24 86 20.19***
3 2.62 1.25 2.94 1.23 86 19.19***
4 2.63 1.14 3.04 1.14 86 21.18***
5 2.54 1.11 3.40 1.05 86 20.87***
***p < .001.
t Test for Correlated Means of Pre- and Postintervention Outcome Expectation
Responses
As with the confidence quiz, a simple t test was performed on the pre- and
postintervention responses to test for significance. This was done to answer
Research Question 7. All nine expectation quiz response categories showed a
significant change from pre- to postintervention. The results are presented in
Table 4.
Processes of Change Survey
The third pre- and postintervention comparison survey was the POCs
survey. The results of this survey determined which types of reminders or
81 processes each freshman utilized effectively to continue a regular exercise routine (e.g., placing one’s gym bag by the door the night before in order to remember to go to the gym the next day, gleaning support from friends in favor of continuing to exercise, giving oneself rewards for exercising, etc.). The
Cronbach’s alpha reliability for the POCs questionnaire with this group of freshmen was α = .88.
There were 20 questions on the POCs survey. Again, as with the two other surveys, the overarching result for the entire population was a shift toward utilizing POCs to a greater extent. Recall, that as individuals start exercising more regularly, they will automatically increase the use of more POCs (Marcus &
Forsyth, 2003). Thus, an upsurge in this population of freshmen’s use of POCs probably indicated an increase in weekly time spent exercising, answering
Research Question 8, from chapter 1.
t Test for Correlated Means of Pre- and Postintervention Processes of
Change Levels
To test whether the shift in POCs survey answers from pre- to postintervention was significant, the t test was utilized (see Table 5). All of the
POCs survey responses demonstrated a statistically significant increase in usage. The results in Table 5 address Research Question 11 posed in chapter 1.
Recall that the goal of this study was to motivate freshmen to exercise more; thus, an increase in use of POCs, as indicated by the significant t test results,
82 coupled with the significant shift from the nonaction to the action stages suggests that one or more of the interventions were successful.
Table 4 t Test for Correlated Means of Pre- and Postintervention Outcome Expectation
Responses
Pre Post Confidence Question M SD M SD df t
1 2.63 1.14 2.76 1.21 86 19.09***
2 2.54 1.11 2.78 1.29 86 20.55***
3 2.82 1.36 3.54 1.29 86 26.05***
4 2.79 1.28 3.17 1.28 86 21.68***
5 2.27 1.21 2.82 1.35 86 22.32***
6 2.98 1.33 3.37 1.26 86 24.08***
7 2.27 1.21 2.76 1.28 86 20.57***
8 3.12 1.25 3.61 1.46 86 29.92***
9 2.93 1.31 3.20 1.32 86 22.17***
***p < .001
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Table 5 t Test for Correlated Means of Pre- and Postintervention Processes of Change Responses
Pre Post
POCs M SD M SD df t Question
1 2.13 1.11 2.56 1.20 86 17.07***
2 2.40 1.18 2.77 1.24 86 18.61***
3 2.55 1.20 2.98 1.33 86 21.75***
4 2.82 1.31 3.20 1.28 86 23.18***
5 2.27 1.21 2.82 1.30 86 19.33***
6 2.88 1.33 3.22 1.26 86 23.98***
7 2.37 1.21 2.76 1.28 86 18.27***
8 3.12 1.25 3.61 1.46 86 27.92***
9 2.76 1.20 3.27 1.21 86 24.17***
10 2.20 1.06 2.63 1.13 86 17.96***
11 2.62 1.15 2.71 1.26 86 18.05***
12 2.93 1.30 3.42 1.31 86 25.08***
13 2.82 1.25 3.24 1.27 86 24.01***
(table continues)
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Pre Post
POCs M SD M SD df t Question
14 2.76 1.15 2.97 1.24 86 21.69***
15 2.27 1.06 2.45 1.19 86 16.98***
16 2.65 1.14 2.96 1.24 86 21.54***
17 2.75 1.19 3.22 1.21 86 23.92***
18 3.13 1.26 3.63 1.16 86 26.58***
19 2.72 1.17 3.13 1.26 86 22.97***
20 3.23 1.24 3.38 1.21 86 24.86***
Note. POCs = processes of change.
***p < .001.
Stages of Exercise Change
As stated, this study was based on the transtheoretical model for change
(TTM), which places a participant in one of five stages of exercise change with change occurring when the participant moves from a lower to a higher stage(s)
(Prochaska & DiClemente, 1992). Thus, tracking a shift in stage membership was important in order to determine whether any of the interventions worked. As can be seen in Figure 7, there was a shift or movement up through or along the stages of exercise change during the intervention period. Initially there were
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more participants in the three nonaction or nonexercise Stages 1, 2, and 3, which
then shifted toward the action or exercise Stages 4 and 5 after the intervention
period.
The greatest increase in stage membership was seen in Stage 4, the stage where the participant has just started exercising regularly. Stage 1 saw the largest eradication of participants during the intervention period. Recall that those freshmen who started out in Stage 1 were purportedly unaware of the benefits of exercise or did not have the time, motivation, or desire to exercise at all, during the fall term. It was not necessarily true that it was the Stage 1 participants who shifted to Stage 4, but this might be a possible explanation.
35
32 31
30
25 25 24
20 20 18 Preintervention 16 Postintervention 15 15
10 10 9
5
0 Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Stages of Exercise Change Figure 5. Comparison of stages of exercise change in percent, pre- and postintervention (N = 121 and N = 87, respectively). The percentage of participants in each stage is marked at the top of each column.
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As before, the t test was utilized in this study to see whether there were
significant changes in stage of exercise change membership postintervention
period. If there was a significant difference in freshmen in the action stages
(which were stages 4 and 5), this would show that an increase in time spent
exercising had taken place. A significant increase in stage 5 membership was
evident. The results are shown in Table 6.
Table 6
One-Sample t Test Between Stage of Change Membership in Pre- and
Postintervention Period
Stage M SD t p 1 9.00 2.83 4.50 .14
2 26.00 1.41 26.00 .02*
3 18.33 2.21 18.33 .04*
4 28.00 12.73 3.11 .20
5 36.50 2.12 24.33 .03*
*p < .05.
To verify that the changes in stage of change membership was significant,
a chi-square analysis was performed to determine whether observed and
expected frequencies were statistically significant for stage of change membership, both pre- and postintervention period. Stages 1-3 are considered
nonexercise stages, in other words, individuals in those stages do not exercise
on a regular basis (meaning 3 or more times per week, 30 minutes or more in
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duration). Stages 4 and 5 are exercise or action stages, where participants are
currently exercising regularly. The results of this analysis can be seen in Table 7.
Table 7
Chi-Square Analysis to Measure Significant Change in Exercise Stage Membership
Stage membership
Time Non Exercise df χ 2
Prea (N = 121) n = 60 n = 61 4 5.405b
Postc (N = 87) n = 32 n = 55 4 15.167** a Pre is the number of participants in nonexercise or exercise stages prior to the intervention period. b p = .248. c Post is the number of participants in nonexercise or exercise stages after to the intervention period **p < .01.
