This item has the following downloads:
1 PERSONAL AND COGNITIVE VARIABLES AS PREDICTORS OF ENGAGEMENT IN PHYSICAL ACTIVITY AMONG A CULTURALLY DIVERSE SAMPLE OF OLDER ADULTS By SARAH ELIZABETH MADISON NOLAN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UN IVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2013
2 2013 Sarah Elizabeth Madison Nolan
3 To the women who paved the way, Anne G annon Nolan and Claire Glennon Madison
4 ACKNOWLEDGMENTS I want to especially thank my chairperson and advisor, Dr. Carolyn Tucker, whose guidance, support, and training have helped tremendously throughout the past five years of my doctoral program and have greatly assisted in shaping my future I am also thankful for the guidance and assistance given to me by my committee members, Dr. Robin West Dr. Edil Torres Rivera and Dr. Chun Chung Choi and my former committee members, Dr. Darlene Kertes and Dr Ken Rice Additionally, I am grateful to Dr. Michael Marsiske and Dr. Susan Nayfield for their gui da nce with the methodology of this project. I am grateful to the entire counseling psychology faculty the Counseling and Wellness Center faculty and staff, and the staff and volunteers at the Alachua County Crisis Center for facilitating my personal and professional growth over the las t five years. I would also like to thank my friend s the Chiu family for inspiring me daily to continue to pursue my dreams. Lastly I want to thank my loved ones for their support, ve happened.
5 TABLE OF CONTENTS page ACKNOWLEDGME NTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 11 Obesity and Related Diseases in the Aging Population ................................ .......... 11 Sex and Race/Ethnicity Differences in Obesity and Related Diseases ................... 13 Physical Activity and Obesity in the Aging Population ................................ ............ 14 Theoretical Framework ................................ ................................ ........................... 16 Present Study ................................ ................................ ................................ ......... 18 2 REVIEW OF THE LITERATURE ................................ ................................ ............ 20 Engagement in Physical Activity ................................ ................................ ............. 20 Personal and Cognitive Variables of Health Self Empowerment Theory ................ 21 Personal and Cognitive Variables and Engagement in ................................ ........... 24 Physical Activity ................................ ................................ ................................ ...... 24 Health Motivation and Engagement in Physical Activity ................................ ... 25 Health Self Praise and E ngagement in Physical Activity ................................ .. 26 Adaptive Coping and Engagement in Physical Activity ................................ .... 26 Health Responsibility and Engagement in Physical Activity ............................. 26 Health Self Efficacy and Engagement in Physical Activity ............................... 27 Associations between Demographic Variables and Variables of this Study ............ 28 Sex and Personal and Cognitive Variables ................................ ...................... 29 Sex and Engagement in Physical Activity ................................ ......................... 30 Race/Ethnicity and Personal and Cognitive Variables ................................ ...... 30 Race/Ethnicity and Engagement in Physical Activity ................................ ........ 31 Other Variables that May Impact Study Variables ................................ .................. 32 Impact of Education Level ................................ ................................ ................ 32 Impact of Physic al and Mental Health ................................ .............................. 32 3 METHODS ................................ ................................ ................................ .............. 34 Participants ................................ ................................ ................................ ............. 34 Measures ................................ ................................ ................................ ................ 35 Demographic Data Questionnaire ................................ ................................ .... 35 Health Self Praise Questionnaire ................................ ................................ ..... 35 Physical Fitness and Exercise Activity of Older Adults Scale ........................... 36 Coping Responses Inventory ................................ ................................ ........... 37
6 Perceived Health Competence Scale ................................ ............................... 37 Health Promotion Activities of Older Adults Measure ................................ ....... 38 Short Form Health Survey 12 ................................ ................................ ........... 39 Montreal Cognitive Assessment ................................ ................................ ....... 40 Procedure ................................ ................................ ................................ ............... 40 4 RESULTS ................................ ................................ ................................ ............... 45 Descriptive Data for all Major Variables ................................ ................................ .. 45 Reliability of Instruments ................................ ................................ ......................... 45 Results of the Preliminary Pearson Correlation Analysis ................................ ........ 46 Health Self Empowerment Theory Variable Associations ................................ 47 Associations between Theory Variables an d Physical Activity Variable ........... 47 Results of the Analyses to Test Hypothesis 1 Examining the Relationship between the Health Self Empowerment Theory Variables and Engagement in Physical Activity ................................ ................................ ................................ ... 48 Results of the Analyses to Test Hypothesis 2 Examining the Relationship between Engagement in Physical Activity and Sex ................................ ............. 49 R esults of the Analyses to Address Research Questions 1 and 2 .......................... 50 Relationships between the Personal and Cognitive Variables and Race/Ethnicity and Sex ................................ ................................ ................. 50 Relationships between Engagement in Physical Activity and Race/Ethnicity ... 51 5 DISCUSSION ................................ ................................ ................................ ......... 55 Summary of the Results ................................ ................................ .......................... 55 Preliminary Analysis ................................ ................................ ......................... 55 Hypotheses One ................................ ................................ ............................... 57 Hypothe ses Two ................................ ................................ ............................... 60 Research Question One ................................ ................................ ................... 60 Research Question Two ................................ ................................ ................... 62 Lim itations and Strengths and Future Directions ................................ .................... 63 Implications for Counseling Psychologists ................................ .............................. 65 Conclusions ................................ ................................ ................................ ............ 66 APPENDIX A INFORMED CONSENT FORM ................................ ................................ ............... 68 B DEMOGRAPHIC DATA QUESTIONNAIRE ................................ ............................ 69 C HEALTH S ELF PRAISE QUESTIONNAIRE ................................ ........................... 71 D PHYSICAL FITNESS AND EXERCISE ACTIVITY OF OLDER ADULTS SCALE MOTIVATION SUBSCALE ................................ ................................ .................. 72
7 E COPING RES PONSES INVENTORY PROBLEM SOLVING AND POSITIVE REAPPRAISAL SUBSCALES ................................ ................................ ................ 73 F PERCEIVED HEALTH COMPETENCE SCALE ................................ ..................... 75 G HEALTH PROMOTI ON ACTIVITIES OF OLDER ADULTS MEASURE EXERCISE AND COLLABORATIVE HEALTH MANAGEMENT/INJURY PREVENTION SUBSCALES ................................ ................................ .................. 76 H SHORT FORM HEALTH SURVEY 12 ................................ ................................ 78 I MONTREAL COGNITIVE ASSESSMENT ................................ .............................. 81 REFERENCES ................................ ................................ ................................ .............. 85 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 98
8 LIST OF TABLES Table page 3 1 Demographic characteristics of participants ................................ ....................... 43 4 1 Means and standard deviations for the variables of study for the total sample and for each sex and race ................................ ................................ .................. 52 4 2 study for the total sample ................................ ................................ ................... 53 4 3 Unstandardized beta weights (B), standard error coefficients of beta weights, physical activity from a ll investigated predictor variables ................................ .... 54
9 Abstr act of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy PERSONAL AND COGNITIVE VARIABLES AS PREDICTORS OF ENGAGEMENT IN PHYSICAL AC TIVITY AMONG A CULTURALLY DIVERSE SAMPLE OF OLDER ADULTS By Sarah Elizabeth Madison Nolan August 2013 Chair: Carolyn M. Tucker Major: Counseling Psychology Given the significant relationship between engagement in physical activity and obesity reduction and health promotion among older adults, there is a need for research to gain a better understanding of variables under the direct control of older adults that influence their engagement in physical activity. Health self empowerment theory (HSET) asserts t hat the following five controllable, psychological variables impact engagement in health promoting behaviors: (a) health motivation, (b) health self praise, (c) adaptive coping, (d) health responsibility, and (e) health self efficacy. In this study, the fo llowing hypotheses were tested among older adults: (1) the HSET based variables will positively predict engagement in physical activity and (2) men will engage in significantly more physical activity than women. Additionally, the following two research que stions were investigated: (1) do the investigated HSET based variables differ in association with sex and/or race/ethnicity and (2) does level of engagement in physical activity differ in association with race/ethnicity? In all analyses the following varia bles were controlled for: mental health, physical health, and education level. Study participants consisted of 95 culturally diverse adults between the ages of 65 and 75.
10 To test the first hypothesis (i.e., the HSET based variables will positively predict engagement in physical activity), a hierarchical regression was conducted. The results provided partial support for the first hypothesis in that health responsibility and health self praise were the only significant independent predictors of engagement in physical activity. To test the second hypothesis (i.e., men will engage in significantly more physical activity than women), an analysis of covariance (ANCOVA) was conducted. The results did not support the second hypothesis in that level of engagement in physical activity did not vary significantly by sex. To test the research questions (i.e., do the HSET based variables differ in association with sex and/or race/ethnicity and does engagement in physical activity differ in association with race/ethnicity), six separate ANCOVAs were run. Results indicated that none of the five variables differed in association with sex or race/ethnicity and engagement in physical activity did not differ in association with race/ethnicity. Conclusions, limitations of the stud y, and implications for research and practice by counseling psychologists are discussed.
