Citation
Social physique anxiety and other factors related to the adoption of exercise in mid-life women

Material Information

Title:
Social physique anxiety and other factors related to the adoption of exercise in mid-life women implications for primary care
Creator:
Brown, Dana Lynn Beall ( author )
Language:
English
Physical Description:
1 electronic file (117 pages). : ;

Subjects

Subjects / Keywords:
Body image in women ( lcsh )
Exercise for women ( lcsh )
Exercise -- Health aspects ( lcsh )
Genre:
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Review:
Exercise is one of the most beneficial activities or physical and mental health yet a great percentage of Americans do not engage in enough exercise or are sedentary. As a whole, women tend to exercise less than men across the lifespace and exercise decreases during middle age. For women, this is a particularly important time considering that the physiological changes accompanying menopause can result in weight gain and put women at a higher risk for chronic illnesses. The majority of exercise interventions have been conducted within primary care setting and many are based on Motivational Interviewing techniques (Miller and Rollnick, 2002) and the Transtheoretical Model (Prochaska and DiClimente, 1982, 1983). There have been mixed finding with respect to the effectiveness of these interventions suggesting that more information is needed about the barriers to exercise that middle-age women experience. One barrier that has been identified as particularly salient for women is Social Physique Anxiety (SPA). SPA refers to anxiety about the evaluation of one's physique by others and has been negatively correlated with exercise in women (Lantz, Hardy, and Ainsworth, 1997). This study tested the relationship between SPA and related variables (self-efficacy, affect, and BMI) at different stages of change in an online sample of 140 midlife women between the ages of 35 and 55. Data were analyzed using a MANOVA with a polynomial contrast to test for a curvilinear relationship between the stages of change for exercise and SPA. Results revealed significant differences in SPA, self-efficacy, Positive Affect, and BMI between the stages of change. A cubic relationship with SPA was confirmed; SPA was significantly higher in the precontemplation and preparation stages compared to the maintenance stage. Knowledge of how these variables relate to the various stages of change may help practitioners anticipate and address barriers to exercise in mid-life women more effectively.
Thesis:
Thesis (Ph.D.)--University of Colorado Denver.
Bibliography:
Includes bibliographic references.
System Details:
System requirements: Adobe Reader.
General Note:
Department of Psychology
Statement of Responsibility:
by Dana Lynn Beall Brown.

Record Information

Source Institution:
University of Colorado Denver
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
903696242 ( OCLC )
ocn903696242

Downloads

This item is only available as the following downloads:


Full Text

PAGE 1

i SOCIAL PHYSIQUE ANXIETY AND OTHER FACTORS RELATED TO THE ADOPTION OF EXERCISE IN MID-LIFE WOMEN: IMPLICATIONS FOR PRIMARY CARE by DANA LYNN BEALL BROWN B.A., University of Arizona, 1994 M.A., University of Colorado Denver, 2007 M.A., University of Colorado Denver, 2012 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy Clinical Health Psychology 2015

PAGE 2

ii This thesis for the Doctor of Philosophy degree by Dana Lynn Beall Brown has been approved for the Clinical Health Psychology Program by Kevin Masters, Chair Barbara Walker, Advisor Rick Gardner Krista Ranby Colleen Conry June 24, 2014

PAGE 3

iii Brown, Dana Lynn Beall (Ph.D., Clinical Health Psyc hology) Social Physique Anxiety and Other Factors Related t o the Adoption of Exercise in Mid-Life Women: Implications for Primary Care Thesis directed by Clinical Professor Barbara Walke r ABSTRACT Exercise is one of the most beneficial activities f or physical and mental health yet a great percentage of Americans do not engage in enou gh exercise or are sedentary. As a whole, women tend to exercise less than men across the lifespan and exercise decreases during middle age. For women, this a particularly important time considering that the physiological changes accompanying menopause can re sult in weight gain and put women at a higher risk for chronic illnesses. The majority of exercise interventions have been conducted within primary care settings and man y are based on Motivational Interviewing techniques (Miller & Rollnick, 2002) a nd the Transtheoretical Model (Prochaska & DiClemente, 1982, 1983). There have b een mixed findings with respect to the effectiveness of these interventions suggesting that more information is needed about the barriers to exercise that middle-age women expe rience. One barrier that has been identified as particularly salient for women is Soc ial Physique Anxiety (SPA). SPA refers to anxiety about evaluation of oneÂ’s physiqu e by others and has been negatively correlated with exercise in women (Lantz, Hardy, & Ainsworth, 1997). This study tested the relationship between SPA and related variables (self-efficacy, affect, and BMI) at different stages of change in an online sample of 1 40 mid-life women between the ages of 35 and 55. Data were analyzed using a MANOVA wi th a polynomial contrast to test for a curvilinear relationship between the stages o f change for exercise and SPA. Results

PAGE 4

iv revealed significant differences in SPA, self-effic acy, Positive Affect, and BMI between the stages of change. A cubic relationship with SP A was confirmed; SPA was significantly higher in the precontemplation and pr eparation stages compared to the maintenance stage. Knowledge of how these variable s relate to the various stages of change may help practitioners anticipate and addres s barriers to exercise in mid-life women more effectively. The form and content of this abstract are approved. I recommend its publication. Approved: Barbara Walker

PAGE 5

v ACKNOWLEDGEMENTS This study was possible because of the tremendous d edication of my advisors, committee members, and department. I am extraordin arily grateful for the support, involvement, and guidance of my advisors, Drs. Rick Gardner, Barbara Walker, and Abbie Beacham. Each of you played a unique and ess ential role in the conception, design, and completion of this project. I am most appreciative of the participation of my committee members, Drs. Kevin Masters, Krista Ranby Colleen Conry, and Elizabeth Allen. Your effort and advice for this project was significant. Finally, thank you to the University of Colorado Denver Psychology Department and Dr. Peter Kaplan for the financial support for this study.

PAGE 6

vi TABLE OF CONTENTS CHAPTER I. INTRODUCTIONÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…..Â…Â…Â…Â…Â…Â…Â… 1 II. REVIEW OF THE LITERATUREÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… ...Â…Â…Â… 4 Definition and Benefits of ExerciseÂ…Â…Â…Â…Â…Â… Â…Â…Â…Â….Â…Â…Â…Â…Â…Â…Â… .Â… 4 Women and ExerciseÂ…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â… Â…Â…Â…Â…Â… .. 7 Role of Primary Care in ExerciseÂ…Â…Â…Â…Â…Â…Â…Â…Â… Â…...Â…Â…Â…Â…Â…Â…Â… ..Â… 8 Stages of ChangeÂ…Â…Â…Â…Â…Â…Â… Â….Â…Â…Â…Â…Â…Â… Â…Â…Â…Â…...Â…Â…Â…Â….Â…Â… 12 Social Physique AnxietyÂ…Â…Â…Â…Â…Â…Â…Â…..Â…Â…Â…Â…Â…... Â…Â…Â…Â…Â…Â…Â…Â… 14 Self-efficacy and ExerciseÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â… ...Â…Â…Â…Â…Â…Â…Â…Â… 18 Affect and ExerciseÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…..Â…Â…Â…Â…...Â…Â… Â…Â…Â…Â…Â…Â… 20 BMI and ExerciseÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â… Â…Â… 22 Literature SummaryÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… Â… 23 III. METHODSÂ…Â… Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… ..Â…. 26 ProcedureÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… ...Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â… 26 ParticipantsÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â… 27 MeasuresÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… Â…Â… .Â…Â…Â…..Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â… 28 IV. RESULTSÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â….Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â… 34 DemographicsÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â… ...Â…Â… 34 Statistics for Overall SampleÂ…Â…Â…Â… Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â… 35 Comparisons Across the Stages of Change Â…. Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â… 36 V. DISCUSSIONÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â…Â…Â…Â… ... 43 LimitationsÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… .Â….. 50

PAGE 7

vii Clinical and Research Implications………………………………………… .…… 52 REFERENCES………………………………………..…………...…………………… 56 APPENDIX A. Informed consent and agreement to be in study…… ………………… ….… 71 B. Demographics and study qualification questions ……… ..….....…………… 74 C. Stages of Change – Short Form…………………………………………… .. 76 D. Barriers Specific Self Efficacy Scale (BARSE)… …………………………. 77 E. Social Physique Anxiety Scale (SPAS)………………………… …………. 82 F. Positive and Negative Affect Scale (PANAS)………… …………………... 85 G. Questions about exercise frequency and duration ……………...………… .. 89 H. Questions about interest in exercise activitie s…………………………… .... 91 I. Questions about likelihood of participation in exercise…………………..... 92

PAGE 8

viii LIST OF TABLES TABLE 1. Participant demographicsÂ…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…Â…Â…Â…Â… .Â…...... 93 2. Mean standard values for Social Physique Anxiety (SPA), Self-efficacy, Positive Affect (PA), Negative Affec t (NA), and BMI for the five stages of change for exercise. Â…Â…Â…Â…..Â…Â…Â…Â… ......Â… 94 3. Analyses of variance comparing mean differences in SPA, self-efficacy, PA, NA, and BMI across the five stages of change for exerciseÂ…Â…Â…Â…. .Â…Â…Â…Â….....Â…..Â…...Â… 95 4. SheffeÂ’ post-hoc comparisons for differences in SPA between the stages of change for exerciseÂ…Â…Â…Â…Â…Â…Â…Â…Â… Â…Â….Â…Â…...Â… 96 5. Number of participants classified into the stag es of change compared to actual stage membership using SPA as a singular predictor variable. Percentages represent accuracy or correct classificationÂ…Â…Â…Â…Â…Â… Â…Â…Â…Â…...Â…Â…...Â… 97 6. Number of participants classified into the stag es of change compared to actual stage membership using self-efficacy as a singular predictor variableÂ…Â…Â…Â… ..Â…Â…Â…Â…Â…Â….............. 98 7. Number of participants classified into the stag es of change compared to actual stage membership using both self-efficacy and SPA as predictor variablesÂ…Â…Â…Â…..Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â…....... 99 8. SheffeÂ’ post-hoc comparisons for self-efficacy between the stages of change for exerciseÂ…Â…Â…Â…..Â…Â…Â… Â…Â…Â…..Â…......Â… 100 9. SheffeÂ’ post-hoc comparisons for PA between the stages of change for exerciseÂ…Â…Â…Â…..Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â… ......Â… 101 10. SheffeÂ’ post-hoc comparisons for BMI between the stages of changeÂ…Â…Â…Â…..Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…......Â… 102 11. Analyses of variance comparing mean differences in exercise preferences for company and location across the fiv e stages of change.....Â….... 103

PAGE 9

ix LIST OF FIGURES FIGURE 1. Mean scores for SPA by stages of change for exercise of precontemplation, contemplation, preparation, action, and maintenanceÂ…Â…Â…Â…Â…Â…Â…Â… Â…Â…Â…Â…Â… Â…Â… 104 2. Mean scores for self-efficacy by stages of change for exercise Â…Â…Â…Â…Â…Â…Â…Â…..Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…...Â… ..Â… 105 3. Mean scores for PA by stages of change for exercise Â…Â…Â…Â…Â…Â…Â….Â…. 106 4. Mean BMI values by stages of change for exerciseÂ…Â…Â… Â…Â…Â…Â….Â….... 107 5. Mean NA scores by stages of change for exe rciseÂ…Â…Â…Â…Â…Â…Â…Â…Â… ... 108

PAGE 10

1 CHAPTER I INTRODUCTION The vast literature demonstrating that regular exer cise is beneficial for physical and mental health is so convincing that it is now w idely considered fact. In spite of this, a large percentage of Americans do not engage in re gular exercise, and women in particular tend to exercise less than men across th e life span (Centers for Disease Control and Prevention, 2014; Martin, Morrow, Jackson, & Du nn, 2000). This is a particularly important issue for women in mid-life who are very likely to benefit from exercise as many struggle with unintended weight gain associate d with pregnancy and numerous hormonal, emotional, and bodily changes associated with menopause. Unfortunately, efforts to increase participation in exercise have not met with overwhelming success. Since health care providers are in a unique position to educate patients and recommend exercise, several studies ha ve focused on interventions delivered within primary care (Eakin, Glasgow, & Riley, 2000; Lawlor & Hanratty, 2001; Pavey et al., 2011). Within this setting, a large percentag e of providers have utilized Motivational Interviewing (MI) techniques (Miller & Rollnick, 20 02) tailored to the stages of change and the Transtheoretical Model (TTM; Prochaska & Di Clemente, 1982; 1983). The TTM provides a structure for understanding the behavior al change process, which includes progression through various stages of change (Proch aska & DiClemente, 1982, 1983). MI is designed to facilitate behavioral changes by addressing motivational issues through a collaborative relationship between the provider a nd the patient (Miller & Rollnick, 2002). There have been conflicting results from th e studies on the effectiveness of MI exercise interventions in primary care (Britt, Huds on, & Blampied, 2004). The mixed

PAGE 11

2 findings suggest more information about how barrier s to exercise specific to mid-life women relate to the stages of change may be useful. One barrier found to be particularly relevant for w omen is Social Physique Anxiety (SPA). Studies have shown a reduced likeli hood of exercise among mid-life women who report high SPA (Hart, Leary, & Rejeski, 1989; McAuley, Bane, Rudolph, & Lox 1995; Ransdell, Wells, Manore, Swan, & Corbin, 1998). Other significant variables related to participation in exercise include self-e fficacy, Positive and Negative Affect and body mass index (BMI). Previous studies have shown that these factors also play an important part in understanding womenÂ’s motivation and participation in exercise. The present study was designed to further explore h ow SPA and several other variables such as self-efficacy, affect, and BMI ar e related to the different stages of change for exercise in mid-life women. Given that the majority of exercise interventions are conducted in primary care settings using MI, th e overarching goal was to gain information that may ultimately contribute to the d evelopment of more targeted and effective exercise interventions for mid-life women in primary care. While the study was not conducted in primary care, efforts were made to capture women who regularly visit primary care providers with the hope of increasing the relevance of study findings to this population in particular.

PAGE 12

3 Study Aims and Hypotheses There were three primary aims of this study. The f irst aim was to explore differences in SPA and other related factors of sel f-efficacy, affect, and BMI between mid-life women in different stages of change for ex ercise. The second aim was to explore whether a curvilinear relationship exists b etween SPA and the stages of change. The third main aim of this study was to assess whet her SPA and related factors are a significant predictor of the stages of change for e xercise. Based on these primary aims, the following hypotheses were formulated: Hypothesis 1 There will be significant overall differences obs erved in SPA, self-efficacy, Positive Affect (PA), Negative Affect (NA), and BMI with respect to the stages of change for exercise. Hypothesis 2 A curvilinear relationship will exist between SPA a nd the stages of change for exercise. Specifically, it was hypothesized that a quadratic relationship would reveal that SPA increases in women as they move from precontemp lation through the preparation stage and decreases as they take action and continu e exercising during maintenance. Hypothesis 3 SPA will be a significant predictor of group membe rship in the five different stages of change for exercise. No specific predict ions were made for the other four variables.

PAGE 13

4 CHAPTER II REVIEW OF LITERATURE Definition and Benefits of Exercise Exercise is defined as, “physical activity that is planned, structured, and repetitive and has a final or an intermediate objective the im provement or maintenance of physical fitness” (Caspersen, Powell, & Christenson, 1985, p .126). The U.S. Department of Health and Human Services (2008) defines health-enh ancing physical activity as moderate to vigorous activity (e.g. brisk walking, jumping rope). There are numerous physical and mental benefits to regular exercise. For example, physical benefits of moderate to vigorous activity include decreased ris k of numerous serious health conditions including obesity, Type 2 diabetes, coro nary heart disease, stroke, breast cancer, colon cancer, and hypertension (U.S. Depart ment of Health and Human Services). There are also numerous mental health benefits rela ted to exercise including an increased ability to effectively manage depression and anxiet y (Paluska & Schwenk, 2000). Using a prospective design, one study (Brown, Ford, Burton, Marshall, & Dobson, 2005) revealed a significant inverse relati onship between physical activity and depressive symptoms in middle-aged women. Dunn, Tr ivedi, Kampert, Clark, and Chambliss (2005) concluded that exercise is an effe ctive treatment for mild to moderate Major Depressive Disorder when performed at the lev el recommended by the American College of Sports Medicine. The relationship betwe en exercise and depression is so strong that even older adults with treatment-resist ant depression showed a 30% decline in depressive symptoms after 10 weeks of increased exe rcise (Mather et al., 2002).