Another question that was answered earlier in the literature with older
populations (Burbank, Reibe, Padula & Nigg, 2002) was, Can gender dictate a
participant belonging to a particular exercise stage of change? This was also
investigated in this study and it was discovered that males were more prevalent
in the “higher” stages (e.g., action stages). More specifically, with this freshman
population there were the most males in stage 5 (see Table 8).
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Table 8
Percent of Stage-of-Exercise Change Membership by Gender
Postintervention Period
Stage
Gender 1 2 3 4 5
Male (n = 34) 3 1 5 12 18
Female (n = 53) 6 9 13 19 14
Note. The percentages listed here are from 100% of the total sample, meaning that the percentages in this table will add up to 100, rather than separating male percentages from female percentages.
Favored Intervention Method
One week after the last intervention survey was administered, an exit survey, a feasibility questionnaire, was given to the remaining 87 participants
(18% attrition rate). The 18% attrition rate was in the middle range of attrition rates previously reported in other proexercise studies; the range of attrition rates reported in the literature as being from 7% to 52% (Junno, 2003; Marcus, Bock, et al., 2002; Russell & Hutchinson, 2000; Titze et al., 2001). Recall that the three intervention methods utilized in this study were (a) the specially created Web site
(www.freshman15.com), (b) colorful posters (point-of-decision prompts), and (c) preprinted pamphlets delivered in the mail.
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A visual representation of the favorability data is presented in Figure 8.
Nearly all the participating freshmen saw the point-of-decision posters and the
Web site (note: they had to see the Web site in order to sign up). Surprisingly,
few admitted seeing (much less reading) the pamphlets. Overwhelmingly, the
point-of-decision posters were the most popular with 85% (71 freshmen) of the
students having read them. Slightly over half (51%) of the freshmen admitted
reading the information presented on the Web site that was related to his or her
respective stage of change. Only a small group, 8 students (17%), actually
utilized the Web site information during the intervention period. Sixty percent (43
students) of the remaining freshmen sample stated that they both read and used
the information posted on the point-of-decision placards, which was slightly
higher than what had been reported in the literature previously (Boutelle et al.,
2001; Coleman & Gonzales, 2001).
A 3x3 chi-square analysis for favored intervention method
generated a statistically significant difference between expected and observed
number of participants (N) assuming all three interventions were each favored by
exactly 33% of the population, p < .001, χ 2 = 64.50 (df = 2). See Table 9 for data set-up and row totals.
100
90 87 84
80
71 70
60
Point-of-Decision 50 Website 44 43 Pamphlets
40
30
20 20
10 8
2 0 0 Saw Read Read and Used Usage Of Each Intervention Figure 6. Headcounts of freshman utilization of the respective interventions. The action taken (x-axis) implies what each student did upon encountering the specified intervention type. Saw means they saw or glanced at it; read means they actually read the information given; read and used means they actually read and then utilized what was suggested.
Table 9
3x3 Chi-Square Test for Significance of Favored Intervention Method
Action taken Read and Intervention type Saw Read used Total
Web site 15 2 1 18
Point-of-Decision 40 3 20 63
Pamphlets 5 1 0 6
Total 60 6 21 87
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The data were further broken down by gender and favored intervention
method. This was done in an attempt to answer the question, Did gender play a
role in which intervention method was favored? As was the case, more females
preferred the Web site, while males seemed to prefer the point-of-decision posters (see Table 10).
Table 10
Percent Favoring Intervention Method by Gender Postintervention Period
Intervention method
Gender Web site Pamphlets P-O-D
Male (n = 34) 10 7 83
Female (n = 53) 30 2 68 Note. P-O-D = point-of-decision posters. Here the percentages are done such that the female sample sums to 100% and the male sample adds to 100%.
To uncover whether stage of change membership possibly dictated the favored intervention method, a frequency table was created (see Table 11).
Curiously, only individuals in Stages 3 or 4 liked the Web site or the pamphlets.
All other stages preferred the point-of-decision posters.
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Table 11
Percent Favoring Intervention Method by Stage of Change Postintervention
Period
Intervention method
Stage Website Pamphlets P-O-D
1 (n = 8) 0 0 100
2 (n = 9) 0 0 100
3 (n = 15) 28 5 67
4 (n = 27) 54 16 30
5 (n = 28) 0 0 100 Note. P-O-D = point-of-decision posters. Each row adds to 100%. N = 87.
Auxiliary Data
Interestingly, the data showed that females who reported being smokers moved up one or two Stages during the intervention period, which was the most movement by any participant group. In other words, female smokers were seemingly more motivated by the interventions than their nonsmoking counterparts (see Table 12).
The discovery that smokers had the least contact with their families was a bit surprising, but perhaps they wanted to keep their habit a secret and thus did not wish to speak to a family member. Smoking might not be an acceptable behavior by a freshman’s family; thus those who smoke may have less contact with any family member because of the conflict over the habit.
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Table 12
Percent of Female Smokers Versus Nonsmokers in Corresponding Stages of
Exercise Change, Postintervention Period
Stage
Tobacco habit 1 2 3 4 5
Smoker (n = 20) 7 9 7 4 11
Nonsmoker (n = 33) 11 4 26 17 4
Note. Smokers and nonsmokers are seen as one group, in other words
100% of the females, thus the percentages in this table sum to 100.
In addition to the results already presented, the exit survey or feasibility
questionnaire revealed some other interesting facts. For example, 41% of the remaining 87 freshmen reported losing weight during spring semester. Another
41% of the population reported staying the same weight during spring semester;
thus 82% of the freshmen avoided gaining any weight after New Year.
Thirty-five percent of the freshmen reported increasing their weekly time
spent exercising by 30 minutes or more, while 30% exercised the same amount of time per week as before and 20% had stopped exercising recently. Only 5% of the remaining 87 freshmen reported not exercising at all.
Nearly half of the remaining freshmen in the sample (47%) reported being their own motivators to exercise, while 20% were motivated by friends or peers, and another 30% were motivated by one or more of the interventions. A family
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member or relative served as a source of motivation for only 3% of the freshmen.
Recall that previous studies reported family being the greatest motivator for
female students in favor of exercising.
Oddly, 86% of the freshmen would recommend the www.freshman15.com
Web site to others. This is a peculiar finding, because only 8 students read and used the information on the Web site (recall Figure 8). Seventy-four percent of the participants were happy they had been a part o this study. Only 2 of the freshmen reported utilizing the free personal counseling that was offered. No freshmen used the free personal training at the gym. This was surprising
because personal training is usually $25 per hour for students.
Based on the presentation and analysis of the aforementioned data, the
freshmen showed a noticeable increase in activity levels after being subjected to
the interventions. It appears that the point-of-decision posters in particular were
converted to positive exercise outcomes when one compares (a) the movement
along the stages, (b) the increased confidence levels, (c) elevated positive
outcome expectations, and (d) increased use of POCs.