11 CHAPTER 1 INTRODUCTION Obesity and Related Diseases in the Aging Population In this paper, the term s refer to adults who are at l east 65 years old. The present study investigated the behaviors and characteristics of older adults who are between the ages of 65 and 75 years old and, as such, whenever possible in this paper, research presented will be specific to older adults in that a ge range. The aging population in the U.S. is expected to grow at a rapid pace over the next 20 years, and at a slightly less rapid pace thereafter. Using a projection of population growth based on the 2000 U.S. Census, researchers have estimated that th e population of aging adults will increase from 13% to 19% of the total population from 2010 to 2030. Additionally, the aging population is expected to become more culturally diverse, with the expected proportion of white individuals decreasing from 87% i n 2010 to 77% in 2050. Specifically, it is expected that there will be increases in the following racial/ethnic minority groups: Hispanics (7% to 20%), single race blacks (9% to 12%), Asians (3% to 9%), and multiracial groups (5.1% to 7.8%) (Vincent & Gra yson, 2010). Given this information, it is important to do research that aims to understand the challenges facing the aging population and that reflects awareness of the cultural diversity of this population. There is evidence that the population of aging adults is becoming increasingly overweight (Flegal, Carroll, Ogden, & Johnson, 2002). Among adults, being overweight is defined as having a body mass index (BMI) between 25 and 29.9, and being obese is defined as having a BMI of 30 or higher (Centers for Disease Control and Prevention
12 [CDC], 2010). In a study of U.S. adults in 1991, researchers found that 14.7% of individuals between the age of 60 and 69 and 11.4% of individuals over the age of 70 were obese (Mokdad et al., 1999). A similar study in 2000 found that these rates had increased to 22.9% and 15.5%, respectively (Mokdad et al., 2001). Further, other researchers found that in a national sample, men and women older than 60 had a median BMI of 27.6 and 28.3, respectively (Flegal, Carroll, Ogden, & Curtin, 2010 ). The prevalence of diseases related to overweight and obesity is also high among older adults. There is evidence that 24% of women between the ages of 65 and 74 have high cholesterol levels (National Center for Health Statistics, 2010). Further, among adults over the age of 55, one in four has been diagnosed with heart disease and d iabetes has a prevalence rate of 17% among adults between the ages of 65 and 74 (Schoenborn, Vickerie, & Powell Griner, 2006). Obesity and obesity related di seases are not only dangerous in themselves, but they her/his physical and mental health (Lopez Garcia et al., 2003; Sachs Ericsson et al., 2007; Daviglus et al., 2003; Yan et al., 2004) Specifically, r esearch has shown that BMI is associated with physical well being, physical functioning, depression and quality of life among older adults In Healthy People 2010, the U.S. Department of Health set as a primary goal to improv e the quality of life of the aging population (U.S. Department of Health and Human Services, 2000). Additionally, Rowe and Kahn (1997) proposed a model of successful aging comprised of three components: avoidance of disability, maintenance of physical fun ctioning, and active engagement with life. Given the
13 national focus on improving quality of life among the aging population, it is important to understand and increase behaviors among aging adults that achieve this goal. Sex and Race/Ethnicity Differences in Obesity and Related Diseases Among older adults, there is evidence of group differences (i.e., sex and/or race/ethnicity differences) in the prevalence of overweight and obesity. Results from the 2003 2004 National Health and Nutrition Examination Surveys (NHANES; Wang & Beydoun, 2007) indicate that among male and female individuals over the age of 60, 71.1% of non Hispanic whites were overweight, while 78.8% of non Hispanic blacks were overweight. Further, 29.7% of non Hispanic whites compared to 44.9% of non Hispanic blacks were found to be obese. In looking at rates of extreme obesity (i.e., BMI > 40) in this sample, the rate was 2.8% for non Hispanic whites and 6.6% for non Hispanic blacks. These percentages are consistent with research that de monstrates that African American older adults tend to have higher BMIs and rates of overweight and obesity than Whites (Glass, Rasmussen, & Schwartz, 2006). The research on sex differences in prevalence of overweight and obesity among older adults has pr oduced mixed results. Some researchers have found that there are no significant differences in prevalence of obesity and overweight between older men and women (Riebe et al., 2009), while others have found that older women are more likely to be obese and have higher BMIs than older men (Wang, Colditz, & Kuntz, 2007; Swartz, Strath, Parker, Miller, & Cieslik, 2007; Glass et al., 2006). Other researchers have demonstrated that there are differences in BMI levels in association with the interaction of sex an d race/ethnicity among older adults. Specifically, African American women report higher BMIs than African American men, White men, and White women (Sachs Ericsson et al., 2007). Similarly, other
14 researchers found that while older Black women reported hig her BMIs than older White women, there were no significant differences in BMI in association with race/ethnicity among older men (Walsemann & Ailshire, 2011). These results are supported by the 2006 NHANES (CDC, 2009), which found that among adults over t he age of 60, obesity was significantly more prevalent for African American/black women than for non Hispanic white women. Results of this survey also indicate that there are no significant differences in BMI level in association with race/ethnicity among men over the age of 60. Physical Activity and Obesity in the Aging Population One of the most direct ways of promoting successful aging is reversing and preventing obesity and promoting overall health through engaging in various health promoting behaviors (de Silva Sanigorski et al., 2010). Health promoting behaviors are behaviors include engaging in physical activity, healthy eating, stress management, and health responsibility behaviors. In this paper such behaviors are also called health smart behaviors (HSBs) a term set forth by C. Tucker (Tucker, Daly, & Herman, 2009). The HSB that was targeted in this study is engagement in physical activity. The reason fo r studying this particular HSB in the present study is that engagement in physical activity has been clearly linked to improved health outcomes among older adults, including the reduction and prevention of certain diseases, improvement in mobility, reducti on in pain, and improved mental health (McCartney, Hicks, Martin, & Webber, 1995; Haskell, Blair, & Hill, 2009; National Center for Chronic Disease Prevention and Health Promotion, 2011).