PAGE 14

5 In addition to improving depressive symptoms, exerc ise has also been shown to reduce anxiety. For example, Herring and Jacob (201 1) studied anxiety symptoms in 30 women diagnosed with Generalized Anxiety Disorder a nd found that Resistance Exercise Training (RET) and Aerobic Exercise Training (AET) significantly reduced feelings of anxiety-tension and irritability. Gutierrez and Lu que (2012) also found that six months of moderate intensity exercise significantly reduced s ymptoms of both anxiety and depression in post-menopausal women. Exercise has also been associated with lower risk o f cognitive decline (Yaffe, Barnes, Nevitt, Lui, & Covinsky, 2001; Lytle, Vande rbilt, Pandav, Dodge, & Ganguli, 2004; Weuve et al., 2004). In a prospective study, Yaffe, et al. (2001) found that even moderate levels of physical activity were significa ntly correlated with a lower risk of cognitive decline in women over the age of 65. Ano ther prospective study found that “high” levels of exercise (30 minutes, 3 times per week) in a sample of men and women over 65 was associated with absence of cognitive de cline at two year follow-up (Lytle et al., 2004). Weuve et al. (2004) also found similar results in a large sample (N = 17,766) of women over the age of 65. The prospective study found that higher levels of physical activity were significantly associated with stronge r cognitive functioning. To summarize, the literature is clear that active engagement in exercise is associated with numerous health benefits. In addit ion, it is important to note that studies have also shown that the absence of exercise or sed entary behavior is associated with serious health risks for a multitude of diseases. In fact, only cigarette smoking is a bigger cause of preventable death in the United States (Mo kdad, Marks, Stroup, & Gerberding, 2004). Exercise and physical activity have been fo und to reduce mortality and morbidity

PAGE 15

6 and influence a wide range of physiological and psy chological health conditions (McAuley & Mihalko, 1998). Sedentary individuals t ypically have higher body mass indexes (BMI), which are associated with a higher r isk of Type 2 diabetes, hypertension, and cholesterol levels. Physical inactivity is als o a known risk factor for coronary heart disease due to elevated serum cholesterol and blood pressure (Bouchard, Shephard, Stephens, Sutton, & McPherson, 1990; Powell, Thomps on, Caspersen, & Kendrick, 1987). Given the importance of increasing exercise in the general population, the American College of Sports Medicine (ACSM) has reco mmended four specific types of exercise: cardiorespiratory, flexibility, resistanc e, and neuromotor (Garber et al., 2011). According to the ACSM (Garber et al., 2011), cardio respiratory or aerobic exercise is defined as, “continuous and rhythmic in nature” and involves major muscle groups (p.1336). Cardiorespiratory recommendations are fo r a minimum of 30 minutes, 5 days per week of moderate-intensity exercise or a minimu m of 20 minutes, 3 days per week of vigorous-intensity exercise. Flexibility exercises are designed to improve joint range of movement through stretching major muscle-tendon gro ups to the point of tightness or slight discomfort. ACSM recommends engaging in str etching exercises two days per week and holding each stretch for 60 seconds. Resi stance exercises are intended to improve strength and are recommended 2-3 days per w eek, with varying intensities depending on the experience and strength of the ind ividual. Lastly, neuromotor training targets motor skill development including balance, coordination, agility, and gait and improves physical function and reduces risk of fall s. Examples of neuromotor training

PAGE 16

7 include yoga and tai chi. A minimum of 20-30 minut es, 2-3 days per week of neuromotor training is recommended. Women and Exercise Despite the well-known benefits of regular exercis e, estimates of exercise participation paint a distressing picture. For exa mple, it has been estimated that in 2010 and 2011, only 51.6% of Americans exercised three o r more days per week for a minimum of 30 minutes (Gallup Well-Being, 2012). I t is likely that these estimates may be inflated given that self-report for exercise can be unreliable (Pruitt et al., 2006). Additionally, a significant percentage of individua ls are largely sedentary. A metaanalysis of 71 published studies found that 30% of the total sample identified as inactive or sedentary (Marshall & Biddle, 2001). While many Americans fall short of the exercise rec ommendations put forth by the ACSM, it is noteworthy that women have been fou nd to exercise less than men (Centers for Disease Control and Prevention, 2014; Martin, Morrow, Jackson, & Dunn, 2000). The Centers for Disease Control and Prevent ion (2014) estimate that approximately 10% more men than women meet the 2008 Physical Activity Guidelines for aerobic activity. A similar discrepancy in exe rcise rates between genders was reported by Martin et al. (2000) with 71.4% of fema les compared to 62.9% of males falling short of the CDC/ACSM recommended guideline s for physical activity. Physical activity in women has been shown to declin e with age with the largest decrease occurring after age 50 (Evenson et al., 2002). It is during this mid-life period that many women tend to experience weight gain, which is asso ciated with a loss of muscle mass and decline in metabolic rate (Shangold & Sherman, 1998). According to the Mayo

PAGE 17

8 Clinic (2010), women experience the most weight gai n during perimenopause or the years just prior to menopause and menopausal women exercise less than non-menopausal women. Weight gain during this period has been att ributed to a number of factors including estrogen deficiency, and reduced aerobic power or capacity (Kohrt, 2009). The combination of infrequent exercise and weight gain places women at higher risk for a variety of chronic illnesses such as diabetes, hype rtension, and heart disease (USDHHS, 2008). Osteoporosis is also associated with sedent ary behavior and is a serious medical condition that primarily affects women and involves bone loss in mid-life (Shangold & Sherman, 1998). Coronary artery disease affects bo th men and women as they age, but the risk increases greatly in post-menopausal women as estrogen deficiency leads to adverse lipid and vascular changes (Shangold & Sher man, 1998). Wheras the benefits of exercise are well known for both men and women of any age, mid-life women in particular are in a position to benefit from regular engagement in exercise. Exercise has been shown to prevent weigh t gain during menopausal periods (Kohrt, 2009) and may help with the emotional chang es women experience during this time as well. Role of Primary Care in Exercise It is clear that exercise is extremely beneficial f or health and that sedentary behavior is associated with serious health risks, y et many people in the United States do not exercise regularly. Equally important is the p ossibility that individuals may be unaware of how much exercise is recommended includi ng associated benefits and risks. Primary care providers are in a unique position to provide information about exercise and discuss recommendations because they have establish ed health-focused relationships with

PAGE 18

9 patients they see on a routine basis. As a result of this, the American College of Preventive Medicine published a statement advocatin g for primary care providers to incorporate counseling related to physical activity into routine visits (Jacobson, Strohecker, Compton, & Katz, 2005). According to t he Centers for Disease Control and Prevention NCHS Data Brief (Barnes & Schoenborn, 20 12), in 2010 approximately onethird of adults who had visited a health profession al in the last year were advised about exercise and physical activity, and women were more likely to have been advised than men. Numerous studies have investigated the effect iveness of exercise recommendations and interventions delivered in primary care with mi xed findings (Pavey et al., 2011; Lawlor & Hanratty, 2001; Eakin, Glasgow, & Riley, 2 000). A systematic review by Lawlor and Hanratty (2001) examined the effect of advice regarding physical activity during consultations in primary care. Randomized and nonrandomized studies were included if they: 1) assess ed the effectiveness of advice given by a health professional in a primary care setting, 2) included a control group who did not receive advice regarding activity levels, and 3) ut ilized physical activity as an outcome measure. A total of eight studies with 4,747 parti cipants were selected from four databases (MEDLINE, Cochrane Library, EMBASE, and S port discus). Outcome measures of physical activity varied and included b oth dichotomous (active or not) and continuous (exercise duration) measures. Four of t he studies reported significant increases in physical activity four to six weeks po st-intervention. Four studies presented long-term results measured between eight to twelve months post-intervention. One of the four reported significant increases in activity and one study reported significant odds of increasing exercise. Neither of the randomized con trolled trials reviewed revealed

PAGE 19

10 significant short-term or long-term increases in ph ysical activity. Based on results of their systematic review, the authors concluded that routine consultations delivered in primary care in the United States do not result in meaningful sustained increases in physical activity. However, given that some of the trials reported positive findings, it appears that primary care interventions hold some p romise to influence behavior change and more targeted interventions may increase effect iveness. One of the most effective interventions that has be en found to help people change behavior is Motivational Interviewing (MI; Miller a nd Rollnick, 2002). Miller and Rollnick (2002) describe MI as, “a collaborative, n ot prescriptive, approach, in which the counselor evokes the person’s own intrinsic motivat ion and resources for change” (p. 41). The goal of MI is to utilize clinical techniques an d interviewing skills to partner with individuals to help resolve motivational issues tha t are inhibiting positive behavior change. MI also recognizes that an individual’s re adiness is a significant factor in behavior change, and interventions and techniques a re tailored to each individual based on where they are in the stages of change (Miller & Rollnick, 2002). For example, an individual who is not even considering exercise wou ld receive a different intervention than an individual who acknowledges some benefits t o exercise but is ambivalent about moving forward. A large body of literature has demonstrated that MI is effective in changing a wide range of behaviors (Burke, Arkowitz, & Menchol a; 2003; Dunn, Deroo, & Rivara, 2001; Rubak, Sandboek, Lauritzen, & Christensen, 20 05), so it is not surprising that a large majority of exercise interventions that have been done in primary care have employed MI techniques. After performing an extens ive review of interventions to

PAGE 20

11 promote physical activity, The American Heart Assoc iation concluded that, “there is general consensus that Motivational Interviewing of fers an evidence-based approach for enhancing adherence to behavioral interventions” (A rtinian et al., 2010, p. 426). Rubak et al. (2005) also conducted a systematic rev iew and meta-analysis to evaluate the effectiveness of MI as an intervention in health care settings and found that it was significantly more effective than advice giving to change a variety of health behaviors including increasing physical activity. Harland et al. (1999) also examined the effectiveness of interventions based on MI in an ur ban general medical setting with 523 adults ages 40 to 64. Results suggested that an in tensive MI intervention (six interviews over twelve weeks) was effective at increasing phys ical activity in the short term (after 12 weeks), although improvements were not maintained a t one year follow up. Although several studies have found MI to increase physical activity, it is important to point out that not all studies report positive results. Hillsdon, Thorogood, White, and Foster (2002) found that a “negotiation” intervention based on MI did not lead to greater increases in physical activity when compared to direct advice in 1,658 middle-aged adults. The inconsistency in findings suggests that additional research would be beneficial with respect to effective exerc ise interventions in primary care. In a review of MI in health settings, Britt, Hudson, and Blampied (2004) point out that MI has the potential to be helpful in promoting healthy be haviors such as exercise. However, they suggest that additional outcome research is ne eded in health settings to further understand the relationship between MI and health b ehavior change and its potential as a useful intervention strategy. It is possible that specific techniques used within the MI

PAGE 21

12 framework may be of particular importance with rega rd to exercise interventions in primary care. Stages of Change The Transtheoretical Model (TTM) developed by Proch aska and DiClemente (1982, 1983) has been widely applied to numerous he alth behaviors including exercise (Green, Rossi, Rossi, Velicer, & Fava, 1999; Procha ska, DiClemente, Velicer, & Rossi, 1993; Rodgers, Courneya, & Baybuza, 2001; Rossi, Bl ais, Redding, & Weinstock, 1995). The TTM provides a structure for understanding beha vioral change that includes both verbal and behavioral processes. Verbal processes help individuals prepare to implement a change wheras behavioral processes become relevan t once an individual is committed to action (Prochaska & DiClemente, 1982, p. 276). The model was originally developed following an analysis of processes of change with c igarette smokers who were attempting to quit (Prochaska & DiClemente 1982; Prochaska, Re dding, & Evers, 1997). Prochaska and DiClemente (1983) developed a stage model for c hange with quitting smoking and the model was later applied to a broad range of beh aviors including substance abuse, condom use, eating disorders, obesity, medication a dherence, smoking cessation and pregnancy, avoidance of high-fat diets, and use of sun protection (Prochaska et al., 1997). The stages of change are a central construct in the TTM and include five main stages individuals pass through when implementing i ntentional behavioral change. Stages of change is a model for understanding the g eneral change process and understanding exercise behavior in various populati ons. The five stages of change include: precontemplation, contemplation, preparati on, action, and maintenance (Prochaska & DiClemente, 1983). Prochaska et al. ( 1997) describe the stages in the

PAGE 22

13 following ways: Precontemplation describes individu als who have no intention of changing their behavior within the next six months. People in this stage avoid thinking, reading, or talking about a particular behavior and either may not have information about the consequences of their behavior (or lack thereof ) or may have tried unsuccessfully to change in the past. The contemplation stage descri bes individuals who are considering making a change within the next six months. These individuals typically are weighing pros and cons of change, which can lead to ambivale nce that may be hard to move beyond. The preparation stage describes individual s who are actively planning to make a change in the near future, usually within the next month. These individuals have typically already started to identify and investiga te tools and resources to help them change such as self-help books or consulting with a counselor or physician. The action stage describes when people have successfully made overt behavior change within the last six months. In the maintenance stage, individ uals are maintaining the change in behavior and actively working to reduce relapse. T hese individuals continue to gain confidence in their ability to maintain the change as time passes and this stage is estimated to last from about six months to five yea rs. Successful maintenance with respect to exercise has typically been conceptualiz ed as maintenance of physical activity rather than maintaining abstinence from behaviors s uch as smoking or weight control (Marcus et al., 2000). A sixth stage called termin ation was part of the original model and has been applied primarily to addictive behaviors. This stage refers to individuals who have 100% self-efficacy that they will not return t o old ways of coping. This stage is not typically included in the exercise or physical acti vity literature.

PAGE 23

14 Social Physique Anxiety Social Physique Anxiety (SPA) refers to anxiety abo ut the anticipated evaluation of one’s physique by others (Hart, Leary, & Rejeski 1989). SPA can prompt people to avoid situations in which they fear their body migh t be evaluated, and this has been shown to affect motivation to exercise (Lantz, Hard y, & Ainsworth, 1997). Some individuals with high SPA avoid exercise situations altogether because they fear negative evaluation from others (Hart et al., 1989). SPA is similar to social anxiety disorder or socia l phobia, which occurs when individuals have concerns about embarrassing themse lves in front of others or that others will judge them negatively (American Psychiatric As sociation, 2000). Rapee and Heimberg (1997) developed a model of how anxiety is generated and maintained in social-evaluative situations for individuals with s ocial anxiety. The presence of an “audience” or being in the presence of others is pe rceived as a situation with potential for negative evaluation because the audience is perceiv ed as inherently critical (Turk, Heimberg, & Magee, 2008). Socially anxious individ uals have been found to construct negative, distorted mental representations of how t hey appear (Turk et al., 2008). From a behavioral perspective, anxiety is maintain ed through the avoidance of anxiety-provoking experiences and is eventually red uced when individuals participate in the experiences they fear (Kaplan & Tolin, 2011). In the case of SPA, anxiety-provoking experiences could include exercise situations in th e presence of others. Applying the behavioral perspective to SPA and the stages of cha nge for exercise, one might reasonably expect SPA to be higher in the stages le ading up to participation in the feared

PAGE 24

15 stimulus (exercising in the action phase) and lower in the action and maintenance stages of change. In addition to the behavioral perspective of anxiet y reduction, studies have noted decreases in SPA following exercise interventions ( McAuley, Bane, & Milhalko, 1995; McAuley, Marquez, Jerome, Blissmer, & Katula, 2002; Williams & Cash, 2001). The study by McAuley et al. (1995) demonstrated that a 20 week exercise intervention with 114 previously sedentary middle-aged adults with a mean age of M = 54.52 years ( SD = 5.79) resulted in reductions in SPA predicted by in creases in self-efficacy. Reductions in SPA were also observed in a later study by McAuley et al. (2002) who utilized a randomized contolled trial to evaluate a six month physical activity intervention on SPA in a sample of 174 adults with a mean age of M = 65 years ( SD = 5.35). The authors observed significant reductions in SPA following th e six month intervention and at the six month follow-up. Similarly, Williams and Cash (2001) demonstrated that a six week circuit training program resulted in significant re ductions in SPA in 39 college students compared to controls. Research has identified SPA as a significant facto r in predicting exercise behavior, with several studies focusing on its impo rtance in women (Cumming & Thogersen-Ntoumani, 2011; Diehl, 2001; Eklund & Cra wford, 1994; Lantz, Hardy, & Ainsworth, 1997; Ransdell, Wells, Manore, Swan, & C orbin, 1998). For example, Lantz et al. (1997) examined the relationship between exe rcise and SPA including the effects of age, gender, and depression. The authors predicted that SPA would be inversely related to exercise frequency because individuals with high er SPA may want to protect themselves from situations in which their physiques may be evaluated. Age, gender, and