A more in-depth discussion of these findings and answers to the questions
posed in the first chapter are contained in the next chapter. The generalized
finding of this study is that the freshmen seemed to respond positively to the
proexercise interventions, with point-of-decision posters being the favored
approach. On all quizzed points, the freshmen excelled and increased their
awareness. As a whole, more than 81% of this sample reported being able to
stop or reduce weight gain during the spring semester.
CHAPTER V
DISCUSSION
The current body of information regarding the freshman 15 acknowledges
the complex and multidimensional nature of this construct, as well as the lack of
a complete understanding of the etiology of related behaviors, such as being
away from home, school stressors, hormones, lack of sleep, group dynamics,
food availability and more. In the present study, I attempted to explore the
comparable patterns of freshman weight gain, lack of exercise, and feasible
intervention methods by surveying a group of college freshmen. Results from this
study show that point-of-decision posters are the preferred method for getting the
freshmen’s attention and thus affecting their behavior patterns (with respect to
exercise habits). Furthermore, the results confirm that freshmen weight gain is
prevalent and needs to be addressed by the institutions. Despite certain
limitations of this study, valuable insight and significant associations were discovered.
Feasibility Questions
This section begins by listing each feasibility question.
1. Which type of proexercise intervention did the freshmen prefer?
95 96
2. Which intervention method worked best?
3. Was there a significant difference between preferred intervention type and
gender?
4. Was there a parallel between the freshmen’s preferred intervention type
and the freshmen’s stage of exercise change?
Answer to Feasibility Question 1. Point-of-decision posters were clearly the
favored intervention method, with the Web site being second favorite and the pamphlets being the least favorite. Furthermore, it was discovered that males
favored the point-of-decision posters more than the females, and while females
liked the posters, they reported using the Web site to a greater extent than the
males. This might be explained by the fact that females usually take longer when
making a decision to do something (like trying a new type of exercise). Females
seemed to like taking their time and studying the information on the Web site
(online role play and use of human models is mentioned as a very positive
feature of Web-based interventions in the literature [Barnanowski et al., 2002;
Robinson et al., 1998]), before they decided to try any new exercises. Males are
usually quicker at deciding whether or not to try out something new (males being
generally more daring and assured), particularly in terms of new exercise tactics
(like those posted by the researcher); thus, they voted in favor of the point-of-
decision posters.
Answer to Feasibility Question 2. Clearly, the preprinted pamphlets did not
work. They were the least favored intervention materials, and none of the
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participants read or utilized the data in these booklets. The Web site was favored
less than anticipated. The researcher believes that if the log on procedure was
modified or even omitted it might make utilization of the Web site increase. The
freshmen complained about the log in procedure, and several participants said it
hindered their use of the Web site completely (not being able to log on or
forgetting their password). This is an area that could lend itself to further study, in
other words, the utilization of personalized log on procedures versus open log on
and increases or decreases in a certain Web site.
Answer to Feasibility Question 3. Male participants seemed to prefer the
point-of-decision posters, based on the fact that males were in higher
concentrations in Stage 5, and Stage 5 participants preferred only the posters.
Female freshmen liked the posters too, but they also utilized the Web site more than the males. The 8 students that reported reading and utilizing the information on the Web site were all females. Females often professed being more visual individuals (during the recruitment period), thus the Web site, which offered
videos and pictures of particular exercises, may have been of more use to female
freshmen who were starting out with their exercise plan. Females are also known
to be more patient than males on average (Smith & Smits, 1994), so needing to
go through a log on process did not deter them from utilizing the Web site for
exercise information.
Answer to Feasibility Question 4. The data showed that only participants
in Stages 3 and 4 were at all interested in any other intervention type other than
the point-of-decision posters. Freshmen in Stages 1, 2, and 5 favored only the
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posters. Freshmen in Stage 4 preferred the Web site the most (54%), the posters second (30%), and the pamphlets the least (16%). Even though the participants in Stage 4 preferred the pamphlets the least, they preferred the pamphlets more than freshmen in any other stage. Two thirds of the Stage 3 participants preferred the point-of-decision posters, while less than one third (28%) preferred the Web site (the remaining 5% liked the pamphlets).
There are numerous explanations to why the breakdown of stage membership is related to the three intervention types in such a way. This author believes the following best accounts for this: Those individuals in Stages 1 and 2 are not currently exercising, therefore logging on to a Web site or reading pamphlets takes too much effort for their liking. They prefer the point-of-decision posters that they can effectively walk right past and ignore, because they are only peripherally interested in exercising. Participants in Stage 5 are already exercising on a regular basis and do not need reminders or tips on how to start exercising, such as those offered on the Web site or in the pamphlets. They prefer the point-of-decision posters that they too can effectively ignore or glance at in passing. That leaves the individuals in Stages 3 and 4.
Stage 3 freshmen are preparing to start a regular exercise program; they are at the point where they want to learn more about exercising, and they seek out information, thus the posters, Web site and pamphlets, in that order, are useful. The posters are the most popular because they are the least threatening; they are short, succinct, and contain exercises that are easily accomplished by someone who is a beginner. The Web site was the second favorite with freshmen
99 in Stage 3 because it contains a wealth of information that helps them learn what to expect in terms of life changes when they finally do decide to exercise on a regular basis. Remember, Stage 3 persons have not started exercising regularly, only randomly. The pamphlets are preferential after everything else, only because they contain information that can supplement the two aforementioned interventions, but they are likely viewed as the most boring.
Stage 4 freshmen have just started exercising, so it is an activity that is new and exciting to them. These freshmen may have a hard time figuring out what sort of exercises to do or how to motivate themselves to continue exercising. One of the pitfalls for those in Stage 4 of exercise change is having the motivation to continue. The Web site offered a multitude of exercises and suggestions to help the participants maintain an exercise plan, which might explain why Stage 4 freshmen favored the Web site over the two other interventions.
Theoretically Based Research Questions
1. Was there an association between gender and a specific stage of exercise
change?
2. Was there a connection between smoking and a specific stage of exercise
change?
3. Was there a relationship between previous level of exercise (in high
school) and amount of fall weight gain?
100
4. Was there a significant difference in stage of exercise change
membership pre- and postintervention period?
5. Was there a difference in weight gain after fall semester, then following
spring semester?
6. What was the primary mechanism that motivated freshmen to exercise
during spring semester?
7. Was there a significant difference in confidence and outcome expectation
levels pre- and postintervention period?
8. Was there a significant difference in levels of processes of change (POCs)
use pre- and postintervention period?
Answer to Research Question 1. Males outnumbered females (percentage wise) in Stage 5 only. Females were predominant in Stages 1, 2, and 3 preintervention, then Stages 2, 3, and 4 postintervention. This implies that more males exercised on a regular basis and had been exercising for the past 6 months. This might be explained by what has been declared in previous studies regarding social support and exercise (DeVoe et al., 1998; Henderson, 2001).
Males glean support in favor of exercising from their peers, making college the ideal place for them to start (or continue) exercising regularly. Females glean their support in favor of exercising primarily from family members, making college a difficult place for them to start or to continue an exercise program because they are separated from their families. In essence the data did show a difference in gender and exercise stage membership. Males were found in higher
101
concentrations on the upper stages implying that male freshmen exercised on a
more consistent basis than females.