15 There is evidence of links between engagement in physical activity and health outcomes among aging adults. For example, a decrease in engagement in physical activity behaviors (i.e., general physical activity, strength training, walking for transportation, walking for leisure, and reduced television screen time/sitting t ime) has been found to be associated with increased rates of overweight, obesity, and related diseases among this population (Riebe et al., 2009; Kaplan, Huguet, Newsom, McFarland, & Lindsay, 2003; Kruger, Ham, & Prohaska, 2009; Jenkins & Fultz, 2008; Chas tin, Ferriolli, Stephens, Fearon, & Greig, 2011; Gardiner et al., 2011). It is noteworthy that older men who are physically inactive have been found to be 39% more likely to be obese than older men who are physically active, and older women who are physic ally inactive have been found to be 28% more likely to be obese than older women who are physically active. It is clear that efforts aimed at preventing or reducing obesity among the aging population should target the HSB of engagement in physical activit y. Given the significant relationship between engagement in physical activity and obesity reduction among older adults, there is a need for research to gain a better understanding of the variables under the direct control of older adults, such as personal and cognitive variables, that may influence level of engagement in physical activity among older adults. Consequently, the goal of this study was to use h ealth s elf e mpowerment t heory (HSET; Tucker, Butler, Loyuk, Desmond, & Surrency, 2009) to examine the relationship s between personal and cognitive variables and engagement in physical activity among a culturally diverse sample of older adults. Additionally, this
16 study examine d whether there are differences in personal and cognitive variables, and levels o f engagement in physical activity in association with sex and /or race/ethnicity. Theoretical Framework Researchers have come up with a number of theories that aim to explain the relationship s between both personal and cognitive variables and engagement in health promoting behaviors (Jackson & Aiken, 2000; Ajzen & Madden, 1986 ; Ajzen & Fishbein, 19 8 0; Rosenstock, Strecher, & Becker, 1988; Maddux & Rogers, 1983). Using such theories, researchers have found consistent support for certain health indicators. For example, researchers have found that health self efficacy is a strong pred ictor of engagement in health promoting behaviors (Schm i e ge, Aiken, Sander, & Gerend, 2007; Grembowski et al. 1993 ), that perceived barriers and benefits to health promoting beh aviors (i.e., health smart behaviors; HSBs) are strong predict ors of engagement in these behaviors (Purnell, Katz, Andersen, & Bennett 2010; Hill & Gick, 2011), and that perceived severity of the health risk from not engaging in a particular health promot ing behavior is an important predictor of engagement in that behavior (Calder & Aitken, 2008). One theory of health behavior is h ealth s elf e mpowerment t heory (HSET; Tucker et al. 2009), which is based in part on s ocial c ognitive t heory (SCT; Bandura, 19 91). When applied to health behaviors, SCT posits that engagement in health promoting behaviors is a result of social and environmental influences on health, as well as personal and cognitive control over health. HSET posits that many individuals, partic ularly minorities, have little power or control over social and environmental influences on health (e.g., access to knowledge about health and health behaviors, financial means to afford healthier foods, access to safe environments in which to
17 exercise) As such, this theory acknowledges social and environmental influences on health but asserts that efforts to influence HSBs must target/emphasize five modifiable personal and cognitive variables over which an individual has or can learn to control. Researc h has supported the use of this model with low income and racial/ethnic minority adults (Tucker et al. 2009; Grandoit, 2010 ; Tucker et al. 2011 ); however more research is needed to support the use of this model with other populations who are (a) in posit ions of reduced power and/or control over the social and environmental influences on their health and (b) at a disproportionate ly high risk for diseases and disorders that often impede or prevent engagement in HSBs (e.g., engagement in physical activity) Older adults tend to have less control over their environments (Heckhausen, 1999; Levasseur, St Cyr Tribble, Desrosiers, 2009), as well as an increased number of normative uncontrollable events (e.g., death of a spouse, physical illness ) (Schaie & Willis, 2002). Thus, g iven the evidenced decrease in control that comes with aging, as well as the aforementioned high proportion of older adults who suffer from obesity and its related diseases, older adults are an appropriate population with whom to test HSET. The five personal and cognitive variables emphasized in HSET are (1) motivation to engage in health promoting behaviors, (2) self praise of health promoting behaviors, (3) adaptive coping styles to manage emotions that often negatively impact health, (4 ) health responsibility that includes health knowledge, and (5) health self efficacy. In applying HSET to research on engagement in physical activity among older adults, it is important to consider the personal and cognitive variables that have been shown to be associated with engagement in physical activity among aging adults. Research with the
18 aging population has shown that health self efficacy and perceived benefits of preventative health behaviors are significantly associated with engagement in physi cal activity ( Ayotte, Margrett, & Hicks Patrick, 2010; Kwong & Kwan, 2007; Arras, Ogletree, & Welsheimer, 2006). Other personal and cognitive variables that have been found to be associated with protective health behaviors among this population include pe rceived susceptibility to the disease and level of health related self motivation ( Galvin Fu, Nguyen, Glasheen, & Scharff 2008 ; Loeb, 2004). In the present study, the measures used to assess each construct of HSET (i.e., each of the five personal and co gnitive variables) reflect the findings from literature on older adults. Present Study In the present study, HSET was used to guide the investigation of variables that influence engagement in physical activity among older adults between the ages of 65 and 75 Specifically, the variables constituting HSET (i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy) were examined as predictors of engagement in physical activity among older adults. In all an alyses, the following variables were controlled for: mental health, physical health, and education level. This study investigate d the following hypothes e s among a sample of older adults between the ages of 65 and 75 : 1. The health self empowerment theory (HSE T) based personal and cognitive variables (i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy) will positively predict engagement in physical activity. 2. Men will engage in significantly more physica l activity than women.
19 Additionally, this study will investigate the following research questions among the same sample: 1. Do the investigated HSET based personal and cognitive variables differ in association with sex and/or race/ethnicity? 2. Does level of eng agement in physical activity differ in association with race/ethnicity?