PAGE 25

16 depression were predicted to moderate the proposed relationship such that older females with higher levels of depression would exercise the least. The study included 320 participants ranging in age from 18 to 60 years old (180 females, 120 males) from two southeastern cities. SPA was measured using the So cial Physique Anxiety Scale (SPAS; Hart, Leary, & Rejeski, 1989). A significant inver se relationship was found between SPA and exercise. Individuals with higher SPA were significantly less likely to exercise, and older women with elevated SPA reported the lowe st level of exercise. Notably, depression did not moderate the relationship betwee n SPA and exercise as originally predicted. Another study exploring the relationship between SP A and physical activity in postmenopausal women age 50 to 79 years also found that SPA was related to exercise (Ransdell, Wells, Manore, Swan, & Corbin, 1998). T his cross-sectional study examined the relationship between leisure time physical acti vity and SPA, age, body fat, and hormone replacement therapy. A total of 164 women with a mean age of 66.3 years ( SD = 7.3) were recruited from newspaper advertisements and senior centers in the Phoenix area. Inclusion criteria were “apparently healthy” women over the age of 50 who had not experienced a menstrual period for over one year. Participants completed questionnaires related to demographic information, SPA, and leisur e-time physical activity. A trained technician completed a body composition assessment that included waist-to-hip ratio, skinfolds, and height and weight measurements, whic h were used to estimate body fat percentage. Findings revealed that women who repor ted low levels of physical activity (<500 kcal/wk) with waist/hip ratios greater than 0 .85 and body fat greater than 37.5% had significantly higher SPA than active women (>20 00 kcal/wk) with less than 37.5%

PAGE 26

17 body fat and a waist/hip ratio less than 0.85. Hor monal status and age were not related to the differences in SPA. Women with an abdominal up per body fat distribution reported more SPA than women with lower fat distribution (gl uteal/thigh). The authors speculate these differences may have been due to the social “ ideal” that promotes small waists and large hips as attractive in women and that there ma y be a more negative psychological profile in women with upper body fat distribution. McAuley, Bane, Rudolph, and Lox (1995) looked at SP A in relation to body composition and exercise in 114 women and men betwe en 45 and 64 years old. With respect to SPA, the older age groups (55 to 64) wer e significantly less anxious than the younger participants (45 to 54). Women had signifi cantly higher SPA compared to men in the sample. The authors also reported that thos e who exercised more frequently had less physique anxiety. Woodgate, Ginis, and Sinden (2003) looked at SPA i n addition to selfpresentation efficacy (SPE) in relation to physical activity in 81 women between the ages of 53 and 84 ( M = 70.9, SD = 6.5). According to the authors, “SPE has been conceptualized as individuals’ confidence in their ability to successfully convey images of being a competent exerciser” (Woodgate et al., 2 003, p.117). Results revealed that SPA significantly predicted physical activity and t hat there was a significant interaction between SPA and SPE. Woodgate et al. (2003) sugges ted that for older women, physical activity is influenced by SPE in addition to SPA. SPA appears to be an important predictor of exerci se behavior in women. Surprisingly, a literature search revealed no studi es to date that have explored how SPA might differ between the various stages of change f or exercise in women. This seems

PAGE 27

18 particularly important to explore since difference in SPA among women in difference stages of change would have several implications fo r interventions. For instance, if SPA is highest while an individual is in the preparatio n phase, it may become a barrier to progression to the action stage unless effectively addressed. The present study aims to build on previous work by replicating findings that SPA is significantly related to exercise in mid-life women. The study seeks to ext end previous findings by examining how SPA may be more or less relevant for women in v arious stages of the change process. Self-Efficacy and Exercise Based on Social Cognitive Theory another factor tha t has consistently been shown to be particularly relevant to exercise behavior is self-efficacy (Bandura, 1986, 1977). Self-efficacy has a direct influence on oneÂ’s choic e of behaviors as well as how much effort one will expend and how long one will persis t despite obstacles and negative experiences (Bandura, 1977). Further, the longer o ne persists in a behavior or activity, the stronger oneÂ’s sense of self-efficacy becomes ( Bandura, 1977). Self-efficacy has consistently been shown to be a s ignificant factor in predicting change in exercise behavior (Calfas, Sallis, Oldenb urg, Ffrench, 1997; Keller, Fleury, Gregor-Holt, & Thompson, 1999; McAuley & Mihalko, 1 998; Sallis, Hovell, Hofstetter, & Barrington, 1992) and it is associated with highe r and sustained levels of physical activity (Purath, 2006; Sullum & Clark, 2000). The re are several ways that self-efficacy can be defined and operationalized including effica cy with respect to barriers, scheduling, task, and coping (Rodgers & Sullivan, 2001). Barri ers to exercise are an important consideration in understanding exercise behaviors a nd can provide useful information

PAGE 28

19 about how to help individuals overcome them (Simona vice & Wiggins, 2008). Studies that have focused on engagement in exercise have ge nerally operationalized self-efficacy as belief in oneÂ’s ability to overcome various barr iers to exercise such as bad weather, boredom with the exercise activity, or an exercise location that is difficult to get to (DuCharme & Brawley, 1995). Hausenblas, Nigg, Symons Downs, Fleming, and Conna ughton (2002) examined self-efficacy with respect to barriers to exercise and stage of change in middle school students. Although the primary purpose of the stud y was to examine concurrent validity of stage of change in this particular age group, th e authors also investigated self-efficacy for barriers to exercise because of its known relat ionship with behavior change and positive relationship with stages of change (i.e., self-efficacy for exercise barriers increases as participants progress from precontempl ation to maintenance). Results were consistent with previous findings; barrier self-eff icacy scores improved at each stage of change. Blanchard et al. (2007) also looked at self-effica cy for overcoming barriers to physical activity as well as self-efficacy for enga ging in physical activity for more than 20 minutes up to 7 days per week for 6 weeks (task self-efficacy). Participants were recruited from a primary care practice and included 120 inactive patients (<150 minutes) ages 18-69 recruited from the community in a primar y care practice. All participants received a brief physical activity intervention and were then randomly assigned to receive further intervention or no intervention. Results su ggested that self-efficacy related to barriers to exercise had a significant sustained re lationship with physical activity.

PAGE 29

20 Simonavice and Wiggins (2008) assessed self-efficac y related to exercise barriers, coping, and task (confidence in one’s ability to en gage in weekly physical activity) in relationship to stage of change for exercise in mal e and female undergraduate students. The authors predicted lower self-efficacy and more perceived barriers in students in the precontemplation, contemplation, and preparation st ages. Measures included the Stages of Exercise Behavior Change (Marcus, Selby, Niaura, & Rossi, 1992), the Barriers section from the Exercise Benefits/Barriers Scale ( Sechrist, Noble Walker, Pender, 1987), and questionnaires developed by the authors related to coping and task self-efficacy. Results revealed that self-efficacy ratings increas ed as the stages of change progressed from precontemplation through maintenance. Results also indicated that earlier stages of change were associated with more perceived barriers Studies in the literature to date have consistently supported self-efficacy as a significant predictor of exercise behavior. Moreo ver, studies have found that selfefficacy related to barriers to exercise is particu larly important and relevant to the stages of change for exercise. Clearly, self-efficacy is an important variable to consider when conceptualizing exercise behavior in an attempt to improve interventions for women. Affect and Exercise Mood has also been identified as a significant fact or influencing exercise behavior. Self-reported mood state is often captur ed in the literature by assessing both Positive Affect (PA) and Negative Affect (NA). Wat son, Clark, and Tellegen (1988) define PA as, “the extent to which a person feels e nthusiastic, active, and alert” (p. 1063). Thus, high PA is characterized by, “high energy, fu ll concentration, and pleasurable engagement” and low levels of PA, with an absence o f “sadness and lethargy” (p.1063).

PAGE 30

21 In contrast, NA is defined as, “a general dimension of subjective distress and unpleasurable engagement” with mood states includin g, “anger, contempt, disgust, guilt, fear, and nervousness” (p.1063). Low NA is charact erized by feelings of “calmness and serenity” (p.1063). Watson et al. (1988) have conc eptualized PA and NA to be independent dimensions of mood rather than opposite s on a continuum. Studies have found significant relationships betwee n PA and NA and exercise factors such as SPA and self-efficacy. For example Ostir, Cohen-Mansfield, Leveille, Volpato, and Guralnik (2003) examined PA and NA wit h respect to self-efficacy and found that PA was associated with self-efficacy wit h respect to exercise in 324 primarily Caucasian community-based participants between the ages of 75-85. Participants were grouped into high performers and at-risk performers based on scores of lower body function and self-reported exercise level. Results revealed that PA was associated with self-efficacy to perform exercise. No significant association was found in the high performance group between exercise self-efficacy an d PA or NA. In the at-risk group, increased PA was associated with increased probabil ity for self-efficacy. Ostir et al. (2003) concluded that improving PA may increase exe rcise participation in older adults. Williams et al. (2008) conducted a longitudinal, o bservational study examining the relationship between affect experienced during moderate-intensity exercise and physical activity participation at 6 and 12 month i ntervals. The 37 healthy, sedentary mostly female Caucasian participants were recruited from a pool of 249 participants enrolled in a randomized controlled physical activi ty trial. Affect was measured before and during a treadmill task that ensured moderate i ntensity exercise. Findings revealed

PAGE 31

22 that PA experienced during moderate exercise was pr edictive of increased physical activity at both 6 and 12 months. Ekkekakis, Lind, and Vazou (2010) conducted a stud y to assess the impact of affect on self-efficacy and SPA in a sample of 50 s edentary middle-aged women of varying weights. The authors also assessed affecti ve responses to exercise of increasing intensity and compared responses between normal-wei ght, overweight, and obese women. All participants completed a treadmill prot ocol that increased speed until the participant reached “maximal effort” determined by various physiological markers such as heart rate and oxygen uptake. Measures of affec t and exertion were recorded once a minute. Results revealed no differences between th e normal-weight and overweight groups with respect to affect or SPA. The obese gr oup reported lower pleasure and energy ratings. SPA was inversely related to both pleasure and energy; the higher the SPA, the lower both pleasure and energy. No relati onship was found between selfefficacy and affect. This study (Ekkekakis et al., 2010) is particularly relevant to the present study as it examined SPA, affect, and selfefficacy in midlife women. The present study explores these relationships in more detail in relation to stages of change for exercise relative to mid-life women with primar y care providers. BMI and Exercise The World Health Organization (2012) defines overwe ight and obesity as, “abnormal or excessive fat accumulation that may im pair health”. Body mass index (BMI) provides a universal measure of combined weig ht and height and is used to classify adult body size into normal and abnormal r anges. BMI is calculated by the formula: (weight in kilograms / height in meters2) or (weight in pounds / height in

PAGE 32

23 inches2) x 703 (Centers for Disease Control and Prevention 2011). Higher BMI has been associated with lower levels of exercise and physic al activity (Petersen, Schnohr, & Sorensen, 2004). There may be numerous explanation s for reduced exercise in individuals with higher BMI such as issues with mob ility or pain. It is also possible that low levels of exercise contribute to weight gain. A longitudinal study conducted by Petersen et al. ( 2004) evaluated the relationship between obesity and physical activity in a sample of 2,626 men and 3,653 women ages 20 to 78 years living in Copenhagen. Th e association between obesity and leisure time physical activity was significant and indicated that the greater the BMI the greater the risk of physical inactivity. Similarly Evenson et al. (2002) examined factors associated with vigorous physical activity in women who participated in the Women’s Health Initiative Observational Cohort Study, which included 71,837 women ages 55 to 79 years. Vigorous physical activity was defined a s exercise where, “you work up a sweat and your heart beats fast” such as in jogging swimming laps, aerobics, etc. Participants assessed activity levels retrospective ly, and findings revealed a clear inverse relationship between BMI and vigorous activity, wit h significantly fewer obese participants reporting vigorous activity. Literature Summary To summarize, exercise is a critical component of g ood physical and mental health. Exercise is a particularly salient issue f or mid-life women, who may be struggling with weight-related issues around the menopausal pe riod. Unfortunately, this group tends to exercise less compared to men and exercise participation decreases with age

PAGE 33

24 (Centers for Disease Control and Prevention, 2014; Martin, Morrow, Jackson, & Dunn, 2000). SPA has been shown to be associated with lower lev els of exercise in women. Understanding more about how SPA relates to the sta ges of change in mid-life women may help health care professionals design and imple ment more informed and targeted interventions. Following their study of predictors of SPA in postmenopausal women, Ransdell, Wells, Manore, Swan, and Corbin (1998) su ggest, “health promotion professionals should be aware of these concerns whe n developing physical activity interventions for postmenopausal women” (p.19). Th e other factors of self-efficacy, PA, NA, and BMI have also been shown to be relevant in this population with respect to exercise. These factors are useful in understandin g the process by which women make a decision to exercise and eventually act on that dec ision illustrated by the stages of change (Prochaska & DiClemente, 1982, 1983). Various efforts to promote exercise have been attem pted by health care providers in primary care settings. Many of the intervention s have utilized Motivational Interviewing techniques incorporating Prochaska and DiClemente’s (1982, 1983) Transtheoretical Model of Change (Eakin, Glasgow, & Riley, 2000; Lawlor & Hanratty, 2001; Pavey et al., 2011). There have been mixed f indings on the effectiveness of exercise interventions based on Motivational Interv iewing (Britt, Hudson, & Blampied, 2004), suggesting it would be useful to gather more information about the relationship between known barriers to exercise in mid-life wome n and the stages of change. As a result, the present study was designed to character ize how SPA and other variables such

PAGE 34

25 as self-efficacy, affect, and BMI relate to the sta ges of change for exercise in this population.

PAGE 35

26 CHAPTER III METHODS Procedure After obtaining approval to carry out the study thr ough the Colorado Multiple Institutional Review Board (COMIRB) at the Universi ty of Colorado Denver, participants were recruited by an academic-based re search organization that facilitates nationwide online social science research. The Stu dy Response Project ( http://www.studyresponse.net/index.htm ) maintains a database of over 55,000 individuals interested in participating in online r esearch. Study Response identified 7,014 potential participants who met the initial st udy criteria of being female, between the ages of 35 and 55, and residing in the United S tates. These individuals were invited by Study Response to answer additional pre-screenin g eligibility questions and 923 women responded to those. Of these, 245 individual s met the elgibility requirements and were invited to participate in the study, which res ulted in 140 participants who completed the study and received payment. Pre-screened participants who were invited to the s tudy were provided with an electronic survey link administered through Researc h Electronic Data Capture (REDCap), a secure web-based application for online data collection (Harris, et al., 2009). Interested candidates followed this web-bas ed link to the website where they accessed an electronic version of the questionnaire Participants were first asked to read an informed consent page describing the purpose and scope of the study. They were then asked to answer a set of questions to confirm volun tary consent and comprehension of the study purpose and related procedures (Appendix A). Comprehension questions included,

PAGE 36

27 “What are you being asked to do in this study?”, “P lease finish this sentence: The purpose of this study is:”, and “True or false: Aft er beginning this study, you can decide not to continue at any time, without penalty.”. Pa rticipants indicated consent by answering the comprehension questions correctly and by choosing the option, “I agree” under “Agreement to be in this study.” Instruction s were provided at the beginning of each survey section and participants were advised t o respond to questions by clicking on the response closest to their preferred answer. Respondents remained anonymous to the researchers t hrough the use of identification numbers assigned by Study Response. Researchers were unaware of personally identifying information such as particip ant name or address. Participants completed the survey online in a setting of their c hoosing and had an unlimited amount of time to complete the survey. The time to complete the survey was not recorded although it is estimated it took approximately 15-20 minutes for most individuals to complete. The researcher sent Study Response the identification n umbers of participants who completed the survey and Study Response dispersed payment (a $5.00 Amazon gift card) to each participant. Participants The 140 study participants were female, between the ages of 35 and 55, resided in the United States, and had a primary medical provid er with whom they had seen within the last 12 months. Participants were excluded fro m the study if they were male, under the age of 35 or over the age of 55, if they were c urrently pregnant, or if they had an illness, injury, or other condidtion that prevented them from exercising.