Answer to Research Question 2. As shown in Table 12 in chapter 4, the
majority of smokers (postintervention period) were in Stage 5. This is a peculiar
finding because individuals in Stage 5 have been exercising regularly for more
than 6 months. Usually it is uncommon to find people who exercise regularly and smoke at the same time, but that is what this result indicates. One possible explanation to this may be found in a comment that was told to the researcher during the recruitment period, which was, “If you were handing out cigarettes, you would get a lot more people signing up for your study.” Smoking is a form of appetite suppression; it alters the metabolism and gives the sensation of lessening hunger. It is speculated by the researcher that those who reported being in Stage 5 and who also were smokers were females who used smoking to control their weight. This is simply a speculative guess and is clearly an area where more research is warranted.
Answer to Research Question 3. The data showed that those who gained between 1 and 10 pounds during the fall semester were predominantly on a sports team in high school. This might be explained one of four (or more) ways.
Either the active student(s) simply stopped exercising at the end of high school
because they were only doing it to please their parents and therefore gained
weight. Or these freshmen were on a team in high school and once they got to
college did not qualify for an intercollegiate or intramural team and, in despair,
started eating the same or greater amounts and exercising less. Perhaps when
102
on a sports team in high school the student(s) had a good coach or had friends
on the team, but when transferring to college and not being on a team or having any friends to train with, it became too difficult to self-motivate to continue a regular exercise program. The last explanation might be that those who were on a sports team in high school simply did not want to compete any longer and stopped training, but maintained their competitive eating habits, which led to the
1-10 pound weight increase.
Answer to Research Question 4. Because this study was based on the transtheoretical model (TTM), tracking the changes in stage membership numbers was important. Stage 1 showed an 11% drop in members from pre- to postintervention. This implies that 11% of the individuals who reported “not being interested in starting an exercise program whatsoever” managed to motivate themselves to find out more (e.g., not dismiss exercise entirely). Stage 2 showed a 5% drop in membership, meaning that although 11% of the individuals came over to Stage 2 from Stage 1, an additional 5% went from Stage 2 to Stage 3.
Individuals in Stage 2 are aware of the benefits of exercising, but do not have the time or motivation to follow through. Stage 3 saw a 6% decrease in membership numbers, again indicating that in addition to the individuals coming up from Stage
2, another 6% went from Stage 3 to Stage 4.
The interchange between Stages 3 and 4 is important because that is when the individual goes from being active sporadically to committing to a regular exercise program, meaning exercising 3 or more times per week, 30 minutes or more each time. Stage 4 saw the largest increase in participants, with a 15%
103
jump in membership numbers. This means that after the intervention period, 31%
of the remaining 87 participants were in the beginning stages of exercising regularly. This was far greater than expected. Lastly, Stage 5 saw a 7% increase
in membership numbers. These individuals had to have been exercising on a
regular basis prior to the intervention period and hit the 6-month mark of their
regular exercise program thus “graduating” them up to Stage 5. These individuals
would not have been very affected by the interventions, as they were already
exercising months before this study. Needless to say a jump in percentages in
stage 5 is still a positive finding.
Answer to Research Question 5. After the fall semester 59% of this
sample of freshmen self-reported having gained 5 lbs or more. Interestingly, over
half of those (30% of those 59%) had gained over 10 pounds, making them well
on their way to making the freshman 15 by spring. After the intervention period,
the remaining participants were polled regarding their spring semester weight
gain. Surprisingly, 81% of the students had stayed the same weight or lost
weight. This was a remarkable change from the fall semester weight increases.
Unfortunately, all weight gain or loss was self-reported, which is a method that
can be unreliable for determining weight changes. Actually weighing the students
would have been far more desirable and was included in the planning stages of
this study. Due to restrictions enforced by the dormitory staff, it became
impossible for the researcher to follow through with the idea of weighing each
freshman. This is a drawback with this study, and measurements of actual weight
should be included in similar studies in the future.
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Answer to Research Question 6. Postintervention period, nearly half
(47%) of the freshmen reported motivating themselves to exercise for the most
part. Another 20% were motivated by peers or roommates, some 30% were
motivated by this intervention study, and only 3% reported being motivated by
family members. These numbers were a bit unexpected because previous
research had stated it was likely freshmen would be motivated the most by
peers, roommates, or family members. This question may have been a bit
ambiguous because if a freshman determined to start exercising based on some
of the information from the interventions, yet he or she went alone to train, then
that freshman may have answered “I motivated myself” (based on being alone during the training period). This is purely a speculation, but it is a possibility making this quiz question a bit unclear, implying that this question likely did not have solid reliability.
Answer to Research Question 7. The postintervention data and the t test results showed that there was indeed a significant increase in confidence levels and outcome expectations suggesting that the interventions were successful.
Confidence level answers given by the freshmen went from not at all confident up to very or extremely confident. Outcome expectation answers given by the freshmen rose from strongly disagree to agree or strongly agree over the course of the intervention period. These results imply that one or more of the interventions helped elevate the freshmen’s self-confidence levels and their outcome expectations in favor of exercise, thus the time spent exercising. An increase in an individual’s confidence levels and outcome expectations indicates
105
an increase in time spent exercising (Baranowski et al., 2002; Dunn & Marcus,
2001). An increase in time spent exercising likely means a decrease in weight
gained, which was the purpose of this intervention study.
Answer to Research Question 8. Nearly all of the POCs questions had an
increase from never or seldom to frequently. Recall that POCs are strategies that
people use to help them remember to exercise the next day or later in the week
or at a certain time. If the freshmen were reminding themselves more, this likely
indicates an increase in time spent exercising. These increases were shown to
be statistically significant via the t test results. This demonstrates that the
freshmen were effectively using the ten processes of change to a greater extent
after the intervention period. An increase in the use of the POCs indicates an escalation in time spent exercising (Marcus & Forsyth, 2003), which was a goal
of this study.
In general, an increase in confidence levels, outcome expectations, and
processes of change utilization was a major success of this study as it, in
essence, suggested that the participants were spending more time being active.
Similarly, the decrease in freshman weight gain during spring semester, although
self-reported, was of central importance. Even if some of the plans of the study
were altered, ideas were changed, or results were different than anticipated, the study had some key findings that can be utilized and translated into positive ideas to help future freshmen.
106
Further Reflection
When socializing with the freshmen, it was observed by the researcher
that some of the participants appeared to be remarkably needy. These students
seemed in need of attention and someone to listen to them. When at the
dormitory to hang up point-of-decision posters or when recruiting students for this
study, the researcher was often overrun with students who had questions
regarding the study: When was the next time the researcher would be available,
what could be expected further, and what should they be doing next if they were
on Stage 2 or 3 or 4. This type of needy behavior made this researcher wonder
whether perhaps some of the freshmen signed on to be in the study for attention-
getting purposes only, and thus were not at all interested in weight loss, exercise, or stages of change. Or perhaps they signed on to get attention and started
exercising only to see if they could go up a stage or do better than a friend or
roommate. Unfortunately, this is not something this researcher was able to
formally assess, but it needed to be mentioned here.