20 CHAPTER 2 REVIEW OF THE LITERATURE This chapter includes a description of the health smart behavior (HSB) of interest (i.e., physical activity) and an overview of the aging adult lite rature on the personal and cognitive variables that constitute health self empowerment theory (HSET). Additionally, there is a discussion of the associations of these theory based personal and cognitive variables with engagement in physical activity. Lit erature on sex and race/ethnicity differences in these personal and cognitive variables and in engagement in physical activity is also presented. Finally, certain factors (i.e., education level, physical health status, and mental health status) that may in fluence the relationships between the HSET based personal and cognitive variables and level of engagement in physical activity are presented and discussed. Engagement in Physical Activity In this study, the health smart behavior (HSB) variable that was inv estigated was engagement in physical activity. Within the health promotion literature, this behavior is commonly investigated due to evidence that engagement in physical activity is linked to the prevention and reduction of obesity and obesity related dis eases. In this paper, engagement in physical activity is defined according to the definition set forth in the commonly used Health Promoting Lifestyle Profile (Walker, Sechrist, & Pender, 1987). Thus, engagement in physical activity refers to regular part icipation in light, moderate, and/or vigorous activity, and can occur in a specific exercise regime, or as part of daily leisure activities (Walker & Hill Polerecky, 1996). In this study the assessment used to measure this variable was the Health Promotion Padula, 1997 ). This measure
21 assesses engagement in physical activity behaviors that are common among older adults. Research indicates that approximately 30 percent of older adults between the ages of 65 and 74 engage in regular leisure time physical activity (USDHHS, 2007). Personal and Cognitive Variables of Health Self Empowerment Theory Health self empowerment theory (HSET) acknowledges social and environmental influences on health smart behaviors (HSBs; e.g., engagement in physical activity), such as access to safe environments to exercise and time to engage in exercise; however, this theory asserts that efforts to influence HSBs must target/emphasize five modifiable and self empowerment oriented p ersonal and cognitive variables over which an individual has or can learn to control. The five personal and cognitive variables emphasized in HSET are (1) health motivation, (2) self praise of health promoting behaviors, (3) adaptive coping styles to mana ge emotions that often negatively impact health, (4) health responsibility that includes health knowledge, and (5) health self efficacy. of purpose that fosters engaging in one or more behaviors. Researchers have posited event contingencies that are relevant to her/his personal values and goals, and that this motivation can change over the c ourse of the lifetime due to changes in these personal values and goals (Heckhausen & Shulz, 1995). Further, as individuals age into older adulthood, these personal values and goals tend to become more health related (Cross & Markus, 1991; Heckhausen, 199 7). The construct of health motivation has been identified as motivation for engaging in health promoting behaviors among aging adults and has been assessed using
22 measures of perceived susceptibility to diseases related to lack of engagement in health pr omoting behaviors and perceived benefits of engagement in health promoting behaviors (Davis et al., 1995; Finch, 1997). Literature on health motivation indicates in a particular health promoting behavior (Jimenez Beatty Navarro, Graupera Sanz, del Castillo, Izquierdo, & Rodriguez, 2007; Caragata, Tuokko, & Damini, 2009). Self praise of health promoting behaviors (i.e., health self praise) is a construct designed to a ssess the degree to which an individual engages in verbal or non verbal messages of affirmation created by and for the self when he/she engages in a particular health promoting behavior. Researchers assessing levels of health self praise have done so by m easuring the frequency with which individuals use helpful self talk following a positive health behavior (Gilchrist, Schinke, Bobo, & Snow, 1986; Tucker et al., 2009). The concept of self praise of health promoting behaviors is based on evidence that this construct has been shown to have a positive significant relationship & Hegney, 2009; Shawler & Logsdon, 2008; Hamilton, Scott, & MacDougall, 2007; Epton & Harris, 2008 ). The construct of adaptive coping is defined as coping in a way that is effective and positive for an individual. In the proposed study, adaptive coping will be defined as engagement in problem solving and positive reappraisal coping responses. Problem characterized by intentional problem focused efforts to alter the situation, as well as an analytic approach to solving the problem. Positive reappraisal coping involve s cognitive
23 approach coping strategies, such as creating a positive meaning from a stressful experience by re construing the experience as harmless or valuable (Lazarus & Folkman, 1984). These two types of coping are consistent with responses that have be en shown to be adaptive coping responses for older adults. In a study of adults older than 55, researchers found that for a variety of stressful life events (i.e., health related, interpersonal, and financial/work), positive reappraisal and problem solvi ng coping responses were significantly associated with positive consequences. Additionally, it was found that individuals who relied on cognitive avoidance and emotional discharge coping were found to have higher rates of depression and late life drinking problems (Moos, Brennan, Schutte, & Moos, 2006). Similarly, Folkman, Lazarus, Pimley, & Novacek (1987) found that in all types of home maintenance, and household respon sibilities), older adults used significantly more positive reappraisal coping responses than younger adults; and in health related solving coping responses than younger adults. The construct of health personal responsibility for their own health, in terms of the level at which they are involved in their own health care and health practice. This construct includes an wledge. Health responsibility is most often used as an outcome measure that assesses a domain of engagement in health promoting behaviors (Padula & Sullivan, 2006; Worthington & Myers, 2003), where health
24 responsibility is a health promoting behavior. In the proposed study, however, health responsibility is examined as a cognitive predictor of engagement in physical activity. Self her/his own functioning and other events that impact their lives (Bandura, 1997). Health self her/his level of engagement in health promoting behaviors and their health outcomes. Literature on health self efficacy i ndicates that, among older adults, perceived health self efficacy has a significant positive relationship with a number of health promoting behaviors (Morowatisharifabad, Ghofranipour, Heidarnia, Ruchi, & Ehrampoush, 2006; Orshan, & Cook, 2000; Wiesmann & Hannich, 2011). Personal and Cognitive Variables and Engagement in Physical Activity According to HSET, the aforementioned personal and cognitive variables may smart behaviors (HSBs) and, specifically, physical activity. In the following section, research will be presented that has examined the relationships between each of these personal and cognitive variables and engagement in physical activity among older adults. Researche rs have found that, among older adults, the identified barriers to engaging in physical activity include personal and cognitive factors (e.g., beliefs, fears, perceived capabilities, social support; Lees, Clark, Nigg, & Newman, 2005). Additionally, over t ime, the negative impact of personal and cognitive variables on level of engagement in physical activity may lead to overweight/obesity. Therefore, it is important to understand the specific relationships between these variables and engagement in physical activity among older adults.