PAGE 37

28 Measures After consenting, participants were asked a series of questions to obtain demographic information (Appendix B). Demographic items included height and weight, education, occupational status, race/ethnicity, rel ationship status, and number of children under 18 years living at home. After this, particip ants were asked to complete a set of questionnaires that measured the following: Stage of Change To determine stage of change with regard to exercis e, the Stages of Change – Short Form (Norman, Benisovich, Nigg, & Rossi, 1998 ; Appendix C) was administered to each participant. The Stages of Change – Short Form consists of five statements about regular exercise representing the precontemplation, contemplation, preparation, action, and maintenance stages of change. Respondents were first informed that “regular exercise” is defined as “physical activity that is planned, structured, and repetitive and has a final or intermediate objective the improveme nt or maintenance of physical fitness” (Caspersen, Powell, & Christenson, 1985, p. 126). They were also informed that this activity is performed “three or more times per week for twenty or more minutes per session” (Norman et al., 1998). When asked if they perform regular exercise using that definition, participants who selected the statement “No and I do not intend to exercise regularly in the next 6 months” were placed in the precontemplation stage. Participants who responded, “No, but I intend to exercise regula rly in the next 6 months” were placed in the contemplation stage. The preparation stage was represented by the statement, “No, but I intend to exercise regularly in the next 30 d ays”. Participants who chose, “Yes, I have been exercising regularly for less than 6 mont hs” were categorized in the action

PAGE 38

29 stage. Lastly, participants were placed in the mai ntenance stage if they selected the statement, “Yes, I have been exercising for more th an 6 months”. Although this measure is widely used to assess the stages of change for e xercise, a comprehensive literature search revealed only one study that reported on the psychometric properties. Schumann et al. (2002) assessed the construct validity of th is measure by examining the correlational relationship between the stages of ch ange and three levels of intensity of physical activity (mild, moderate, and strenuous) i n an adult population. Significant correlation coefficients were found between the sta ges of change and moderate (.41) and strenuous (.46) exercise indicating the measure has empirical support for the validity of the measure for those exercise intensities. The cu rrent study found a significant correlation between the Stages of Change – Short Fo rm and self-reported total minutes of exercise per week, r = .53, p < .001. Self-Efficacy The Barriers Specific Self Efficacy Scale (BARSE) w as administered to assess perceived ability to exercise three times per week for three months in the face of various obstacles such as pain, boredom, or difficulty gett ing to the exercise location (McAuley, 1992; Appendix D). The BARSE is a 13-item self-rep ort measure; sample statements include, “I believe that I could exercise 3 times p er week for the next 3 months if the weather was very bad”, “I believe I could exercise 3 times per week for the next 3 months if I was bored by the program or activity”, and “I believe that I could exercise 3 times per week for the next 3 months if I felt pain or discom fort when exercising”. Each statement was rated in 10% increments on an 11-point scale fr om 0% (“Not at all confident”) to 100% (“Highly confident”). The ratings from the 13 statements were averaged creating a

PAGE 39

30 self-efficacy score ranging from 0 to 100%. McAule y (1992) reported a Cronbach’s alpha coefficient of .88 for the scale indicating s trong internal consistency between the items included on the BARSE. Cronbach’s alpha from the current study was .94. Social Physique Anxiety Social Physique Anxiety (SPA) was measured using th e Social Physique Anxiety Scale (SPAS; Hart, Leary, and Rejeski, 1989; Append ix E). The SPAS consists of 12 items about anxiety about one’s body or physique wh en being observed or evaluated by others. Sample statements on the measure include, “I am comfortable with the appearance of my physique/figure” and “Unattractive features of my physique/figure make me nervous in certain settings”. Participants rated each statement on a 1 (not at all characteristic of me) to 5 (extremely characteristi c of me) scale, creating a total combined SPAS score from 12 to 60. Hart et al. (1989) repo rted Cronbach’s alpha coefficient of .90 and test-retest reliability of .82. Cronbach’s alpha for the SPAS from the current study was also .90. Construct validity was assesse d through comparisons to measures such as body esteem, fear of negative evaluation, a nd body cathexis (the degree of satisfaction with one’s body). Hart et al. (1989) reported significant correlations of .82 on the weight concern/physical attractiveness s ection of the Body-Esteem Scale (Franzoi & Shields, 1984), .47 with the Fear of Neg ative Evaluation Scale (Leary, 1983), and -.58 on the Body Cathexis Scale (Secord & Joura rd, 1953). Affect Affect was assessed using the Positive and Negative Affect Scale (PANAS) shown in Appendix F (Watson, Clark, & Tellegen, 198 8). The PANAS includes 20 selfreport items of 10 positive and 10 negative mood st ate adjectives rated on a scale ranging

PAGE 40

31 from 1 (“very slightly or not at all”) to 5 (“extre mely”). Separate scores were calculated for both PA and NA, with each having possible score s ranging from 10 to 50. Participants were asked to rate the extent to which they felt each adjective during the previous week. Examples of positive mood state adj ectives on the PANAS included, “Interested”, “Excited”, “Strong”, and “Enthusiasti c”. Negative items on the PANAS included, “Hostile”, “Scared”, “Upset”, and “Guilty ”. Negative and positive items were summed separately to create independent PA and NA s cores as recommended by Watson et al. (1988). The authors reported Cronbach’s alp ha coefficients ranging from .86 to .90 for PA and .84 to .87 for NA. Cronbach’s alpha coe fficients for PA and NA in the current study were observed at .91 and .90 respecti vely. Watson et al. (1988) reported correlations between the PA and NA scales between .12 and -.23, representing a shared variance of 1% to 5%. The authors suggest these co rrelations indicate discriminant validity and the “quasi-independence” of the variab les. The correlation between the scales from the current study was r = -.30, p < .01. Exercise Frequency and Preferences Participants were asked to report both the frequenc y and duration of strenuous, moderate, and mild types of exercise they engaged i n over the past week (Appendix G). For frequency of exercise, participants were asked to enter the number of times they engaged in strenuous, moderate, and mild exercise. If the participants did not engage in a type of exercise, they were instructed to enter “0” for frequency and were not asked a follow up question about duration. If the particip ants reported engaging in any of the three exercise intensities (mild, moderate, strenuo us) at least once, they were asked to give an average number of minutes spent per exercis e session.

PAGE 41

32 Participants were asked to rate their level of inte rest in participating in various exercise activities such as walking, jogging, bikin g, swimming, etc. (Appendix H). Ratings were reported on a scale of 0 to 10, with 0 being not at all interested and 10 being the most interested in an activity. Participants w ere also asked to rate the likelihood of engaging in exercise at home, outdoors, or at fitne ss center and whether they were likely to exercise alone, with a friend, or in a group set ting. Ratings were given on a scale of 0 to 10, with 0 being not at all likely and 10 being extremely likely to engage (Appendix I). Data Analysis Hypothesis 1 was tested using a multivariate analys is of variance (MANOVA) to assess differences in the dependent variables of So cial Physique Anxiety (SPA), selfefficacy for overcoming barriers to exercise, Posit ive Affect (PA), Negative Affect (NA), and BMI between the independent variable of stages of change for exercise. Prior to running the analysis, the statistical assumption of homogeneity of the covariance matrices was confirmed with a non-significnat BoxÂ’s M test, p = .13. Univariate analyses of variance (ANOVA) were conducted on the dependent va riables following the MANOVA Post-hoc tests were conducted on the variables wher e significant differences were observed between the stages of change. The curvili near relationship between SPA and the stages of change predicted in Hypothesis 2 was tested with a polynomial model that tested for linear, quadratic, and cubic equaitions among all the dependent variables in the MANOVA. Hypothesis 3 was tested using a direct discriminant analysis to assess whether SPA was a significant predictor of stage of change for exercise. In addition, sequential discriminant analyses were also conducted to assess the abililty of SPA to improve on the

PAGE 42

33 accuracy of participant classification in the prese nce of other dependent variables such as self-efficacy.

PAGE 43

34 CHAPTER IV RESULTS Demographics The 140 participants included residents from 38 sta tes. Participants were relatively evenly distributed among the states. The largest percentages of participants came from New York, New Jersey, and California, how ever these were still relatively small percentages at 9%, 8% and 7% respectively. D emographics are shown in Table 1, which illustrates that the average age of participa nts was 46 years and they were primarily white (87%), married/partnered (74%), emp loyed (79%), and overweight or obese (63.6%). The participants’ last visit to their regular medic al provider was M = 4.1 months ( SD = 2.9) prior to completing the survey. Total week ly exercise ranged from 0 to 14.2 hours per week, ( M = 2.3, SD = 2.8). Hours of strenuous exercise ranged from 0 to 5 per week ( M = .6, SD = 1.2), moderate exercise from 0 to 5.8 ( M = .7, SD = 1.3), and mild exercise from 0 to 10 hours ( M = .9, SD = 1.6). Strenuous exercise was defined as “heart beats regularly, sweating”, moderate exercise “not exhausting, light perspiration”, and mild exercise “minimal effort, no perspiration” (Go din & Shephard, 1997). Participants were queried about their preferences for types of exercise activities such as walking, jogging, yoga/pilates, swimming, a nd golf. Overall, they expressed the strongest preference for walking outdoors, ( M = 7.4, SD = 2.1) and walking on a treadmill, ( M = 5.5, SD = 3.0). Golf and gymnastics received the lowest pr eference ratings, (golf M = .9, SD = 2.0; gymnastics M = .9, SD= 1.8).

PAGE 44

35 Participants also rated how likely they would be to exercise at home, outdoors, or at a fitness center and whether they were likely to exercise alone, with a friend or in a group in those settings. Participants indicated th ey would be most likely to exercise alone at home, M = 8.0 ( SD = 2.5) and alone outdoors, M = 6.6 ( SD = 3.4). Least likely activities were exercising in a group at home, M = 1.5 ( SD = 2.6) and exercising in a group outdoors, M = 2.7 ( SD = 3.3). Statistics for Overall Sample SPA The mean score on the SPAS scale for all participan ts combined was 41.3 ( SD = 9.1), which is considered high anxiety. Based on a procedure by Chu, Bushman, and Woodard (2008) groups of low, medium, and high scor es were formed. Chu et al. (2008) divided the scores into high, medium, and low group s where scores of 40 were considered high in anxiety, scores between 31 to 39 indicated moderate anxiety, and scores 30 indicated low anxiety. Scores from the current study revealed that the majority of participants (62.9%) fell into the top third and were considered to have high SPA. There were 23.6% of participants with moderat e SPA scores and 13.6% with low SPA. Self-efficacy The average total score on the BARSE for all partic ipants was 46.9 ( SD = 23.3), indicating a moderate level of self-efficacy for ov ercoming barriers to exercise. Similar to the procedure used for SPA, participant scores w ere sorted into low, medium, and high groups, which revealed that the majority of partici pants (47.1%) were in either the

PAGE 45

36 medium or moderate group with respect to self-effic acy. There were 29.3% of participants in the low self-efficacy group and 20. 7% in the high self-efficacy group. Affect Participants had an average PA score of 30.1 ( SD = 7.9) and NA score of 18.4 ( SD = 7.1). Crawford and Henry (2004) have shown that a PA score of 32 and NA of 15 represent approximately the 50th percentile in a non-clinical sample. A PA score 18 is “abnormally low” and in approximately the 5th percentile. A score for NA 29 is “abnormally high” in approximately the 95th percentile. Of the current sample, 10 participants (7.1%) had PA scores 18 and 12 (8.6%) reported NA scores 29. Comparisons Across the Stages of Change Participants were classified into one of five group s with respect to their stage of change for exercise. Ten participants were classif ied in the precontemplation stage, 31 in contemplation, 34 in preparation, 25 in action, and 38 in the maintenance stage. Significnat differences in demographic variables be tween the stages of change were assessed with analyses of variance (ANOVA). No sig nificant differences were found between women in the different stages of change wit h respect to the demographic variables of age, years of education, employment, r elationship status, or the number of children under 18 living at home. A multivariate analysis of variance (MANOVA) was co nducted with the dependent variables of SPA, self-efficacy for overc oming barriers to exercise, PA, NA, and BMI. The independent variable was stage of cha nge for exercise with five groups: precontemplation, contemplation, preparation, actio n and maintenance. Table 2 presents the means and standard deviations for the five depe ndent variables for each stage of

PAGE 46

37 change for exercise. A significant overall multiva riate effect was observed between the stages of change and the five dependent variables ( WilksÂ’ = .45, F (20, 429) = 5.91, p < .001; 2 = .55). An 2 of .55 is indicative of a large effect size (Cohen 1977). The significant multivariate effect confirmed the hypot hesis that overall differences would be observed among the dependent variables with respect to stages of change for exercise. It was also hypothesized that significant differences would be observed in each of the five dependent variables. Follow up univariate analyses of variance (ANOVAs) revealed that this hypothesis was supported for SPA, self-efficac y, PA and BMI. However, no significant differences were observed for NA. Tabl e 3 illustrates the univariate analyses subsequent to the MANOVA. Post-hoc analyses were performed to further examine significant differences in SPA, self-efficacy, PA, and BMI with regard to stag es of change. Results of these analyses are described below. No post-hoc analysis was conducted with NA as no significant differences were observed in this varia ble between the stages of change. SPA A significant main effect was observed for SPA acro ss the five stages of change, F (4, 133) = 4.94, p = .001 and a ScheffeÂ’ post-hoc analysis was conduct ed to further characterize these significant differences. As sho wn in Table 4, women in both precontemplation and action had significantly highe r SPA than women in the maintenance stage. Surprisingly, contemplators had lower SPA than either precontemplators or those in the action stage. It was hypothesized that a curvilinear relationship would exist between SPA and the stages of change for exercise. A quadratic ter m was anticipated to fit the relationship

PAGE 47

38 such that SPA would increase through the preparatio n stage and begin to decrease in the action stage of change. A polynomial contrast was run with the one-way MANOVA to test for a curvilinear relationship between the sta ges of change for exercise and SPA. The polynomial contrast revealed a significant effect f or the cubic term for SPA, F (1, 135) = 6.22, p < .05. Figure 1 illustrates a decrease in SPA betw een the precontemplation and contemplation stages, an increase in SPA between co ntemplation and preparation, and a decrease in SPA between preparation and action and maintenance stages. As reported earlier, significant differences were observed in t he post-hoc tests between precontemplation and maintenance as well as between preparation and maintenance. It was also hypothesized that SPA would be a signif icant predictor of stage of change. In order to evaluate this, a direct discri minant analysis was conducted. When SPA was entered as a singular predictor of stage me mbership, 30.0% of participants overall were correctly classified into the stages o f change, = .87, 2 (4) = 19.0, p < .001. As shown in Table 5, 50% were correctly classified in the precontemplation stage, 25% in contemplation, 14.7% in preparation, 7.7% in act ion, and 57.9% were correctly classified in the maintenance stage using this mode l. A sequential discriminant analysis was also conduct ed to assess the capability of SPA to improve upon participant classification into the stages of change with selfefficacy entered first as a predictor variable, as described by Tabachnick and Fidell (2007). Based on previous findings it was anticipa ted that self-efficacy would be the strongest predictor of correct classification into the stages of change. As a result, selfefficacy was entered first into the model. As a si ngular predictor of stage membership, self-efficacy correctly classified 42.9% of partici pants overall into the stages of change,

PAGE 48

39 = .54, 2 (4) = 84.3, p < .001. As shown in Table 6, 70% were correctly cl assified in the precontemplation stage, 31.3% in contemplation, 23. 5% in preparation, 34.6% in action, and 68.4% of participants were correctly placed in the maintenance stage. SPA was subsequently added into the discriminant an alysis along with selfefficacy to assess whether the correct classificati on of participants into the stages of change would improve with the addition of the SPA v ariable. This model correctly classified 50.7% of participants overall into the s tages of change, = .51, 2 (8) = 92.4, p < .001. The addition of SPA as a predictor resulted in a 7.8% improvement in correct classification overall. As shown in Table 7, 80% o f participants were correctly placed in the precontemplation stage, 40.6% in contemplation, 32.4% in preparation, 42.3% in action, and 73.7% were correctly classified in the maintenance stage. When other variables (PA, NA, BMI) were tested as predictors i n the model along with self-efficacy and SPA, the percent of correctly classified partic ipants into the stages of change never exceeded the 50.7% correctly classified with self-e fficacy and SPA alone as predictor variables. Self-efficacy Self-efficacy also differed among participants acro ss the different stages of change as evidenced by a significant main effect in the univariate analysis, F (4, 133) = 31.36, p < .001. Table 8 illustrates ScheffeÂ’ post-hoc comp arisons for self-efficacy to overcome barriers to exercise. Participants in mai ntenance were significantly more selfefficacious than participants in each of the four e arlier stages of change. Self-efficacy was also significantly higher in women in the actio n stage of change than it was in women in precontemplation and contemplation. Women in preparation also had

PAGE 49

40 significantly higher scores than women in precontem plation. The linear relationship between self-efficacy and the stages of change and is illustrated in Figure 2. PA The univariate analysis with PA also revealed that women in different stages of change for exercise differed significantly in PA, F (4, 133) = 9.28, p < .001. Table 9 shows ScheffeÂ’ post-hoc comparisons for PA and reve als that women in maintenance endorsed significantly more PA than women in precon templation, contemplation and preparation stages. The linear relationship betwee n PA and the stages of change is illustrated in Figure 3. NA Significant differences were hypothesized but not observed in NA in subsequent univariate analyses following the MANOVA, F (4, 133) = 1.81, p = .13. No post-hoc analysis was conducted with this variable. BMI Univariate analysis with BMI revealed a main effect for BMI between the five stages of change, F (4, 133) = 4.16, p = .003. As shown in Figure 4, the body weights of participants decreased across the five stages of ch ange. Post-hoc tests (shown in Table 10) revealed that the weights of women in maintenan ce were significantly lower than those in contemplation and preparation, but women i n precontemplation did not differ in BMI from those in the action stage. The linear rel ationship between BMI and the stages of change is illustrated in Figure 4.