Not all of the freshmen started an exercise program, but the shift from
nonexercising (nonaction, Stages 1, 2, and 3) stages to exercising stages (4 and
5) was found to be significant. Closely related to the increase in stages of
exercise change was the finding that 81% of the participants stayed at the same
weight or lost weight during the spring semester.
As mentioned, freshmen who admitted to being smokers reported gaining
the least weight, some even lost weight, during the fall semester. This might not
be surprising, because smoking is generally an appetite suppressant and it can
107
alter metabolism. Students who worked part or full time outside of school
generally gained less weight, likely explained by the fact that when students are
at work, they are doing something other than eating or lounging around.
Limitations
It was impossible to take into account all variables that can lead to
freshman weight gain. Not weighing each participant pre- and postintervention
was a serious drawback to this study. Self-reported weight is subject to large discrepancies. The same can be said for self-reported time spent exercising. In order to please the researcher, it is plausible that students answered as they thought would be acceptable (much like the Hawthorne effect or other expectancy effects).
The distribution of the stages of exercise change pamphlets was a bit challenging. The researcher was not permitted access to the upper floors of the dormitory or to the participating freshmen’s respective rooms and was, therefore, forced to distribute the pamphlets via campus mail. It is unknown whether all
participants actually received the pamphlets, or even if they were placed in the
correct mail slots. The seeming unpopularity of this last introduced intervention type may well be explained by this discrepancy. Furthermore, all students who have an on-campus mailbox receive overwhelming amounts of advertisements, fliers for upcoming events, campus newspaper, and so forth, making a freshman’s mailbox a veritable black hole for intervention materials.
108
The absence of a comparison group is a further limitation of the study. The
secondary dormitory that was pegged to be the control group was at the last
minute changed to an all-student dormitory, which meant that not only freshmen
were in residence there. The previous semester the dorm had been only
freshmen, but due to construction, this was changed for Spring 2003. This
secondary dorm was given the preintervention quizzes, but when the researcher
realized that not all the students were freshmen, it was decided by the committee
that this was no longer an appropriate control group.
Getting freshmen to enroll turned out to be a part of the study that took far longer and was more tedious than predicted. The researcher was forced to purchase prizes and gifts for the participants to encourage them to sign up. It was also necessary for the researcher to go to the dormitory with a laptop, and monitor that the participants actually created an account on the Web site because so few logged on by themselves. This is a limitation because only during the recruitment phase (prior to the enrollment period) did the researcher have access to all freshmen. After classes were in session, the researcher’s access to the dormitory was very limited. Because of restricted access only those freshmen who walked through the lobby on the three nights of the enrollment period had an opportunity to receive a prize and log on with assistance from the researcher. Others were required to create a log on and complete all the surveys alone.
The entry and exit questionnaires were only cursorily pilot tested using graduate students, thus the internal and external validity of these surveys could
109
be in question. Because this was a feasibility study, these surveys were used
primarily to gather information, such as demographic data, favored intervention
method, self-reported weight, time spent exercising, etc. and the Cronbach’s
reliability coefficients were not taken into account.
One variable that was purposely omitted from this study was food and
eating habits. Eating disorders or abnormal relationships with food are often
initiated in college. This was too large a variable to take on in conjunction with the others included in this study, so food consumption, caloric intake, eating
patterns, and snacking were not included as variables that can lead to the
freshman 15. This is clearly another area for further study. The researcher’s
contact, the resident assistants, at the dormitory did mention the unhealthy types
of foods that are offered at this university’s dining hall and that many of the
freshmen are on a meal plan that allows them huge quantities of food three times
daily. This is clearly an issue of freshman weight gain that could be researched
further. Serving sizes and caloric intake in relation to weight gained in college is
another research idea that should be considered for the future.
Some freshmen complained of difficulty logging on to the Web site. It was
brought to the researchers attention that the login procedure was tedious and often not working. The Web site was hosted on the University’s faculty account, which experienced a multitude of problems throughout the spring and summer semesters. The University changed from one type of e-mail and Web site hosting and formatting program to another during this time, causing glitches in the server accessibility, especially during the weekends when the freshmen were most
110
liable to sign on. Although the technology department apologized and, at times,
sent a warning e-mail, this was a serious and unfortunate issue. Future studies
using a similar intervention method should consider omitting rigorous log on
procedures, as this seems to deter young adult students.
It was speculated by the researcher, as a likely explanation for the low
usage of the Web site, that if one or more freshmen wanted to logon and could not, they would soon become tired of trying and forfeit the entire Web site, hance foiling the effectiveness of it. Because so much time was spent creating the Web site, the researcher admits to being disappointed by the low percentage of freshmen who reported taking advantage of it.
Finale
The overarching purpose of this study was to determine which intervention method was favored by freshmen in order to help shape future policy at national universities regarding exercise and freshmen. In order to help combat the freshman 15, the researcher suggested intervening with pro exercise interventions to increase the freshmen’s amounts of weekly exercise, in essence, utilizing exercise as a combatant toward weight gained during freshman year in college. The idea was a good one and did work to a certain extent, but will this help change policy? The answer is uncertain.
The researcher predicted that the Web site would be favored by the freshmen, but it was not. The researcher predicted the intervention materials would motivate the freshmen the most; however, they motivated themselves for
111
the most part. The researcher predicted handing out stage-based pamphlets
would be a good idea, but this was unsuccessful. Offering free counseling and
personal training was unsuccessful as well.
Initially this researcher predicted that very few freshmen were capable of
motivating themselves to start an exercise program during spring semester. The data showed otherwise. Movement along the stages were related to significant
increases in use of POCs, heightened confidence levels, and increased outcome
expectations toward regular exercise. This study has shown that intervening with
proexercise messages that are simple and motivational and based on the TTM make it possible to persuade college freshmen to exercise.
An increase in time spent exercising and a decrease in self-reported
weight gained during spring semester were exhibited from the results of this
study. There was a significant increase in use of POC, in exercise confidence,
and in outcome expectation levels. There was unmistakable movement along the
stages of exercise change indicating that the students were indeed exercising.
Surprisingly, the cheapest intervention method, the point-of-decision posters,
was the most popular. This makes it relatively inexpensive and easy for
universities to implement a pro exercise intervention plan to motivate the
freshmen to exercise and thus prevent the freshman 15.
Many more studies along these lines, i.e. studying student weight gain and
the effectiveness of proexercise interventions are proposed, particularly (a)
studies where the intervention period is extended to include an entire school
year, (b) offering a free health expo to get freshmen more interested from the
112 start, (c) having more free items to give away to enhance participation, and (d) more exciting and fun Web sites which incorporate moving characters and background music, are only a few of the ideas this researcher can suggest.
Policy change will not happen overnight, but if several studies can corroborate their findings about student weight gain and the positive impact of proexercise or healthy lifestyle interventions, guidelines and procedures will eventually be improved.