25 Health Motivation and Engagement in Physical Activity Health behavior research indicates that, among older adults, a perceived barrier to engagement in physical activity is lack of motivation to engage in a health behavior (Br awley, Rejeski, & King, 2003; Lees et al., 2005 ; Haq & Griffin, 1996 ). Similarly, the presence of health motivation has been found to be associated with engagement in physical activity among older adults (Cousins, 2000; Jimenez Beatty Navarro et al., 2007 ; Lucas et al., 2000 ). Among older adults research suggests that an perception of what it means to engage in physical activity (e.g., perceptions of the risks and benefits of engaging in physical activity) is highly related to her/his level of motivation to engage in this behavior Further these perceptions have been found to be important motivational factors for engagement in physical activity as adults age and begin to assess the impact of certain behaviors on their quality of life (Cousi ns, 200 0 ). In a study of older adults who were suffering from arthritis, researchers found that while symptoms of arthritis were initially seen as barriers to engagement in physical activity, once individuals became aware of the fact that engagement in ph ysical activity could alleviate the same negative symptoms, the perception of the benefits of physical activity became a motivator for these individuals (Wilcox et al., 2006). The found relationship between perceived benefits of physical activity and enga gement in physical activity has also been reported by other researchers (King, 2001 ; Williams, Anderson, & Wi nnett, 2005). R esearchers have also found that older adults identify health concerns as an important motivator to engaging in various health smar t behaviors (HSBs; e.g., healthy eating and physical activity) In a qualitative study, Buman, Yasova, & Giacobbi (2010) found that the prevention of certain diseases related to overweight and obesity
26 was a significant motivator for engaging in physical a ctivity. Similarly, in a focus group study, Greaney, Lees, Greene, & Clark (2004) found that, among older adults, fear of illness, desire to remain independent, and desire for health maintenance were motivators for engagement in physical activity. Health Self Praise and Engagement in Physical Activity There is limited research investigating the relationship between health self praise and engagement in physical activity. Tucker et al. (2009) found that among low income African American and White mothers of chronically ill children, when health self praise was coupled with health self efficacy, active coping, and health motivation, these personal and cognitive variables accounted for 67% of the variance in engagement in a healthy lifestyle (i.e., physical ac tivity and healthy eating). Thus, there is evidence that health self praise may be predictive of engagement in physical activity. Adaptive Coping and Engagement in Physical Activity For the purposes of this study, adaptive coping is considered to be proble m solving coping and positive reappraisal coping responses. Generally, research on the relationship between coping and engagement in physical activity among older adults is sparse, particularly research investigating specific adaptive coping responses. I n a study of adults over the age of 55, researchers found that individuals who perceived themselves as having coping skills engaged in more physical activity (Bergland, Thorsen, & Loland, 2010). These findings give support for the notion that coping respon ses may be associated with increased engagement in physical activity. Health Responsibility and Engagement in Physical Activity The construct of health responsibility is typically used as a health outcome measure and so there is no found evidence of it bei ng predictive of engagement in
27 physical activity among older adults However, there is some evidence that health responsibility is significantly associated with engagement in physical activity (Beverly & Wray, 2008) among older adults and, further, that older adults report engaging in health responsibility behaviors significantly more than younger adults (Becker & Arnold, 2004; Walker, Volkan, Sechrist, & Pender, 1988) A study of adults over the age of 55 found that while 95.2% of participants knew tha t exercising for 20 minutes or more three times a week was important, 39.3% of them did not practice this. Additionally, 96% of participants believed that moderate exercise is an important part of a healthy lifestyle, but 40% of them did not practice this (Coulson, Strang, Marino, & Minichiello, 2004). These researchers posit that the aforementioned results are indicative of the fact that health knowledge is not a sufficient motivator of engagement health promoting behaviors and that older adults must be taught about how to be responsible for their health in a way that enables them to use their health knowledge. Further, researchers investigating the effectiveness of an intervention program that included educational components related to increasing heal th responsibility found that, among a sample of Korean adults over the age of 55, there were significant improvements in physical activity (Song, June, Kim, & Jeon, 2004). These results suggest that improvements in health responsibility may lead to increa sed engagement in physical activity Health Self Efficacy and Engagement in Physical Activity Researchers have consistently found that increased levels of health self efficacy are associated with increased levels of engagement in physical activity among ol der adults (Elavsky et al., 2005; Kirk, MacMillan, & Webster, 2010; Rimal, 2001). The
28 relationship between health self efficacy and engagement in physical activity has been found to be significant for both the adoption and maintenance of physical activity behaviors among older adults (McAuley & Blissmer, 2000; McAuley et al., 2007). Further, when health self efficacy was measured before and after a health behavior intervention program, it was found to be predictive of engagement in physical activity (Klug Toobert, & Fogerty, 2008). Finally, research indicates that health self efficacy is associated with long term weight loss among this population (Batsis et al., 2009; Warziski, Sereika, Styn, Music, & Burke, 2008; Richman, Loughnan, Droulers, Steinbeck, & Caterson, 2001 ), making it a highly relevant variable to consider in doing research aimed at increasing engagement in health smart behaviors (HSBs; e.g., engagement in physical activity) and decreasing risk of disease among older adults. Associations bet ween Demographic Variables and Variables of this Study In exploring the relationships between personal and cognitive variables and engagement in physical activity, it is important to consider other variables that may be associated with these relationships Specifically, the demographic variables sex and race/ethnicity have been found to be associated with differences in rates of obesity and obesity related diseases. As such, it is important to investigate whether there are sex and/or race/ethnicity diffe rences in engagement in physical activity and personal and cognitive variables. Gaining insight into these relationships may allow researchers to better understand how to address health issues differently for different groups of older adults.