PAGE 50

41 Exercise preferences Supplemental analyses were conducted to explore gro up differences in exercise preferences between the stages of change for exerci se. First, a multivariate analysis of variance (MANOVA) was conducted with the independen t variable of stages of change and dependent variables of preferences about compan y when exercising (whether participants preferred to exercise alone, with a fr iend, or in a group). A significant main effect was observed in the MANOVA, (WilksÂ’ = .75, F (12, 331) = 3.13, p < .001). Subseqent univariate analyses of variance (ANOVAs) revealed significant differences between the stages of change and preferences for ex ercising alone, excercising with a friend, and exercising in a group, illustrated in T able 11. A ScheffeÂ’ post-hoc analysis revealed only significant differences between the s tages of change with exercising alone. Specifically, the precontempation stage expressed s ignificantly lower preference for exercising alone compared to preparation, action, a nd maintenance. Maintenance also had a significantly higher preference for exercisin g alone compared to contemplation. Differences in exercise preference related to locat ion and the stages of change were also analyzed in a MANOVA. A significant main effect was observed, WilksÂ’ = .77, F (12, 331) = 2.90, p < .01. Follow up univariate analyses revealed sign ificant differences in preferences for exercising at home, exercising outdoors, and exercising at a fitness center, illustrated in Table 11. A Scheffe Â’ post-hoc analysis revealed significant differences between the stages of change for home a nd outdoors only. Specifically, participants in the maintenance stage indicated a s ignificantly higher preference for exercising at home than participants in the precont emplation stage. Similarly,

PAGE 51

42 participants in the maintenance stage rated a signi ficantly higher preference for exercising outdoors than participants in the precon templation or contemplation stage. A multivariate analysis of variance (MANOVA) was a lso conducted with high, medium, and low SPA and preferences about company w hen exercising (whether participants preferred to exercise alone, with a fr iend, or in a group). No significant main effect was observed indicating there were no signif icant differences in preferences about with whom one exercises between individuals with hi gh, medium, and low SPA. Differences in preferences about exercise location (home, outdoors, or fitness center/gym) between individuals with high, medium, and low SPA were also analyzed in a MANOVA. A significant main effect was observed i ndicating there were significant differences in preferences for exercise location be tween high, medium, and low SPA groups, WilksÂ’ = .89, F (6, 254) = 2.45, p = .026. Follow up ANOVAs revealed differences between individuals with high, medium, and low SPA with respect to exercising outdoors only, F (2, 129) = 4.76, p = .01. A ScheffeÂ’ post-hoc analysis indicated that individuals with low SPA reported a significantly stronger preference for exercising outdoors than individuals with medium an d high SPA. No significant differences between high, medium, and low SPA group s were observed with respect to preferences for exercising in a gym or fitness cent er or at home.

PAGE 52

43 CHAPTER V DISCUSSION The purpose of this study was to understand correla tes of stages of change for exercise among mid-life women with a particular foc us on SPA. Based on existing literature and theory, it was predicted that: a) th ere would be significant differences in SPA between the five stages of change, b) that a no n-linear relationship would exist between SPA and the stages of change, and c) that S PA would significantly predict group membership in the stages of change. Results lent s upport to all three of these hypotheses. First, women in the five stages of change for exerc ise differed significantly in selfreported SPA scores. Second, a significant curvili near relationship was confirmed between SPA and the stages of change. Finally, SPA was a significant predictor of group membership in the stages of change for exercise. In addition to supporting the three primary hypothe ses, the results also revealed some interesting and unexpected findings. For exam ple, the curvilinear relationship between SPA and stage of change was cubic rather th an quadratic as hypothesized. It was hypothesized that women would exhibit the least amount of SPA during the precontemplation stage, show increasingly more SPA as they contemplated beginning an exercise regimen, and that SPA would begin to decre ase when they started (action stage) and continued exercising (maintenance stage). Inst ead, SPA was highest during the precontemplation stage, lower in contemplation, hig her in preparation and action, with the least amount of SPA measured in the maintenance stage. Closer examination of the results suggests that th e difference between the relationship hypothesized and the one actually foun d may relate primarily to the findings

PAGE 53

44 for the 10 women in the precontemplation group. Th is was an unusual group in several ways. Not only did members of this group have the highest SPA of the five stages, they also had the highest BMI, lowest self-efficacy, low est PA, and highest NA. Specifically, the 10 participants in this stage were obese (avera ge BMI of 33.8), had extremely low scores on self-efficacy (average 16.3 out of 100), and expressed the lowest PA (approximately 18th percentile) and the highest NA (approximately 88th percentile; Campbell and Henry, 2004). Taken together, results suggest that the group was highly distressed across several psychological and physiol ogical dimensions. While it is possible that these data are not generalizable to l arger populations, the current findings suggest that individuals in the precontemplation gr oup face a multitude of challenges that should be considered in order to deliver appropriat e and effective interventions. Given that SPA was highest in the precontemplation stage and lowest in the maintenance stage, it is also interesting to consid er how well SPA predicted group membership in the various stages of change. As a s ingle predictor, SPA correctly placed the highest percentage of participants in the preco ntemplation and maintenance stages at 50% and 57.9% respectively. The action stage of ch ange had the lowest percentage correctly placed by SPA (7.7%), indicating that SPA score is not particularly helpful in predicting individuals who have recently begun to e xercise. In contrast, self-efficacy correctly placed 34.6% of participants into the act ion stage. Significant differences were also observed in the o ther variables of interest including self-efficacy, PA, and BMI. With respect to self-efficacy, it was interesting to note that with the exception of action and maintena nce, no significant differences were observed between adjacent stages (i.e. precontempla tion and contemplation,

PAGE 54

45 contemplation and preparation, or preparation and a ction). The significant difference observed between the adjacent action and maintenanc e stages suggests that individuals may need significantly more confidence in their abi lity to overcome barriers to progress to maintenance and long-term exercise. It is also interesting to note the relatively high level of self-efficacy in the maintenance group (68 .4 out of 100), which lends support for the level of confidence it would take to maintain a n exercise regimen long-term (i.e. > 6 months). Analyses of affect across the stages of change also revealed some interesting findings. For example, the maintenance group demon strated significantly higher PA than those in the precontemplation, contemplation, and p reparation, but did not significantly differ from those in action. This suggests that po sitive feelings are positively associated with the adoption of exercise. It is possible that although positive emotions may continue to increase with longer-term exercise represented b y the maintenance stage, it is possible that most of the positive emotional benefit may be realized soon after an individual begins exercise. These possibilities could be inve stigated with a prospective design. The relationship between PA and NA observed in the present study was also of considerable interest. Although there were signifi cant differences in PA between the stages of change demonstrated by a linear relations hip (i.e. PA steadily increased from pre-contemplation through maintenance), there were no significant differences in NA between the stages of change. NA was highest in th e precontemplation stage and dropped to a high-normal range in each of the other stages. A slight but non-significant increase was observed in action (following the prep aration stage), which was then followed by a slight decrease in NA in the maintena nce phase.

PAGE 55

46 The suggestion by Watson et al. (1988) that PA and NA are independent variables as evidenced by low correlations (-.12 and -.23) ma y help provide some context to these findings. If PA and NA represent opposite ends of a n emotional continuum, one would expect to see significant differences in both of th e variables or neither of the variables across the stages of change (i.e.. PA increases as NA decreases). Close examination of Figure 5 suggest that the lack of significant diffe rences stem from four of the five stages having relatively similar NA scores (ranging from 1 6.9 to 19.1) following the highest NA score (23.5) in precontemplation. The significant finding observed in PA but not NA s uggests that the two variables may be independent rather than exist as opposites o n a continuum. Though the present study did not specifically evaluate the independenc e of these variables, the significantly low correlation observed ( r = -.30, p < .01) is consistent with this interpretation. Ano ther possible explanation is that the way NA is operatio nalized is less related to exercise than the way PA is operationalized. For example, three of the ten PA descriptors (strong, active, determined) could be associated with physic al strength whereas none of the descriptors of NA seem related to exercise or stren gth. This could account in part for the significant increases in positive feelings without a corresponding decrease in negative feelings. The significant linear relationship between BMI and the stages of change was expected. Previous studies have demonstrated an in verse relationship between BMI and exercise with higher BMI being associated with lowe r levels of exercise (Evenson et al., 2002; Petersen, Schnohr, & Sorenson, 2004). With r espect to the stages of change, lower levels of exercise are represented by the precontem plation through the preparation stages

PAGE 56

47 and one would expect significantly higher BMIs in t hese groups than in the action and maintenance stages. Women in precontemplation, con templation, and preparation all had BMIs in the obese range ( 30.0), while those in the action phase were in the overweight range, and the maintenance group was just slightly above the normal range. In the present study, there were significant differences i n BMI between the maintenance stage and both the contemplation and preparation stages. Interestingly, no significant differences were observed between the action stage and the earlier stages of change with respect to BMI, which suggests that the length of t ime an individual has been exercising regularly is important. Another curious finding wa s the absence of significant differences between precontemplation and maintenance given that precontemplation had the highest average BMI. The lack of significance is likely du e to the large amount of variance observed in the precontemplation group shown in Fig ure 4. The lack of significant differences in preference a bout exercise alone, with a friend, or in a group between individuals with high medium, and low SPA was not anticipated. It was expected that individuals with high SPA would have stronger preferences about exercising alone due to concerns about being observed or evaluated by others. The differences in preference for exercise location between high, medium, and low SPA was intriguing, with individuals with both medium and high SPA expressing less of a preference for this venue than those with low SPA. Future studies could seek to confirm these findings as they may influence the de sign of interventions and the types of exercise that providers encourage. One of the clear strengths of the current study is the consistency between the data gathered from this sample of 140 mid-life women and data gathered from other studies

PAGE 57

48 with women of similar demographic characteristics. This suggests that the sample may be representative of a broader population, which su pports generalizability of the findings. Specifically, the sample in the present study was s imilar to national averages with respect to the study variables including BMI, exercise pref erences and frequency, and selfefficacy. With regard to BMI, 36.5% of all study participants were in the obese range (BMI 30.00), which is consistent with 36.3% in non-Hisp anic white women between 40 and 59 gathered by the CDC National Center for Health S tatistics (2011) in the National Health and Nutrition Examination Survey (NHNES) rep orted by Ogden, Carroll, Kit, & Flegal (2014). Additionally, 63.6% of study partic ipants were classified in the overweight or obese range (BMI 25.00), which is slightly lower but comparable to 69.1% obtained in the NHNES. Obese Classes II and III had a slightly higher percentage of study participants compared to national averages with 23.6% of participants having a BMI 35.0 compared to the NHNES estimate of 16.9%. Ther e were 14.3% of study participants with a BMI 40.0 (Obese Class III) compared to 8.8% gather in t he NHNES. It is not clear why this sample included a slightly higher percentage of extremely obese individuals than found in the NHNES, particularly g iven that none of the study participants were pregnant or physically disabled t o a point that would prevent them from exercising. Exercise frequency and preferences were also simil ar to what has been found in national studies. The average number of 2.3 hours o f exercise reported in the current study is consistent with approximately 2 hours of w eekly exercise reported in the American Time Use Survey (ATUS) analyzed by researc hers from Pennsylvania State

PAGE 58

49 University and the University of Maryland in a proj ect funded by the Maryland Population Research Center (Americans fall short of exercise recommendations, 2012). The ATUS data was gathered by the Census Bureau and includes more than 100,000 respondents nationwide. The researchers also repor ted that walking was the most common activity, which is consistent with the curre nt findings that participants had the strongest preference for walking, both outdoors and on a treadmill. Golf was among the least preferred activities in the current study, al though it is possible as this participant group ages, they may express more interest in this activity. The researchers from University of Maryland and Penn State found golf wa s the most prevalent exercise activity (aside from walking) for seniors over 65, although the sample included both men and women. It may be as likely that women in these age ranges do not prefer golf as an activity. The data gathered with respect to exercise locatio n and with whom participants are most likely to exercise was also similar to pre vious research. Study participants reported they would be most likely to exercise alon e both at home and outdoors and previous studies have reported that middle-aged adu lts prefer to exercise alone (King et al., 2000; Wilcox, King, Brassington, & Ahn, 1999). Additionally, home-based exercise has been found to have significantly greater partic ipation and weight loss when compared to group exercise in a sample of women ages 40 to 6 0 years with BMIs between 27 and 45 (Perri, Martin, Leermakers, Sears, & Notelovits, 1997). More recently, there has been evidence to suggest that group settings can be more preferable to adults when they include age-matched participants (Beauchamp, Carron McCutcheon, & Harper, 2007). This, however, was not evaluated in the current stu dy.

PAGE 59

50 With regard to self-efficacy, the women in the pres ent study were also similar to those in other studies suggesting that these data a re also generalizable to the broader population. In the present study, participants rep orted a moderate amount of confidence in their ability to overcome barriers to exercise, which was similar to findings reported by Oman and Duncan (1995) in a sample of women recruit ed from exercise programs. Morris, McAuley, and Motl (2008) also examined self -efficacy related to barriers to exercise in women and also found moderate levels of self-efficacy. Similarly, Mailey (2012) reported moderate self-efficacy in women in a study looking at exercise adherence in working mothers. Limitations It is also important to point out several limitatio ns of the study. One is that there were relatively few participants in the precontempl ation stage compared to the other stages. Despite soliciting close to 1,000 potentia l participants over the course of approximately two months to obtain the current samp le of 140, only 10 participants endorsed the statement, “No, and I do not intend to exercise regularly” when asked if they exercise three or more times per week for twen ty or more minutes. The largest percentage of participants endorsed, “Yes, I have b een exercising regularly for more than 6 months”, which was representative of the maintena nce stage. There are several possible explanations for why so few participants e ndorsed the precontemplation statement. First, it is possible that the survey t opic of women’s health and exercise appealed primarily to individuals who were either i nterested in exercising or already exercising (which would also explain the larger num ber of participants in the maintenance phase). Another possibility is that ps ychological factors such as social

PAGE 60

51 desirability or cognitive dissonance (Festinger, 19 62) prevented individuals from reporting their true intentions. Few people may ha ve been willing to admit that they were not even planning to engage in an activity that has been shown to be so beneficial for health. A third possibility relates to the timing of the survey and New Year’s resolutions. Given that the survey was conducted right after the first of the year, it may be that some individuals had recently made a commitment to begin exercising as part of a New Year’s resolution and therefore would have endorsed either the contemplation stage, “No, but I intend to exercise regularly in the next six months ” or the preparation stage, “No, but I intend to exercise regularly in the next 30 days”. Another limitation of study is that while the data gathered is similar to national averages for women with similar demographic charact eristics (i.e. white, middle-aged, educated, etc.), it is not representative of the U. S. population as a whole and findings may not be generalizable to women with different demogr aphics. As it is hoped that this study may be useful clinically in primary care population s, it will be important to know if the findings from the study are relevant to mid-life wo men of different racial and ethnic background, less education, etc. The online nature of the sample is also a limitation. Efforts were made to improve the generalizability o f the findings to a primary care population by including only women who have a medic al provider for routine care they have seen within the last twelve months. The idea being that these women would be more likely to receive an exercise intervention com pared to the general population. The cross-sectional design of the study also has ce rtain limitations. Crosssectional design entails comparing women across gro ups (stages) at the same point in time. Gathering data from groups rather than indiv iduals increases error and variance,

PAGE 61

52 which can affect the findings of the study. Addito nally, it is tempting to consider how the variables change as individuals progress through th e stages of change. However, since these data were gathered from groups of women at th e same point in time we cannot assume that an individual would follow the same pat tern of scores on the variables as they move through various stages of change. It mig ht be interesting to utilize a withinsubjects longitudinal design to characterize indivi dual movement through the change stages with respect to SPA, keeping in mind that mo vement through the stages of change does not always occur in a linear fashion. Clinical and Research Implications The knowledge gained with respect to the variables examined in this study and their relationship to the stages of change for exer cise have some intriguing clinical implications, particularly with regard to MI exerci se interventions delivered in primary care. For example, given the significant linear re lationship between self-efficacy and the stages of change, efforts to increase self-efficacy may be useful in helping an individual progess through the stages of change. This may be especially true with respect to longterm exercise when individuals transition into the maintenance stage of change, a complex area still being explored (Stetson et al., 2005). Previous findings that increased self-efficacy is predictive of reduced SPA (McAuley Bane, Mihalko, 1995) are also relevant and meditational pathways could be explore d in a clinical and research settings as well. The findings with respect to SPA in this study may be of interest to healthcare professionals who conduct exercise interventions wi th mid-life women based on MI and the stages of change. The knowledge that SPA has b een found to be highest in the

PAGE 62

53 precontemplation and preparation stages alerts heal th providers to be more aware of the potential for these concerns to arise in mid-life w omen in these stages. Studies have shown that SPA can be reduced through both physical activity and educational interventions (Lindwall and Lindgren, 2005; McAuley Marquez, Jerome, Blissmer, Katula, 2002; Scott, 2005). A brief intervention i n primary care might consist of one or two screening questions to help indentify individua ls with high SPA concenrs. These individuals could receive a followed by a brief cog nitive behavioral intervention designed to reduce maladaptive thinking and discourage avoid ance of exercise. Such interventions would be tailored to an individualÂ’s particular sta ge of change and adhere to the MI philosophy of collaboration between provider and pa tient described by Miller and Rollnick (2002). The cross-sectional nature of the study prevents in ferences about how one particular individualÂ’s SPA may or may not increase or decrease as they progress through the various stages of change. However, the knowled ge that the lowest SPA was observed in women in the maintenance stage may suggest that sustained engagement in an anxiety provoking experience may eventually lead to reducti on in anxiety levels. This is consistent with the behavioral perspective of anxie ty and exposure therapy techniques where individuals are encouraged to engage in feare d experiences as a means to acclimating to emotional discomfort and eventually decreasing fear (Kaplan & Tolin, 2011). The findings are also consistent with studi es that have utilized exercise interventions to reduce SPA in various populations (McAuley, Bane, & Mihalko, 1995; McAuley, Marques, Jerome, Blissmer, & Katula, 2002; Williams & Cash, 2001).