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APPENDIXES
135
Appendix A
Demographic Data and Chi-Square Testing Set-Up
136
Table A1
Demographic Breakdown of Sample Population by Percent
Male Female Total Grouping (n = 47) (n = 74) (N = 121)
Smokers 22% (10) 64% (47) 47% (57)
Nonsmokers 78% (37) 36% (27) 53% (64)
Working outside of 16% (20) 22% (27) 38% (46) schoola
Current weight gainb 23% (28) 36% (43) 59% (66)
Family contactc 24% (29) 46% (56) 70% (85)
Note. Actual headcount in parenthesis. aWorking outside of school indicates working more than 9 hours per week. bCurrent weight gain refers to a self-reported increase in weight of over 4 lbs. after fall semester. cFamily contact implies communication with a family member two or more times per week (including as often as more than once daily).
138
Table A2
Set-Up of Chi-Square Test For Confidence Quiz Questions (Sample)
Not at all Slightly Moderately Very Extremely Total confident confident confident confident confident Time
Prea Frequency of Individuals Who Answered The Same For 121 Each Answer Choice
Postb Frequency of Individuals Who Answered The Same For 87 Each Answer Choice
Total Column Totals aPre = preintervention. bPost = postintervention.
In the case of the first confidence quiz question the results were as follows: Chi square = 8.738 (df = 4), p = .068.
The same procedure was used on every confidence quiz question to calculate statistical significance of the change in the calculated and expected frequencies of the freshmen’s responses pre- and postintervention. Only the chi- square value, degrees of freedom and the significance is reported in the chapter.
Appendix B
Physical Activity Readiness Questionnaire
139 140
Physical Activity Readiness Questionnaire
Regular activity is fun and healthy, and increasingly more people are starting to become more active every day. Being more active is very safe for most people. However, some people should check with their doctor before they start becoming much more physically active. If you are planning on becoming a lot more physically active than you are now, start by answering the seven questions.
This brief questionnaire will assess your readiness for changing your level of physical activity. If you are between the ages of 15 and 69, the PAR-Q will tell you if you should check with your doctor before you start. Common sense is your best guide when answering these questions. Please read the questions carefully and answer each one to the best of your ability. For each question, select (put an x in the box) either "yes" or "no".
Answers
Questions Yes No
1. Has your doctor ever said that you have a heart condition and that you should only do physical activity recommended by a doctor?
2. Do you feel pain in your chest when you do physical activity?
3. In the past month, have you had chest pain when you were not doing physical activity?
4. Do you lose your balance because of dizziness or do you ever lose consciousness?
5. Do you have a bone or joint problem that could be made worse by a change in your physical activity level?
6. Is your doctor currently prescribing drugs (for example, water pills) for your blood pressure or heart condition?
7. Do you know of any other reason why you should not do physical activity?
I have read and signed the consent form that Linn provided.
From Motivating People To Be Physically Active, by B.H. Marcus and L.H. Forsyth, 2003, p.101.
Copyright 2003 by the American Psychological Association. Reprinted by permission of the authors.
Appendix C
Release Form For Initiating Physical Activity
141 142
To: Physician
From: Linn Caroleo
Re: Release Form for Initiating Physical Activity
The physical activity readiness questionnaire (PAR-Q) is designed to measure a person’s readiness to increase his or her activity level. ______has been unable to pass this required line of questioning and must be cleared by a physician before he/she can continue. Please perform necessary medical testing to determine this patient’s readiness for physical activity. If you deem that this patient is ready to start an exercise program, then please sign and date this physical readiness release form.
Direct any questions regarding this study to Linn Caroleo by e-mail ([email protected]) or by phone (760-822-7616). Thank you for your time.
Blood pressure Height Weight ______
Physician’s Name (PRINT) ______
Physician’s Signature______Date ______
Created by Linn Caroleo.
Appendix D
What Stage Are You In? Quiz
143 144
What Stage Are You In?
We all transform our behaviors by going through stages of change. Maybe you have never walked or exercised on a regular basis, but have been thinking about it recently. Or perhaps you used to work-out in high school, but in college you have not had the time, and now you want to start again. Or maybe you are exercising on a regular basis already. Or was it your New Year's resolution this year to start walking more or start training at the gym?
Before we can give you the information about how to work exercise into your day, it will be important to establish which stage of change you are currently in. The questions below will determine that. Please answer the questions regarding how you feel about exercise at this moment in your life (not how you used to feel, or felt last month, or wish you felt; please be honest).
For each of the following questions, please circle either yes or no. Please be sure to read the questions carefully. Answer as honestly as possible.
Physical activity or exercise includes activities such as walking briskly, jogging, bicycling, swimming, or any other activities in which the exertion is at least as intense as these activities.
1. I am currently physically active. Yes No
2. I intend to become more physically active in the next 6 months. Yes No
Note: Exercising regularly is defined as exercising 3 times or more per week, for a total of 30 minutes (or more) each day.
For example, walking a dog, walking back and forth to class regularly, taking the stairs consistently, doing push-ups and sit-ups during a commercial break on TV, and so on, are examples of regular physical activity.
3. I currently engage in regular physical activity. Yes No
4. I have been regularly physically active for the past 6 months. Yes No
From Motivating People To Be Physically Active, by B.H. Marcus and L.H. Forsyth, 2003, p.68.
Copyright 2003 by the American Psychological Association. Reprinted by permission of the
authors.
Appendix E
Outcome Expectations For Exercise Quiz
145 146
Outcome Expectations for Exercise Survey
The following are statements about the benefits of exercise (walking, jogging, swimming, biking, stretching, or lifting weights). State the degree to which you agree or disagree with these statements by placing an x in the appropriate box.
Answer Choices Neither Strongly Disagree Agree Agree Strongly Exercise... Disagree Nor Agree Disagree
1. Makes me feel better physically.
2. Makes my mood better in general.
3. Helps me feel less tired.
4. Makes my muscles stronger.
5. Is an activity I enjoy doing.
6. Gives me a sense of personal accomplishment.
7. Makes me more alert mentally.
(survey continues)
147
Answer Choices Neither Strongly Disagree Agree Agree Strongly Exercise... Disagree Nor Agree Disagree 8. Improves my endurance in performing my daily activities (such as personal care, cooking, shopping, light cleaning, taking out garbage).
9. Helps to strengthen my bones.
Survey created by Linn Caroleo using as a template, Motivating People To Be Physically Active, by B.H. Marcus and L.H. Forsyth, 2003, p. 88, 93, 113. Copyright 2003 by the American
Psychological Association. Reprinted by permission of the authors.
Appendix F
Confidence (Self-Efficacy) Questionnaire
148 149
Confidence (Self-Efficacy) Questionnaire
Physical activity or exercise includes activities such as walking briskly, jogging, bicycling, swimming, or any other activity in which the exertion is at least as intense as these activities. Select the number that indicates how confident you are that you could be physically active in each of the following situations:
Scale
Not at all Slightly Moderately Very Extremely I Can Continue confident confident confident confident confident Exercising...