29 Sex and Pers onal and Cognitive Variables Research investigating associations between sex and the identified personal and cognitive variables of older adults suggests that there may be sex differences in certain variables (i.e., health responsibility, health self effic acy, and health motivation) among this population. Specifically, some researchers investigating health responsibility and engagement in physical activity have found that older women tend to engage in higher levels of health responsibility than older men ( Ammouri, Neuberger, Nashwan, & Al Ha j, 2007 ; Chen, Wu, Hwang, & Li, 2010 ). Alternatively, in a qualitative study of a racially diverse sample of older adults from a rural community, researchers found that participants engaged in four major domains of heal th maintenance, including a domain of personal responsibility for health (Arcury, Quandt, & Bell, 2001). These researchers found no sex differences in the engagement in the domain of personal responsibility for health, which suggests that the shared cultu re of the rural community in which the participants lived may have been more salient than potential sex differences. The literature investigating sex differences in health self efficacy among older adults is mixed. While some researchers have failed to f ind sex differences in health self efficacy among this population ( Chen, Acton, & Shao, 2010; Carroll, 1995; Gremb owski et al., 1993; King et al., 2000), other researchers have found results suggesting that men report higher levels of health self efficacy related to engagement in health promoting behaviors than women (Morowatisharifabad et al., 2006). Researchers investigating sex differences in specific types of health self efficacy have found that older women report higher levels of nutrition based healt h self efficacy (Callaghan, 2005), while older men report higher levels of exercise based health self efficacy (Jenkins & Gortner, 1998; Clark & Nothwehr, 1999).
30 Research investigating sex differences in health motivation among older adults is sparse. In a qualitative study of health motivation for engagement in physical activity among Asian Indian older adults, researchers found that men reported benefits and medical reasons as motivators significantly more often than women (Kalavar, Kolt, Giles, & Drive r, 2004). Alternatively, Dacey, Baltzell, Zaichkowsky (2008) found that health benefits was a motivator for both men and women, with no significant differences between the two groups. The research investigating sex differences in the use of problem solvi ng coping and positive reappraisal coping among older adults is also very limited. However, Folkman and Lazarus (1980) assert that men can typically be expected to use problem solving coping responses more often than women. There is no found published re search that has investigated differences in the use of health self praise in association with sex among older adults. Sex and Engagement in Physical Activity Research investigating sex differences in engagement in physical activity among older adults has revealed that older men tend to participate in significantly more physical activity than older women (Chad et al., 2005; Smith & Baltes, 1998; Newsom, Kaplan, Huguet, & McFarland, 2004; Ammouri et al., 2007). Race/Ethnicity and P ersonal and Cognitive Varia bles Research investigating the relationship between the identified personal and cognitive variables and race/ethnicity is limited, but the research that does exist has demonstrated that there may be race/ethnicity differences in some of these variables am ong older adults. In research investigating health self efficacy among older adults, results indicate that there are significant race/ethnicity differences. Specifically,
31 Callaghan (2005) found that White older adults reported higher levels of health self efficacy, followed by Black older adults, and Hispanic older adults. This author was unable to find any published research investigating racial/ethnic differences in levels of health responsibility or health self praise. The research literature on race /ethnicity differences in coping among older adults is also scarce. In a study of Caucasian and African American adults over the age of 60, researchers found that coping as a response to a threat (i.e., the threat of living in a vegetative state after a m otor vehicle accident and the threat of vulnerability to being in such an accident) was handled with problem solving coping significantly more by Caucasian older adults than by African American older adults (Allen, Phillips, Pekmezi, Crowther, & Prentice D unn, 2009). Other researchers found that, among women over the age of 55, there was no significant difference in the use of positive reappraisal coping between White adults and African American adults (McIlvane, 2007). Research investigating racial/ethni c differences in the construct of health motivation has been scarce. Allen et al. (2009) found no significant differences between African American adults and White adults over the age of 55 with regard to the motivational level of perceived susceptibility to a health threat. Race/Ethnicity and Engagement in Physical Activity While level of engagement in certain health smart behaviors (HSBs; i.e., engagement in healthy eating) has found to differ significantly by race/ethnicity among older adults, research investigating race/ethnicity differences in level of engagement in physical activity has been scarce. In a large sample of non Hispanic white, African American/black, Asian/Pacific Islander, and Latino older adults, researchers investigated racial/ethnic differences in healthy dietary and exercise behaviors (August