PAGE 63

54 The findings about SPA and exercise preferences may also have other relevant clinical implications. Knowledge about where and w ith whom individuals with high SPA prefer to exercise can help inform interventions, p articularly when patients are in the preparation stage. For example, a provider may cho ose to put more emphasis on helping a patient plan to aquire exercise videos rather tha n encouraging them to plan to enroll in a group fitness class at the local recreation center or gym. While this particular study did not reveal any significant findings in these areas, previous studies have made similar recommendations with exercise preferences and level s of SPA (Diehl, 2001). This study also presents several possible avenues f or future research. The curvilinear relationship identified with SPA could be explored in a larger population that includes more participants in the precontemplation stage of change. Future studies may consider targeted recruitment of individuals in the precontemplation stage who have not even considered exercising. Given the online recru itment procdure in this study where women self-selected to participate, it is likely th at women in precontemplation were not interested or felt the study did not apply to them. More targeted language stating that the study is seeking women who are not exercising might result in higher participation in this stage. Additional data in the precontemplation gro up would facilitate the investigation of the curvilinear relationship observed in this study If the curvilinear relationship is confirmed by subsequent studies, this would add to the body of knowledge necessary for designing stage-based interventions with respect to SPA. In summary, the suggestions for future directions d iscussed above underscore the important relationship between research and clinica l work. The findings in this study suggest some interesting avenues that could be expl ored in both of these arenas.

PAGE 64

55 Increased knowledge about the relationship between SPA and the stages of change may help practitioners deliver interventions that are m ore informed, effective, and relevant for mid-life women and their barriers to exercise.

PAGE 65

56 REFERENCES Angeli, E., Wagner, J., Lawrick, E., Moore, K., And erson, M., Soderlund, L., & Brizee, A. (2012, May 30). General format. Retrieved from http://owl.english.purdue.edu/owl/resource/560/01/ American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington DC: Author. Americans fall short of exercise recommendations. ( 2012). Retrieved from http://news.psu.edu/story/149052/2012/05/08/america ns-fall-short-federalexercise-recommendations Artinian, N. T., Fletcher, G. F., Mozaffarian, D., Kris-Etherton, P., Van Horn, L., Lichtenstein, A. H., . Burke, L. E. (2010). Int erventions to promote physical activity and dietary lifestyle changes for cardiova scular reduction in adults. Circulation, 122 406-441. Bandura, A. (1977). Self-efficacy: Toward a unifyin g theory of behavioral change. Psychology Review, 84 191-215. Bandura, A. (1986). Social foundations of thought a nd action: A social cognitive theory. Englewood Cliffs, New Jersey: Prentice-Hall. Barnes, P. M., & Schoenborn C. A. (2012). Trends in adults receiving a recommendation for exercise or other physical activ ity from a physician or other health professional. NCHS data brief, no 86. Hyatts ville, MD: National Center for HealthStatistics.

PAGE 66

57 Beauchamp, M. R., Carron, A. V., McCutcheon, A., & Harper, O. (2007). Older adultsÂ’ preferences for exercising alone versus in groups: Considering contextual congruence. Annals of Behavioral Medicine, 33 (2), 200-206. Blanchard, C. M., Fortier, M., Sweet, S., OÂ’Sulliva n, T., Hogg, W., Reid, R. D., Sigal, R. J. (2007). Explaining physical activity levels from a self-efficacy perspective: The physical counseling trial. Annals of Behavioral Medicine, 34 (3), 323-328. Bouchard, C., Shepard, R. J., Stephens, T., Sutton, J. R., & McPherson, B. D. (1990). Exercise, fitness and health: A consensus of curren t knowledge Champaign, IL: Human Kinetics. Britt, E., Hudson, S. M. & Blampied, N. M. (2004) Motivational interviewing in health settings: A review. Patient Education and Counseling, 53 (2), 147-155. Brown, W. J., Ford, J. H., Burton, N. W., Marshall, A. L., & Dobson, A. J. (2005). Prospective study of physical activity and depressi ve symptoms in middle-aged women. American Journal of Preventive Medicine, 29 (14), 265-272. Burke, B. L., Arkowitz, H., Menchola, M. (2003). Th e efficacy of motivational interviewing: A meta-analysis of controlled clinica l trials. Journal of Consulting and Clinical Psychology, 71 (5), 843-861. Calfas, K. J., Sallis, J. F., Oldenburg, B., Ffrenc h, M. (1997). Mediators of change in physical activity following an intervention in prim ary care: PACE. Preventive Medicine, 26 297-304. Caspersen, C. J., Powell, K.E., & Christenson, G. M (1985). Physical activity, exercise, and physical fitness: Definitions and distinctions for health-related research. Public Health Reports, 100 (2), 126-131.

PAGE 67

58 Centers for Disease Control and Prevention. (2011). Healthy weight – It’s not a diet, it’s a lifestyle. About BMI for adults. Retrieved September 19, 2012 from www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/i ndex.html Centers for Disease Control and Prevention. (2014). Facts about physical activity. Retrieved August 10, 2014, from http://www.cdc.gov/physicalactivity/data/facts.html Chu, H. W., Bushman, B. A., & Woodard, R. J. (2008) Social physique anxiety, obligation to exercise, and exercise choices among college students. Journal of American College Health, 57 (1), 7-14. CDC National Center for Health Statistics. (2011). National health and nutrition examination survey. http://www.cdc.ogv/nchs/nhanes/nhanes_questionnaire s.htm Cohen, J. (1977). Statistical power analysis for the behavioral scien ces. San Diego, CA: Academic Press. Crawford, J. R., & Henry, J. D. (2004). The positiv e and negative affect schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43 245-265. Cumming, J., & Thogersen-Ntoumani, C. (2011). Selfpresentational cognitions for exercise in female adolescents. Journal of Applied Social Psychology, 41 (2), 429-444. Diehl, N. S. (2001). Exercise partner preferences, social physique anxiety, and social discomfort in exercise settings among women univers ity wellness center patrons. Women in Sport & Physical Activity, 10 (1), 89-101.

PAGE 68

59 DuCharme, K. A., & Brawley, L. R. (1995). Predictin g the intentions and behavior of exercise initiates using two forms of self-efficacy Journal of Behavioral Medicine, 18 (5), 479-497. Dunn, C., Deroo, L., & Rivara, F. P. (2001). The us e of brief interventions adapted from motivational interviewing across behavioral domains : A systematic review. Addiction, 96 1725-1742. Dunn, A. L., Trivedi, M. H., Kampert, J. B., Clark, C. G., & Chambliss, H. O. (2005). Exercise treatment for depression. American Journal of Preventive Medicine, 28 (1), 1-8. Eakin, E. G., Glasgow, R. E., & Riley, K. M. (2000) Review of primary care-based physical activity intervention studies. The Journal of Family Practice, 49 (2), 158168. Ekkekakis, P., Lind, E., & Vazou, S. (2010). Affect ive responses to increasing levels of exercise intensity in normal-weight, overweight, an d obsess middle-aged women. Obesity, 18 (1), 79-85. Eklund, R. C., & Crawford, S. (1994). Active women, social physique anxiety, and exercise. Journal of sport and exercise psychology, 16 431-448. Evenson, K. R., Wilcox, S., Pettinger, M., Brunner, R., King, A. C., & McTiernon, A. (2002). Vigorous leisure activity through womenÂ’s a dult life. American Journal of Epidemiology, 156 (10), 945-953. Festinger, L. (1962). A theory of cognitive dissonance. Stanford, CA: Stanford University Press.

PAGE 69

60 Franzoi, S. L., & Shields, S. A. (1984). The body-e steem scale: Multidimensional structure and sex differences in a college populati on. Journal of Personality Assessment, 42 (2), 173-178. Gallup Well-Being (2012). http://www.gallup.com/poll/153251/no-major-changeamericans-exercise-habits-2011.aspx Garber, C. E., Blissmer, B., Deschenes, M. R., Fran klin, B. A., Lamonte, M. J., Lee, I.,Â…Swaine, D. P. (2011). Quantity and quality of e xercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Medicine & Science in Sports & Exercise, 43 (7), 1334-1359. Godin, G., & Shepard, R. J. (1997). Godin Leisure-T ime Exercise Questionnaire. Medicine and Science in Sports and Exercise, 29 S36-S38. Green, G. W., Rossi, S. R., Rossi, J. S., Velicer, W. F., Fava, J. L. (1999). Dietary applications of the stages of change model. Journal of American Dietary Association, 99 673-678. Gutierrez, C., & Luque, G. (2012). Influence of ex ercise on mood in postmenopausal women. Journal of Clinical Nursing, 21 923-928. Harland, J., White, M., Drinkwater, C., Chinn, D., Farr, L., Howel, D. (1999). The Newcastle exercise project: A randomised controlled trial of methods to promote physical activity in primary care. BMJ, 319 828-832.

PAGE 70

61 Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde. J. G. (2009). Research electronic data capture (REDCap) – A metad ata-driven methodology and workflow process for providing translational re search informatics support. Journal of Biomedical Information, 42 (2), 377-381. Hart, E. A., Leary, M. R., & Rejeski, W. J. (1989). The measurement of social physique anxiety. Journal of Sport and Exercise Psychology, 11 94-104. Hausenblas, H. A., Nigg, C. R., Symons Downs, D., & Flemming, D. S., Connaughton, D. P. (2002). Predictions of exercise stages, barri er self-efficacy, and decisional balance for middle-level school students. Journal of Early Adolescence, 22 (4), 436-454. Herring, M. P., & Jacob, M. L. (2011). Effects of s hort-term exercise training on signs and symptoms of generalized anxiety disorder. Mental Health and Physical Activity, 4 71-77. Hillsdon, M., Thorogood, M., White, I., Foster, C. (2002). Advising people to take more exercise is ineffective: A randomized controlled tr ial of physical activity promotion in primary care. International Journal of Epidemiology, 31 (4), 808815. Jacobson, D. M., Strohecker, L., Compton, M. T., an d Katz, D. L. (2005). Physical activity counseling in the adult primary care setti ng. American Journal of Preventive Medicine, 29 (2), 158-162. Kaplan, J. S., Tolin, D. F. (2011). Exposure therap y for anxiety disorders: Theoretical mechanisms of exposure and treatment strategies. Psychiatric Times, 28 (9), 3337.

PAGE 71

62 Keller, C., Fleury, J., Gregor-Holt, N., & Thompson T. (1999). Predictive ability of social cognitive theory in exercise research: An in tegrated literature review. The Online Journal of Knowledge Synthesis for Nursing, 6 (2), 19-31. King, A. C., Castro, C., Wilcox, S., Eyler, A. A., Sallis, J. F., & Brownson, R. C. (2000). Personal and environmental factors associated with physical inactivity among different racial-ethnic groups of U.S. middle-aged and older-aged women. Health Psychology, 19 (4), 354-364. Kohrt, W. M. (2009). Menopause and weight gain: Doe s exercise attenuate or prevent weight gain during periand postmenopause? Geriatrics, 64 (6), 28-29. Lantz, C. D., Hardy, C. J., & Ainsworth, B. E. (199 7). Social physique anxiety and perceived exercise behavior. Journal of Sport Behavior, 20 (1), 83-93. Lawlor, D. A., & Hanratty, B. (2001). The effect of physical activity advice given in routine primary care consultations: A systemative r eview. Journal of Public Health Medicine, 23 (3), 219-226. Leary, M. R. (1983). A brief version of the Fear of Negative Evaluation Scale. Personality and Social Psychology Bulletin, 9 371-376. Lindwall, M., & Lindgren, E. C. (2005). The effects of a 6 month exercise intervention programme on physical self-perceptions and social p hysique anxiety in nonphysically active Swedish girls. Psychology of Sport and Exercise, 6 643-658. Lytle, M. E., Vanderbilt, J., Pandav, R. S., Dodge, H. H., Ganguli, M. (2004). Exercise level and cognitive decline: The movies project. Alzheimer Disease and Associated Disorders, 18 (2), 57-64.

PAGE 72

63 Mailey, E. (2012). Impact of a brief exercise adherence intervention o n physical activity and quality of life among working mothers (Doctoral dissertation). Retrived from http://hdl.handle.net/2142/31088 Marcus, B. H., Selby, V. C., Niaura, R. S., & Rossi J. S. (1992). Self-efficacy and the stages of exercise behavior change. Research Quarterly for Exercise and Sport, 63 (1), 60-66. Marcus, B. H., Dubbert, P. M., Forsyth, L. H., McKe nzie, T. L., Stone, E. J., Dunn, A. L., & Blair. (2000). Physical activity behavior change: Issues in adoption and maintenance. Health Psychology, 19 (1 Suppl.), 32-41. Marshall, S. J., & Biddle, S. J. (2001). The transt heoretical model of behavior change: A meta-analysis of applications to physical activity and exercise. Annals of Behavioral Medicine, 23 (4), 229-246. Martin, S. B., Morrow, J. R., Jr., Jackson, A. W., & Dunn, A. L. (2000). Variables related to CDC/ACSM physical activity guidelines. Medicine and Science in Sports and Exercise, 32 (12), 2087-2092. Mather, A. S., Rodriguez, C., Guthrie, M. F., McHar g, A. M., Reid, I. C., & McMurdo, M. T. (2002). Effects of exercise on depressive sym ptoms in older adults with poor responsive depressive disorder: Randomized con trolled trial. British Journal of Psychiatry, 180, 411-415. Mayo Clinic. (2010). Menopause weight gain: Stop th e middle age spread. MayoClinic.com. Retrieved from http://www.mayoclinic.com/health/menopauseweight-gain/HQ01076

PAGE 73

64 McAuley, E. (1992). The role of efficacy cognitions in the prediction of exercise behavior in middle-aged adults. Journal of Behavioral Medicine, 15 (1), 65-88. McAuley, E., Bane, S. M, & Mihalko, S. L. (1995). E xercise in middle-aged adults: Selfefficacy and self-presentational outcomes. Preventive Medicine, 24 319-328. McAuley, E., Bane, S. M., Rudolph, D. L., & Lox, C. L. (1995). Physique anxiety and exercise in middle-aged adults. Journal of Gerontology: Psychological Sciences, 50B (5), 229-235. McAuley, E., Marquez, D. X., Jerome, G. J., Blissme r, B., & Katula, J. Physical activity and physique anxiety in older adults: Fitness and e fficacy influnences. Aging Mental Health, 6 (3), 222-230. McAuley, E., & Mihalko, S. L. (1998). Measuring exe rcise-related self-efficacy. In J. L. Duda (Ed.), Advances in sport and exercise psychology measureme nt (pp. 371390). Miller, W. R., & Rollnick, S. R. (2002). Motivational interviewing: Preparing people to change behavior – Second edition. New York: Guilford Press. Mokdad, A. H., Marks, J. S., Stroup, D. F., Gerberd ing, J. L. (2004). Actual causes of death in the United States, 2000. JAMA, 291 (10), 1238-1245. Morris, K. S., McAuley, E., & Motl, R. W. (2008). N eighborhood satisfaction, functional limitations, and self-efficacy influences on physic al activity in older women. International Journal of Behavioral Nutrition and P hysical Activity, 5, (13), doi:10.1186/1479-5868-5-13.