1. When I am tired.
2. When I am in a bad mood.
3. When I feel I don't have time.
4. When I am on vacation.
5. When it is raining or snowing.
Survey created by Linn Caroleo using as a template, Motivating People To Be Physically
Active, by B.H. Marcus and L.H. Forsyth, 2003, p. 47, 83, 100. Copyright 2003 by the
American Psychological Association. Reprinted by permission of the authors.
Appendix G
Processes of Change Usage Questionnaire
150 151
Processes of Change Questionnaire
Please answer the questions below by checking the appropriate box. It should take approximately 20 minutes to finish this questionnaire.
Physical activity of exercise includes activities such as walking; running; exercising in a gym; swimming; walking stairs; walking to class; lifting weights; bicycling; using a treadmill; stair-master or elliptical trainer; or any other activity in which the exertion is at least as intense as these activities.
The following experiences can affect the exercise habits of most people (you included). Think of any similar experiences you may currently have (or have had) during the past month, then rate how frequently the event occurred.
How frequently did this occur (this past month)?
Process of Change Ne Se Oc Of Re 1. Instead of remaining inactive, I engage in some physical activity. 2. I put things around in my room to remind me to be active. 3. I make commitments (with myself or others) to be physically active. 4. I reward myself when I am physically active. 5. Warnings about the health hazards of inactivity affect me emotionally. 6. I look for information related to physical activity. 7. I get frustrated with myself when I am not physically active. 8. Some of my close friends might be more physically active if I would. (survey continues)
152
How frequently did this occur (this past month)?
Process of Change Ne Se Oc Of Re 9. I worry that inactivity can be harmful to my body. 10. I have a healthy friend who encourages me to be physically active when I don’t feel up to it. 11. I am aware of more and more people encouraging me to be physically active these days. 12. I feel I would be a better role model to others if I were regularly physically active. 13. I try to set realistic goals for myself rather than set myself up for failure by expecting too much. 14. I think about information from articles and advertisements on how to make physical activity a regular part of my life. 15. I think about the type of person I will be if I am physically active. 16.I remove things that contribute to my inactivity. 17.I have someone who provides feedback (support) about my physical activity. 18. I am the only one responsible for my health, and only I can decide whether or not I will be physically active. 19. When I am feeling tense, I find physical activity a great way to relieve my worries. 20. I notice that more and more Universities are encouraging their students to be physically active, mainly by offering free exercise facilities (gym, pool, aerobics, weights, etc.). Note. Ne = Never; Se = Seldom; Oc = Occasionally; Of = Often; Re = Repeatedly.
Survey created by Linn Caroleo using as a template, Motivating People To Be Physically
Active, by B.H. Marcus and L.H. Forsyth, 2003, p. 66, 91, 111, 112. Copyright 2003 by the
American Psychological Association. Reprinted by permission of the authors.
Appendix H
Shift in Answer Trends on Confidence Survey Questions 1 Through 5
153
40 37 35 35
31 30
25 25 24 22
20 Preintervention 20 19 18 Postintervention
15
11 10
5
0 NAC SLC MOC VEC EXC Could You Be Physically Active When You Are Tired?
Figure H1. Shift in answer trends on confidence survey Question 1. NAC = Not at all confident; SLC = Slightly confident; MOC = Moderately confident; VEC = Very confident; EXC = Extremely confident.
50
45 44
40
35
30 30 29 27 27 Preintervention 25 Postintervention 21 21 20 19
15 14
10 10
5
0 NAC SLC MOC VEC EXC Could You Be Physically Active When You Are In A Bad Mood?
Figure H2. Shift in answer trends on confidence survey Question 2. NAC = Not at all confident; SLC = Slightly confident; MOC = Moderately confident; VEC = Very confident; EXC = Extremely confident.
45
40 40
35 34
31 30 29
25 25 Preintervention 21 Postintervention 20 19 19 17
15
10 7
5
0 NAC SLC MOC VEC EXC Could You Be Physically Active Even When You Feel You Don't Have Time?
Figure H3. Shift in answer trends on confidence survey Question 3. NAC = Not at all confident; SLC = Slightly confident; MOC = Moderately confident; VEC = Very confident; EXC = Extremely confident.
45
40 40 39
35 33
30 28
25 24 23 Preintervention 20 Postintervention 20 19
15
11 10
5 5
0 NAC SLC MOC VEC EXC Could You Be Physically Active When You Are On Vacation?
Figure H4. Shift in answer trends on confidence survey Question 4. NAC = Not at all confident; SLC = Slightly confident; MOC = Moderately confident; VEC = Very confident; EXC = Extremely confident.
45
41 40
35 33
30 27 26 26 25 Preintervention 21 20 20 Postintervention 20
15 15 13
10
5
0 NAC SLC MOC VEC EXC Could You Be Physically Active When It Is Raining or Snowing?
Figure H5. Shift in answer trends on confidence survey Question 5. NAC = Not at all confident; SLC = Slightly confident; MOC = Moderately confident; VEC = Very confident; EXC = Extremely confident.
Appendix I
Shift in Answer Trends on Expectation Survey Questions 1 through 9
157
45 42 41 40
35 33
30
26 25 23 22 22 Preintervention Postintervention 20
15 14
10 10 9
5
0 SD D N A SA Exercise Makes Me Feel Better Physically.
Figure I1. Shift in answer trends on expectation survey Question 1. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
50
45 43
40 37
35 33
30
Preintervention 25 24 Postintervention 22 21 20 19 17
15 14 12
10
5
0 SD D N A SA Exercise Makes My Mood Better In General.
Figure I2. Shift in answer trends on expectation survey Question 2. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
60
51 50
40 37
Preintervention 30 27 Postintervention 26 24
20 20 20 17
13
10 7
0 SD D N A SA Exercise Makes My Mood Better In General.
Figure I3. Shift in answer trends on expectation survey Question 3. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
50
45 43
40 37
35 33
30
Preintervention 25 24 Postintervention 22 21 20 19 17
15 12
10
5
0 0 SD D N A SA Exercise Makes My Muscles Stronger.
Figure I4. Shift in answer trends on expectation survey Question 4. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
45
41 40
35 34 33
30 29 29
26 25 Preintervention Postintervention 20 17
15 12 11 10 10
5
0 SD D N A SA Exercise Is An Activity I Enjoy Doing.
Figure I5. Shift in answer trends on expectation survey Question 5. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
50
45 45
40
36 35
30 28
25 Preintervention 25 23 Postintervention 22
20 18 17 15 15 13
10
5
0 SD D N A SA Exercise Gives Me a Sense Of Personal Accomplishment.
Figure I6. Shift in answer trends on expectation survey Question 6. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
60
55
50
40 37
Preintervention 30 28 Postintervention 26
20 19 19 16 15 14 13
10
0 SD D N A SA Exercise Makes Me More Alert Mentally.
Figure I7. Shift in answer trends on expectation survey Question 7. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
40 37 36 35 34
31 30 29
25 22
Preintervention 20 Postintervention
15 15 14 12 12
10
5
0 SD D N A SA Exercise Improves My Endurance In Performing My Daily Activities.
Figure I8. Shift in answer trends on expectation survey Question 8. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
40 38
35 35
30 29
26 25
20 20 20 Preintervention 20 19 18 Postintervention 17
15
10
5
0 SD D N A SA Exercise helps To Strengthen My Bones.
Figure I9. Shift in answer trends on expectation survey Question 9. SD = strongly disagree, D = disagree, N = neutral, A = agree, SA = strongly agree.
Appendix J
Frequencies of Participant Responses on Processes of Change Quiz
Questions 1 through 20
163
40
36 35 34 34
30 28 27
25 23 23 21 Preintervention 20 Postintervention
16 15
10
5
0 0 Never Seldom Occasionally Often Repeatedly Instead Of Remaining Inactive, I Engage In Some Physical Activity.
Figure J1. Frequencies of participant responses on processes of change quiz Question 1. Never was not chosen by any participants on the postintervention quiz therefore a 0 is placed there.
40 38
35 33 31 30
25 25 24 24 24
Preintervention 20 19 Postintervention
15 15
10 9
5
0 Never Seldom Occasionally Often Repeatedly I Put Things Around In My Room To Remind Me To Be Active.
Figure J2. Frequencies of participant responses on processes of change quiz Question 2.
45
40 40 39
35
30 27 26 25 23 22 Preintervention 20 Postintervention 20 18 17
15
10 10
5
0 Never Seldom Occasionally Often Repeatedly I Make Commitments (With Myself Or Others) To Be Physically Active.
Figure J3. Frequencies of participant responses on processes of change quiz Question 3.
45
40 39 38
35
30 29 28 26 25 23 Preintervention 20 Postintervention 20
15 15 13 11 10
5
0 Never Seldom Occasionally Often Repeatedly I Reward Myself When I Am Physically Active.
Figure J4. Frequencies of participant responses on processes of change quiz Question 4.
40 38
35 34 33 32
30
25 25 23
Preintervention 20 Postintervention 17
15 14 13 13
10
5
0 Never Seldom Occasionally Often Repeatedly Warnings About The Health Hazards Of Inactivity Affect Me Emotionally.
Figure J5. Frequencies of participant responses on processes of change quiz Question 5.
60
51 50
40 36 35
Preintervention 30 Postintervention
24 23 22
20 19 19
13
10
0 0 Never Seldom Occasionally Often Repeatedly I Look For Information Related To Physical Activity.
Figure J6. Frequencies of participant responses on processes of change quiz Question 6. Often was not chosen by any participants on the preintervention Quiz, therefore a 0 is placed there.
45 42
40
36 35 35
30 29 27
25 Preintervention Postintervention 20 19 18
15 15
11 10 10
5
0 Never Seldom Occasionally Often Repeatedly I Get Frustrated With Myself When I Am Not Active.
Figure J7. Frequencies of participant responses on processes of change quiz Question 7.
50
46 45 42
40
35
30 28
25 Preintervention 25 Postintervention 22 21 20 17 17 15 15
10 9
5
0 Never Seldom Occasionally Often Repeatedly Some Of My Close Friends Might Be More Physically Active If I Were.
Figure J8. Frequencies of participant responses on processes of change quiz Question 8.
45
41 40 38
35
30 28 28
25 23 Preintervention 21 20 Postintervention 20 18 16 15
10 9
5
0 Never Seldom Occasionally Often Repeatedly I Worry That Inactivity Can Be Harmful To My Body.
Figure J9. Frequencies of participant responses on processes of change quiz Question 9.
50
45 45 42
40
36 35
30 29
Preintervention 25 23 Postintervention
20 18 17 15 15
10 10 7
5
0 Never Seldom Occasionally Often Repeatedly I Have A Healthy Friend Who Encourages Me To Be Active When I Don't Feel Up To It.
Figure J10. Frequencies of participant responses on processes of change quiz Question 10.
40 38
35 35 33
30
25 25 24 24
21 Preintervention 20 Postintervention 17
15 13 12
10
5
0 Never Seldom Occasionally Often Repeatedly I Am Aware Of More And More People Encouraging Me To Be Physically Active These Days.
Figure J11. Frequencies of participant responses on processes of change quiz Question 11.
60
50 49
40 40
35
Preintervention 30 29 Postintervention 25 22
20 17
10 10 8 7
0 Never Seldom Occasionally Often Repeatedly I Feel I Would Be A Better Role Model To Others If I Were Regularly Physically Active.
Figure J12. Frequencies of participant responses on processes of change quiz Question 12.
45
40 39 37 35 35
30 29 28
25 25 Preintervention 20 Postintervention 20
15 14
10 8 7
5
0 Never Seldom Occasionally Often Repeatedly I Try To Set Realistic Goals For Myself Rather Then Set Myself Up For Failure By Expecting Too Much.
Figure J13. Frequencies of participant responses on processes of change quiz Question 13.
45
40 39 38
35 32 30 30
26 25 22 Preintervention 20 Postintervention 20
15 14
11 10 10
5
0 Never Seldom Occasionally Often Repeatedly I Think About Information From Articles And Advertisements On How To Make Physical Activity A Regular Part Of My Life.
Figure J14. Frequencies of participant responses on processes of change quiz Question 14.
45 42
40
35 34
30 29
25 25 24 23 Preintervention Postintervention 20 19 19
15 14 13
10
5
0 Never Seldom Occasionally Often Repeatedly I Think About The Type Of Person I Will Be If I Am Physically Active.
Figure J15. Frequencies of participant responses on processes of change quiz Question 15.
50
46 45
40 40
35
30 30
25 Preintervention 25 Postintervention
20 20 20 20
16 15 15
10 10
5
0 Never Seldom Occasionally Often Repeatedly I Remove Things That Contribute To My Inactivity.
Figure J16. Frequencies of participant responses on processes of change quiz Question 16.
45
40 40 39 38
35
30 30
25 24 Preintervention Postintervention 20 19 17 16 15
10 10 9
5
0 Never Seldom Occasionally Often Repeatedly I Have Someone Who Provides Feedback (Support) About My Physical Activity.
Figure J17. Frequencies of participant responses on processes of change quiz Question 17.
60
50 50
40 39
30 Preintervention 30 27 Postintervention 26
21 20 19
15
10 10
5
0 Never Seldom Occasionally Often Repeatedly I Am The Only One Responsible For My Health, And Only I Can Decide Whether Or Not I Will Be Physically Active.
Figure J18. Frequencies of participant responses on processes of change quiz Question 18.
60
50 48
41 40
31 Preintervention 30 Postintervention 24
20 19 20 18 17 17
10 7
0 Never Seldom Occasionally Often Repeatedly When I Am Feeling Tense, I Find Physical Activity A Great Way To Relieve My Worries.
Figure J19. Frequencies of participant responses on processes of change quiz Question 19.
45
41 40
35 34
30 29 27
25 23 Preintervention 21 20 Postintervention 20 19
15 15 13
10
5
0 Never Seldom Occasionally Often Repeatedly I Notice That More And More Universities Are Encouraging Their Students To Be Physically Active, Mainly By Offering Free Exercise Facilities.
Figure J20. Frequencies of participant responses on processes of change quiz Question 20.