PAGE 74

65 Norman, G. J., Benisovich, S. V., Nigg, C. R., Ross i, J. S. (1998). Examining three exercise staging algorithms in two samples. Annals of Behavioral Medicine, 20 S211. Ogden, C. L., Carroll, M. D., Kit, B. K., Flegal, K M. (2014). Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA, 311 (8), 806-814. Oman, R. F., & Duncan, T. E. (1995). Women and exer cise: An investigation of the roles of social support, self-efficacy, and hardiness. Medicine, Exercise, Nutrition, and Health, 4 306-315. Ostir, G. V., Cohen-Mansfield, J., Leveille, S., Vo lpato, S., Guralnik, J. M. (2003). The association of positive and negative affect and exe rcise self-efficacy in older adults. Journal of Aging and Physical Activity, 11 265-274. Paluska, S. A., & Schwenk, T. L. (2000). Physical a ctivity and mental health. Sports Medicine, 29 (3), 167-180. Pavey, T. G., Taylor, A. H., Fox, K. R., Hillsdon, M., Anokye, N., Campbell, J. L.,Â…Taylor, R. S. (2011). Effect of exercise referr al schemes in primary care on physical activity and improving health outcome: Sys tematic review and metaanalysis. British Medical Journal, 343 1-14. Perri, M. G., Martin, A. D., Leermakers, E. A., Sea rs, S. F., Notelovits, M. (1997). Effects of group-versus home-based exercise in the treatment of obesity. Journal of Consulting and Clinical Psychology, 65 (2), 278-285. Petersen, L., Schnohr, P., Sorensen, T. I. A.. (200 4) Longitudinal study of long-term relation between physical activity and obesity in a dults. International Journal of Obesity, 28 105-112.

PAGE 75

66 Powell, K. E., Thompson, P. D., Caspersen, C. J., & Kendrick, J. S. (1987). Physical activity and the incidence of coronary heart diseas e. Annual Review of Public Health, 8 253-287. Prochaska, J. O., & DiClemente, C. C. (1982). Trans theoretical therapy: Toward a more integrative model of change. Psychotherapy: Theory, Research, and Practice, 19 276-288. Prochaska, J. O. & DiClemente, C. C. (1983). Stages and processes of self-change in smoking: Towards an integrative model of change. Journal of Counseling and Clinical Psychology, 51 390-395. Prochaska, J. O., DiClemente C. C., Velicer, W. F., & Rossi, J. S. (1993). Standardized, individualized, interactive, and personalized selfhelp programs for smoking cessation. Health Psychology, 12 399-405. Prochaska, J. O., Redding, C. A., & Evers, K. E. (1 997). The transtheoretical model and stages of change. In K. Glanz, F. M. Lewis, and B. K. RImer (Eds.), Health behavior and health education: Theory research and practice (2T ed.) (pp. 60-84). San Francisco, CA: Josey-Bass Inc. Pruitt, L. A., King, A. C., Obarzanek, E., Miller, M., OÂ’Toole, M., Haskell, W. L., . Reynolds, S. (2006). Reliability of the 7-day physi cal activity recall in a biracial group of inactive and active adults. Journal of Physical Activity and Health, 3 423-438. Purath, J. (2006). Comparison of the traits of phys ically active and inactive women. Journal of the American Academy of Nurse Practition ers, 18 234-240.

PAGE 76

67 Ransdell, L. B., Wells, C. L., Manore, M. M., Swan, P. D., & Corbin, C. B. (1998). Social physique anxiety in postmenopausal women. Journal of Women & Aging, 10 (3). 19-39. Rapee, R. M. & Heimberg, R. G. (1997). A cognitivebehavioral model of anxiety in social phobia. Behavior Research and Therapy, 35 741-756. Rodgers, W. M., Courneya, K. S., & Bayduza, A. L. ( 2001). Examination of the transtheoretical model and exercise in 3 population s. American Journal of Health Behavior, 25 (1), 33-41. Rogers, W. M., & Sullivan, M. J. L. (2001). Task, c oping, and scheduling self-efficacy in relation to frequency of physical activity. Journal of Applied Social Psychology, 31 741-753. Rossi, J. S., Blais, L. M., Redding, C. A., Weinsto ck, M. A., (1995). Behavior change for reducing sun and ultraviolet light exposure: Implic ations for interventions. Determatologic Clinics, 13 613-622. Rubak, S., Sandboek, A., Laurittzen, T., & Christen sen, B. (2005). Motivational interviewing: A systematic review and meta-analysis British Journal of General Practice, 55 305-312. Sallis, J. F., Hovell, M. F., Hofstetter, C. R., & Barrington, E. (1992). Explanation of vigorous physical activity during two years using s ocial learning variables. Social Science and Medicine, 34 25-32.

PAGE 77

68 Schumann, A., Nigg, C. R., Rossi, J. S., Jordan, P. J., Norman, G. J., Garber, C. E., Â…Benisovich, S. V. (2002). Construct validity of th e stage of change for exercise adoption for different intensities of physical acti vity in four samples of differing age groups. American Journal of Health Promotion, 16 (5), 280-287. Scott, L. A. (2005). Effects of exercise and a brief education intervent ion on social physique anxiety in students. (Masters thesis). Retrived from http://digitalcommons.georgiasouthern.edu/etu Sechrist, K. R., Noble Walker, S., Pender, N. J. (1 987). Development and psychometric evaluation of the exercise benefits/barriers scale. Research in Nursing and Health, 10 (6), 357-365. Secord, P.F., & Jourard, S. M. (1953). The appraisa l of body cathexsis: Body cathexsis and the self. Journal of Consulting Psychology, 17 (5), 343-347. Shangold, M. M., & Sherman, C. (1998). Exercise and menopause: A time for positive changes. The Physician and Sports Medicine, 26 (12), 45-50. Simonavice, E. M., & Wiggins, M. S. (2008). Exercis e barriers, self-efficacy, and stages of change. Perceptual and Motor Skills, 107 946-950. Stetson, B. A., Beacham, A. O., Frommelt, S. J., Bo utelle, K. N., Cole, J. D., Siegler, C. H., Looney, S. W. (2005). Exercise slips in high-ri sk situations and activity patterns in long-term exercisers: An application of the Relapse Prevention Model. Annals of Behavioral Medicine, 30 (1), 25-35. Sullum, J., & Clark, M. (2000). Predictors of exerc ise relapse in a college population. Journal of American College Health, 48 175-180.

PAGE 78

69 Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th edition) Boston: Allyn and Bacon. Turk, C. L., Heimberg, R. G., Magee, L. (2008). Soc ial anxiety disorder. In D. H. Barlow (Ed). Clinical handbook of psychological disorders: A ste p-by-step treatment manual (4th ed.) (pp. 123-163). New York, NY: The Guilford Press U.S. Department of Health and Human Services. (2008 ). Physical activity guidelines for Americans. http://www.health.gov/paguidelines/pdf/paguide.pdf U.S. Department of Health and Human Services: Physical Activity and Health: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Preventio n and Health Promotion, 1996. Watson, D., Clark, L. A., & Tellegen, A. (1988). De velopment and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54 (6), 1063-1070. Weuve, J., Kang, J. H., Manson, J. E., Breteler, M. B., Ware, J. H., Grodstein, F. (2004). Physical activity, including walking, and cognitive function in older women, JAMA, 292 (12), 1454-1461. Wilcox, S., King, A. C., Brassington, G. S., & Ahn, D. K. (1999). Physical activity preferences of middle-aged and older adults: A comm unity analysis. Journal of Aging and Physical Activity, 7 386-399. Williams, P., & Cash, T. F. (2001). Effects of a ci rcuit weight training program on the body images of college students. International Journal of Eating Disorders, 30 (1), 75-82.

PAGE 79

70 Williams, D. M., Dunsiger, S., Ciccolo, J. T., Lewi s, B. A., Albrecht, A. E., & Marcus, B. H. (2008). Acute affective response to a moderate-i ntensity exercise stimulus predicts physical activity participation 6 and 12 m onths later. Psychology of Sport and Exercise, 9 231-245. Woodgate, J., & Martin Ginis, K. A., & Sinden, A. R (2003). Physical activity and social physique anxiety in older women: The moderating eff ects of self-presentation efficacy. Journal of Applied Biobehavioral Research, 8 (2), 116-127. World Health Organization (2012, May). Fact sheet. Retrieved from http://www.who.int/mediacentre/factsheets/fs311/en/ World Health Organization (2014, May). BMI classifi cation. Retrieved from http://apps.who.int/bmi/index.jsp?introPage=intro_3 .html Yaffe, K., Barnes, D., Nevitt, M., Lui, L., & Covin sky, K. (2001). A prospective study of physical activity and cognitive decline in elderly women: Women who walk. Archives of Internal Medicine, 161 (14), 1703-1708.

PAGE 80

71 APPENDIX A Confidential Women's Health Survey You are being invited to participate in a research study sponsored by the University of Colorado Denver. Please read the information below before deciding whether or not to take part. You can adjust the font size by using th e tools in the upper right hand corner of the screen. Why is this study being done? You are being asked to be in this research study be cause you are interested in participating in web-based research and meet our el igibility requirements. We are interested in learning about factors related to exe rcise in mid-life women. We will try to recruit 170 people to participate in the study. What happens if I join this study? If you join the study, you will be asked to fill ou t an anonymous online survey that should take approximately 15 minutes to complete. You are asked to complete the survey honestly and on your own (privately). What are the possible discomforts or risks? It is possible that you may experience some emotion al discomfort from answering questions about exercise beliefs and habits, feelin gs about your appearance and body, and your mood. You may also be concerned that others us ing the same computer may see your answers, so please complete the questionnaire privately in a confidential place. Although your browser history could show that you v isited the survey, it would not show your answers to the survey questions. If you wish t o reduce the chance that other users on this computer could see that you viewed the survey site, it is suggested that you clear your browser history when completing the survey (in structions below). Additionally, you may choose to not respond to any questions you find uncomfortable to answer. What are the possible benefits of the study? This research may help us better understand the fac tors related to exercise in mid-life women and will serve as a guide for future research By taking part in this research, you may gain a better understanding of your beliefs abo ut exercise and motivations and/or barriers to participation in exercise. Who is paying for this study? This research is being paid for by the University o f Colorado Denver. Will I be paid for being in the study? Will I have to pay for anything? You will be paid a $5.00 Amazon Gift Card upon comp letion of the study. It will not cost you anything to be in the study.

PAGE 81

72 Is my participation voluntary? Taking part in this study is voluntary. You have th e right to choose not to take part in this study. If you choose to take part, you have the rig ht to stop at any time without penalty. Who do I call if I have questions? The primary researcher carrying out this study is D ana Brown of the University of Colorado Denver. You may ask any questions you have by email or phone: dana.brown@ucdenver.edu or 303-556-5284. You may have questions about your rights as someone in this study. You can call Dana Brown or the University of Colorado Denver Institut ional Review Board (IRB) at 303724-1055 to answer any questions about your rights. Who will see my research information? Your responses will be anonymous, as there will be no record of your name or other identifying information associated with your respon ses. Please do not put your name or contact information anywhere on the survey. The ans wers on the survey will be kept on a secure server and only the researchers will have ac cess. The researchers may be required to share the data with federal agencies that monito r human subject research, the IRB, and regulatory officials from the institution where the research is being conducted who want to make sure the research is safe. The results from the research will be averaged across all the participants, and may be published or presented at research conferences and in a research journal. Again, the study is anonymous so that there will be no way to identify you in this data. Clearing your browser history: You may wish to delete your browser history to redu ce the chances that other users on this computer can view that you visited the survey site. Even after clearing the browser history it is possible for someone to see that you visited the survey, but they would not be able to see your responses. You can clear your brow ser history using the following instructions: If you use Internet Explorer, clear browser history by clicking "Safety" and then choose "Delete Browsing History". Make sure the box next t o "History" is checked and click "Delete". If you use Mozilla Firefox, clear browsing history by clicking "Tools" and then choose "Clear Recent History". Choose the "Last Four Hours from the drop down menu (or longer if you spent more time than four hours on th e survey) and make sure the box next to "Browsing and Download History" is checked under "Details". To finish click "Clear Now". If you use Safari, clear browser history by clickin g the Settings button, which looks like a gear. Under "Collections" on the left side, click History". Click on the webistes under "Last Visited Today" and select the RedCap website. Then, press "Delete" on your keyboard.

PAGE 82

73 If you use Google Chrome, clear browser history by clicking the "Settings" button, which looks like a wrench. Select "History" and then clic k "Edit Items". Check the box next to any RedCap website and click "Remove Selected Items ". If you wish to keep a copy of this page you may pri nt it now. What is your StudyResponse ID number? AGREEMENT TO BE IN THIS STUDY I have read the page about the study. I understand the possible risks and benefits of this study. I know that being in this study is voluntary. I choose to be in this study. If you wish to keep a copy of this page, you may print it or copy it now. ™ I agree ™I do not want to participate in this study What are you being asked to do in this study? ™Complete an online survey privately and honestly ™Complete a telephone survey ™Complete an online survey with other people ™Complete a survey in person Please finish this sentence: The purpose of this st udy is ™To better understand an individual's relationship w ith their parents ™To better understand factors related to exercise in women ™To find out people's preferences in restaurants ™To learn about different individual's pets True or false: After beginning this study, you can decide not to continue at any time, without penalty. ™True ™False What should you do if you have questions about the study? ™Call the local police ™Call or email Dana Brown ™Call the head of the University

PAGE 83

74 APPENDIX B What is your current age? Do you currently live in the United States? ™Yes ™No In what state do you reside? Are you pregnant? ™ Yes ™ No Do you have a primary medical provider that you see for routine care? ™ Yes ™ No Have you visited your primary medical provider with in the last 12 months? ™ Yes ™ No When is the last time you visited your primary medi cal provider for any reason (annual physical, illness, etc.)? ™ Within the last month ™ 2 months ago ™ 3 months ago ™ 4 months ago ™ 5 months ago ™ 6 months ago ™ 7 months ago ™ 8 months ago ™ 9 months ago ™ 10 months ago ™ 11 months ago ™ 12 months ago Do you have an illness, injury, or condition that p revents you from exercising? ™ Yes ™ No

PAGE 84

75 What is your current height in feet and inches? E.g 5 feet, 6 inches? What is your current weight in pounds? How would you describe yourself? ™ American Indian/Alaska Native ™ Asian ™ Hispanic or Latino ™ Native Hawaiian or other Pacific Islander ™ Black or African American ™ White (not of Hispanic origin) ™ Other How many years of education have you completed? (EXAMPLE: high school + 1 year of college = 13 year s of education) Are you currently employed? ™ Yes ™ No What is your current occupation? What is your current relationship status? ™ Single ™ Married/Partnered Do you have children (under 18 years) living at hom e? ™ Yes ™ No If yes, how many?

PAGE 85

76 APPENDIX C Regular Exercise is any physical activity that is p lanned, structured, and repetitive and has a final or an intermediate objective the improv ement or maintenance of physical fitness (e.g., brisk walking, aerobics, jogging, bi cycling, swimming, rowing, etc.). Such activity is performed 3 or more times per week for 20 or more minutes per session at a level that increases your breathing rate and causes you to break a sweat. Do you exercise regularly according to the definiti on above? Mark the one statement that applies to you. Yes, I have been exercising regularly for more th an 6 months. Yes, I have been exercising regularly, but for le ss than 6 months. No, but I intend to exercise regularly in the nex t 30 days. No, but I intend to exercise regularly in the nex t 6 months. No, and I do not intend to exercise regularly in the next 6 months.

PAGE 86

77 APPENDIX D The following items reflect situations that are lis ted as common reasons for preventing individuals from participating in exercise sessions or, in some cases, dropping out. Using the scales below please indicate how confident you are that you could exercise in the event that any of the following circumstances were to occur. Please indicate the degree to which you are confide nt that you could exercise in the event that any of the following circumstances were to occ ur by circling the appropriate %. Select the response that most closely matches your own, remembering that there are no right or wrong answers. FOR EXAMPLE: In the first question, if you have complete confide nce that you could exercise even if “the weather was very bad,” you would select 100%. If ho wever, you had no confidence at all that you could exercise (that is, confidence you wo uld not exercise), you would select 0%. I believe that I could exercise 3 times per week fo r the next 3 months if: The weather was very bad (hot, humid, rainy, cold). ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I was bored by the program or activity. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80%

PAGE 87

78™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I was on vacation. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I was not interested in the activity. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I felt pain or discomfort when exercising. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80%

PAGE 88

79™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I had to exercise alone. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: It was not fun or enjoyable. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: It became difficult to get to the exercise location ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80%

PAGE 89

80™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I didn't like the particular activity program that I was involved in. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: My schedule conflicted with my exercise session. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I felt self-conscious about my appearance when I ex ercised. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80%

PAGE 90

81™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: An instructor does not offer me any encouragement. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident I believe that I could exercise 3 times per week fo r the next 3 months if: I was under personal stress of some kind. ™0% Not at all confident ™10% ™20% ™30% ™40% ™50% Moderately confident ™60% ™70% ™80% ™90% ™100% Highly confident

PAGE 91

82 APPENDIX E Please indicate the degree to which the statement i s characteristic or true of you on the following scale. I am comfortable with the appearance of my physique /figure ™Not at all ™Slightly ™Moderately ™Very ™Extremely I would never worry about wearing clothes that migh t make me look too thin or overweight ™Not at all ™Slightly ™Moderately ™Very ™Extremely I wish I wasn’t so uptight about my physique/figure ™Not at all ™Slightly ™Moderately ™Very ™Extremely There are times when I am bothered by thoughts that other people are evaluating my weight or muscular development negatively ™Not at all ™Slightly ™Moderately ™Very ™Extremely When I look in the mirror I feel good about my phys ique/figure ™Not at all ™Slightly ™Moderately ™Very ™Extremely

PAGE 92

83 Unattractive features of my physique/figure make me nervous in certain settings ™Not at all ™Slightly ™Moderately ™Very ™Extremely In the presence of others, I feel apprehensive abou t my physique/figure ™Not at all ™Slightly ™Moderately ™Very ™Extremely I am comfortable with how fit my body appears to ot hers ™Not at all ™Slightly ™Moderately ™Very ™Extremely If would make me uncomfortable to know others were evaluating my physique/figure ™Not at all ™Slightly ™Moderately ™Very ™Extremely When it comes to displaying my physique/figure to o thers, I am a shy person ™Not at all ™Slightly ™Moderately ™Very ™Extremely I usually feel relaxed when it is obvious that othe rs are looking at my physique/figure ™Not at all ™Slightly ™Moderately ™Very

PAGE 93

84™Extremely When in a bathing suit, I often feel nervous about the shape of my body ™Not at all ™Slightly ™Moderately ™Very ™Extremely

PAGE 94

85 APPENDIX F This scale consists of a number of words that descr ibe different feelings and emotions. Read each item and then indicate the appropriate an swer next to that word. Indicate to what extent you have felt this way DURING THE PAST WEEK. Interested ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Distressed ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Excited ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Upset ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Strong ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely

PAGE 95

86 Guilty ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Scared ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Hostile ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Enthusiastic ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Proud ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Irritable ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely

PAGE 96

87 Alert ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Ashamed ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Inspired ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Nervous ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Determined ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Attentive ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely

PAGE 97

88 Jittery ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Active ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely Afraid ™Very slightly or not at all ™A little ™Moderately ™Quite a bit ™Extremely

PAGE 98

89 APPENDIX G Please report the FREQUENCY and average DURATION of any exercise OVER THE PAST WEEK. As an example, if you exercised 4 times last week a t a moderate intensity, you would select "4" for FREQUENCY next to moderate exercise. We would also like you to give an average of the time you spent exercising. In our example, if two of those "4" exercise sessions were 30 minutes and the other two were 20 minutes, you would put 25 minutes for DURATION next to moderate exercise. When answering these questions, please remember to: a) Only count the exercise that was done in your fr ee time (i.e., not occupational or housework) b) Note that the difference between the three categ ories is the intensity of the exercise. c) If you did not participate in a type of exercise select "0" from the drop-down list. FREQUENCY of STRENUOUS EXERCISE (Heart beats regula rly, sweating) Examples: running, jogging, vigorous swimming, vigo rous long distance bicycling, vigorous aerobic dance classes. How many times in the last week did you engage in STRENUOUS EXERCISE? DURATION of STRENUOUS EXERCISE (Heart beats regular ly, sweating) Examples: running, jogging, vigorous swimming, vigo rous long distance bicycling, vigorous aerobic dance classes How many minutes on the average did you spend per s ession of STRENUOUS EXERCISE? FREQUENCY of MODERATE EXERCISE (Not exhausting, lig ht perspiration) Examples: fast walking, tennis, easy bicycling, eas y swimming, popular and folk dance How many times in the last week did you engage in M ODERATE EXERCISE? DURATION of MODERATE EXERCISE (Not exhausting, ligh t perspiration) Examples: fast walking, tennis, easy bicycling, eas y swimming, popular and folk dance How many minutes on the average did you spend per s ession of MODERATE EXERCISE? FREQUENCY of MILD EXERCISE (Minimal effort, no pers piration) Examples: easy walking, yoga, bowling, shuffleboard, horsesho es, golf How many times in the last week did you engage in M ILD EXERCISE?

PAGE 99

90 DURATION of MILD EXERCISE (Minimal effort, no pers piration) Examples: easy walking, yoga, bowling, shuffleboard, horsesho es, golf How many minutes on the average did you spend per s ession of MILD EXERCISE?

PAGE 100

91 APPENDIX H Please rate your level of interest in participating in the following activities on a scale of 0 to 10, with 0 being no interest and 10 being m ost interest. Walking/hiking (outdoors) Walking (treadmill) Jogging (outdoors) Jogging (treadmill) Biking (outdoors) Biking (stationary) Swimming Dancing (Line dancing, zumba, etc.) Group fitness class Yoga/Pilates Weight lifting Team sport (Volleyball, softball, etc.) Tennis/Racquetball Golf Gymnastics

PAGE 101

92 APPENDIX I Please rate the likelihood that you would engage in the following activities on a scale of 0 to 10, with 0 being not at all likely and 10 b eing extremely likely. Exercise alone at home. Exercise alone outdoors. Exercise alone at a fitness center or gym. Exercise with a friend at home. Exercise with a friend outdoors. Exercise with a friend at a fitness center or gym. Exercise in a group at home. Exercise in a group outdoors. Exercise in a group at a fitness center or gym.

PAGE 102

93 TABLES Table 1. Participant demographics. Variable Mean ( SD ) Frequency (%) Range Age 46.0 (6.4) 35 55 Race/ethnicity White (Not of Hispanic origin) 122 (87.1%) Black or African American 6 (4.3%) Asian 6 (4.3%) Hispanic or Latino 3 (2.1%) American Indian/Alaska Native 1 (.7%) Other 1 (.7%) Years of education completed 15.2 (2.6) 10 2 3 Employment status Currently employed 110 (78.6%) Not employed 29 (20.7%) Relationship status Single 36 (25.7%) Married / Partnered 104 (74.3%) Children under 18 living at home Yes 64 (45.7%) No 76 (54.3%) Number of children under 18 living at home 2.0 (1.2 7) 1 6 Height (inches) 64.5 (2.5) Weight (pounds) 176.8 (51.1) Body Mass Index (BMI) 29.9 (8.6) Underweight (< 18.5) 2 (1.4%) Normal (18.5-24.99) 47 (33.6%) Overweight (25-29.99) 38 (27.1%) Obese Class I (30-34.99) 18 (12.9%) Obese Class II (35-39.99) 13 (9.3% Obese Class III ( 40) 20 (14.3%) *BMI ranges are per the International Classificatio n of BMI (World Health Organization, 2014).

PAGE 103

94 Table 2. Mean standard values for Social Physique A nxiety (SPA), self-efficacy, Positive Affect (PA), Negative Affect (NA) and BMI for the f ive stages of change for exercise. Two participants were excluded from the table due t o missing values. Dependent variable Stage of change M SD N SPA Precontemplation 46.40 8.22 10 Contemplation 40.97 7.83 31 Preparation 44.00 10.06 34 Action 42.61 6.52 25 Maintenance 36.41 9.00 38 Total 41.15 9.07 138 Self-efficacy Precontemplation 16.30 16.62 10 Contemplation 32.13 14.80 31 Preparation 39.94 15.72 34 Action 51.72 15.38 25 Maintenance 68.40 20.25 38 Total 46.44 23.23 138 PA Precontemplation 24.80 4.59 10 Contemplation 27.03 6.63 31 Preparation 27.90 7.57 34 Action 30.51 6.29 25 Maintenance 35.53 7.94 38 Total 30.05 7.90 138 NA Precontemplation 23.50 12.30 10 Contemplation 18.59 6.24 31 Preparation 18.09 6.18 34 Action 19.12 7.32 25 Maintenance 16.94 6.42 38 Total 18.47 7.12 138 BMI Precontemplation 33.84 11.38 10 Contemplation 32.08 8.44 31 Preparation 31.83 9.41 34 Action 29.44 7.28 25 Maintenance 25.62 6.44 38 Total 29.89 8.61 138

PAGE 104

95 Table 3. Analyses of variance comparing mean differ ences in SPA, self-efficacy, PA, NA and BMI across the five stages of change for exercise. Dependent variable df F p SPA 4, 133 4.94 .001 Self-efficacy 4, 133 31.36 .000 PA 4, 133 9.28 .000 NA 4, 133 1.81 .131 BMI 4, 133 4.16 .003

PAGE 105

96 Table 4. SheffeÂ’ post-hoc comparisons for differenc es in SPA between the stages of change for exercise. Precont Cont Prep Action Maint Precont ---* Cont ---Prep ---** Action ---Maint ---* = p < .05, ** = p < .01

PAGE 106

97 Table 5. Number of participants classified into the stages of change compared to actual stage membership using SPA as a singular pre dictor variable. Percentages represent accuracy or correct classification. Number predicted by actual participants in each sta ge of change and (%) of correct categorization Pre Cont Prep Action Maint Pre 5 / 10 (50%) 2 / 0 (0%) 1 / 10 (0%) 0 / 0 (100 %) 2 / 0 (0%) Cont 9 / 0 (0%) 8 / 32 (25%) 1 / 0 (0%) 5 / 0 (0%) 9 / 0 (0%) Prep 16 / 0 (0%) 2 / 0 (0%) 5 / 34(14.7%) 1 / 0 (0% ) 10 / 0 (0%) Action 8 / 0 (0%) 4 / 0 (0%) 4 / 0 (0%) 2 / 26 (7.7 %) 8 / 0 (0%) Maint 5 /0 (0%) 7 /0 (0%) 2 / 0 (0%) 2 / 0 (0%) 22 / 38 (57.9%)

PAGE 107

98 Table 6. Number of participants classified into the stages of change compared to actual stage membership using self-efficacy as a si ngular predictor variable. Percentages represent accuracy or correct classification. Number predicted by actual participants in each sta ge of change and (%) of correct categorization Pre Cont Prep Action Maint Pre 7 / 10 (70%) 2 / 0 (0%) 0 / 0 (100%) 1 / 0 (0% ) 0 / 0 (100%) Cont 9 / 0 (0%) 10 / 32 (25%) 8 / 0 (0%) 2 / 0 (0%) 3 / 0 (0%) Prep 4 / 0 (0%) 11 / 0 (0%) 8 / 34 (23.5%) 7 / 0 (0 %) 4 / 0 (0%) Action 1 / 0 (0%) 2 / 0 (0%) 6 / 0 (0%) 9 / 26 (34. 6%) 8 / 0 (0%) Maint 1 / 0 (0%) 2 / 0 (0%) 2 / 0 (0%) 7 / 0 (0%) 2 6 / 38 (68.4%)

PAGE 108

99 Table 7. Number of participants classified into the stages of change compared to actual stage membership using both self-efficacy an d SPA as predictor variables. Percentages represent accuracy or correct classific ation. Number predicted by actual participants in each sta ge of change and (%) of correct categorization Pre Cont Prep Action Maint Pre 8 / 10 (80%) 1 / 0 (0%) 0 / 0 (100%) 1 / 0 (0%) 0 / 0 (100%) Cont 9 / 0 (0%) 13 / 32 (40.6%) 5 / 0 (0%) 2 / 0 (0%) 3 / 0 (0%) Prep 5 / 0 (0%) 6 / 0 (0%) 11 / 34 (32.4%) 7 / 0 (0%) 5 / 0 (0%) Action 0 / 0 (0%) 5 / 0 (0%) 4 / 0 (0%) 11 / 26 (42.3%) 6 / 0 (0%) Maint 1 / 0 (0%) 4 / 0 (0%) 1 / 0 (0%) 4 / 0 (0%) 28 / 38 (73.7%)

PAGE 109

100 Table 8. SheffeÂ’ post-hoc comparisons for self-effi cacy between the stages of change for exercise. Precont Cont Prep Action Maint Precont ---** *** *** Cont ---** *** Prep ---*** Action ---* Maint ---* = p < .05, ** = p < .01, *** = p < .001

PAGE 110

101 Table 9. SheffeÂ’ post-hoc comparisons for PA betwee n the stages of change for exercise. Precont Cont Prep Action Maint Precont ---** Cont ---*** Prep ---** Action ---Maint ---** = p < .01, *** = p < .001

PAGE 111

102 Table 10. SheffeÂ’ post-hoc comparisons for BMI betw een the stages of change. Precont Cont Prep Action Maint Precont ---Cont ---* Prep ---* Action ----Maint ----* = p < .05

PAGE 112

103 Table 11. Analyses of variance comparing mean diffe rences in exercise preferences for company and location across the fiv e stages of change. Dependent variable df F p Alone 4, 127 8.00 .000 Friend 4, 127 3.01 .021 Group 4, 127 3.09 .018 Home 4, 127 4.64 .002 Outdoors 4, 127 5.90 .000 Gym 4, 127 3.33 .013

PAGE 113

Figure 1 Mean scores for SPA by stages of change of contemplation, preparation, action, and maintenance maintenance was significantly different from precon templators ( ( p < .01) FIGURES Mean scores for SPA by stages of change of precontemplation, contemplation, preparation, action, and maintenance A cubic relationship was observed; maintenance was significantly different from precon templators ( p < .05) and 104 precontemplation, A cubic relationship was observed; < .05) and preparation

PAGE 114

Figure 2 Mean scores for self precontemplation, contemplation, prepara were significant between maintenance and precontemp lation, contemplation, and preparation ( p < .001) as well as between maintenance and actio were also significant between action and both preco ntemplation and contemplation ( .001 and p < .01 respectively) as well as between preparation and precontemplation ( .01) Mean scores for self -efficacy by st ages of change for exercise of precontemplation, contemplation, prepara tion, action, and maintenance. Differences were significant between maintenance and precontemp lation, contemplation, and < .001) as well as between maintenance and actio n ( p < .05). Differences were also significant between action and both preco ntemplation and contemplation ( < .01 respectively) as well as between preparation and precontemplation ( 105 ages of change for exercise of tion, action, and maintenance. Differences were significant between maintenance and precontemp lation, contemplation, and < .05). Differences were also significant between action and both preco ntemplation and contemplation ( p < < .01 respectively) as well as between preparation and precontemplation ( p <

PAGE 115

Figure 3 Mean scores for PA by stages of change precontemplation, contemplation, preparation, actio n, and maintenance. were significant between the maintenance and both t he precontemplation and preparation stages ( p < .01) as well as between maintenance and contempla tion ( Mean scores for PA by stages of change for exercise of precontemplation, contemplation, preparation, actio n, and maintenance. were significant between the maintenance and both t he precontemplation and preparation < .01) as well as between maintenance and contempla tion ( p < .001) 106 for exercise of Differences were significant between the maintenance and both t he precontemplation and preparation < .001)

PAGE 116

Figure 4. Mean BMI values by stages of change for e xercise of precontemplation, contemplation, preparation, action, and maintenance between maintenance and both the contemplation and preparation stages ( Figure 4. Mean BMI values by stages of change for e xercise of precontemplation, contemplation, preparation, action, and maintenance Differences were significant between maintenance and both the contemplation and preparation stages ( 107 Figure 4. Mean BMI values by stages of change for e xercise of precontemplation, Differences were significant between maintenance and both the contemplation and preparation stages ( p < .05).

PAGE 117

Figure 5. Mean NA scores contemplation, preparation, action, and maintenance Figure 5. Mean NA scores by stages of change for exercise of precontemplatio n, contemplation, preparation, action, and maintenance 108 by stages of change for exercise of precontemplatio n,