32 & Sorkin, 2011). Results indicated that the only differences in engagement in physical activity were that limited English proficient Asian/Pacific Islanders were significantly more likely to en gage in moderate physical activity and significantly less likely to engage in vigorous physical activity than whites. Other Variables that May Impact Study Variables There is evidence that a number of personal variables may impact the relationships among t he study variables. In order to control for these potential impacts, certain variables are also included in this study, including education level, mental well being, and physical well being. Impact of Education Level level of engagement in physical activity may be impacted by an her/his socioeconomic status (SES), specifically impacting an literacy) and (b) access to resources to fa cilitate physical activity (Goldman, Turra, Rosero Bixby, Weir, & Crimmins, 2011; Mottus, Johnson, Murray, Wolf, Starr, & Deary, 2013; King, 2001). Research investigating engagement in physical activity among older s education level may be the best indicator of SES as compared with income level or occupation due to the fact that education is the indicator that is least likely to be impacted by changes that occur in later life (Goldman et al., 2011). Thus, in the pres ent study, education level was controlled for in all analyses. Impact of Physical and Mental Health In research aimed at understanding the personal and cognitive variables that predict engagement in physical activity, it is important to control for other v ariables that
33 mental and physical health. Specifically, among older adults, decreases in mental and physical health have been shown to be associated with decreases in p erceived quality of life, engagement in physical activity, and increases in poor health outcomes (Penedo & Dahn, 2005). In the present study, the Short Form Health Survery 12 (Domel, Baranowski, Davis, Leonard, Riley, & Baranowski, 1993) was used to asses s and control for mental and physical health on eight scales (i.e., physical functioning, role limitations as a result of physical health problems, bodily pain, general health, vitality [energy/fatigue], social functioning, role limitations as a result of emotional problems, and mental health [psychological distress and psychological well being]).
34 CHAPTER 3 METHODS Participants One hundred and two participants were recruited for this study and completed the assessment battery (AB). However, only 95 partici pants had scores on the Montreal Cognitive Assessment screening tool that were sufficient for them to be included in this study (i.e., scores of at least 23); thus, only the data for these 95 participants were included in this study Study participants wer e 63 (66.3%) females and 32 (33.7%) males ranging in age from 65 to 75 years old ( M = 69.56; SD = 3.01). Of these participants, 79 (83.2%) identified as non Hispanic White/Caucasian, and 16 (16.8%) identified as African American/Black. Eight (8.4%) partici pants reported that they work full time, while 20 (21.1%) participants reported working part time, and 67 (70.5%) participants reported highest level of education, 1 ( 1.1%) participant reported less than high school, while 10 (10.5%) reported graduating from high school, 22 (23.2%) reported completing some post high school education, and 62 (65.3%) reported completing a post high school degree. Self reported annual hou sehold income levels of participants were also collected. Five (5.3%) participants reported an income of less than $25,000, 24 (25.3%) participants reported an income ranging between $25,000 and $49,999, 23 (24.2%) participants reported an income ranging b etween $50,000 and $74,999, and 35 (36.8%) participants reported an income of $75,000 or more. Demographic information for the total sample is presented in Table 3 1.
35 Measures All participants in this study anonymously completed an Assessment Battery (AB) that included the following instruments: (1) a Demographic Data Questionnaire (DDQ), (2) the researcher constructed Health Self Praise Questionnaire (HSPQ) (3) the Motivation subscale of the Physical Fitness and Exercise Activity of Older Adults Scale (PF EAOAS; Melillo, Williamson, Futrell, & Chamberlain, 1997), (4) the Problem Solving and Positive Reappraisal subscales of the Coping Responses Inventory (CRI; Moos, Brennan, Schutte, & Moos, 2006), (5) the Perceived Health Competence Scale (PHCS; Smith, Wal lston, & Smith, 1995), (6) the Exercise and Collaborative Health Management/Injury Prevention subscales of the Health Promotion Activities of Older Adults Measure (HPAOAM; Padula, 1997), and (7) the Short Form Health Survey 12 (SF 12; Domel, Baranowski, Da vis, Leonard, Riley, & Baranowski, 1993). Additionally, each participant engaged in a cognitive interview with a trained researcher, using the Montreal Cognitive Assessment (MoCA; Nasreddine et al., 2005). Detailed descriptions of these instruments are pro vided below and each instrument may be found in Appendices B through I. Demographic Data Questionnaire The Demographic Data Questionnaire (DDQ; see Appendix B) is a researcher constructed instrument used to collect demographic information, including age, s ex income level, education level, race/ethnicity, marital status and current living situation Health Self Praise Questionnaire The Health Self Praise Questionnaire (HSPQ; see Appendix C ) is a researcher constructed instrument designed to assess the exte nt to which an individual engages in self praise of specific health smart behaviors (HSBs) related to engaging in physical
36 activity. The instructions on the HSPQ are to indicate how often an individual praises her/himself for each of the behaviors listed b elow using a Likert type scale ranging from yourself, think positively about yourself, or feel good about yourself when you exercise (e.g., like walking, swimming, or ri mean of all of the items in the scale. Higher scores indicate higher levels of engagement in self praise of HSBs. Physical Fitness and Exercise Activity of Older Adults Scale The Physical Fitness and E xercise Activity of Older Adults Scale (PFEAOAS; Melillo, Williamson, Futrell, & Chamberlain, 1997; see Appendix D) is a 41 item measure designed to assess the self perceived fitness and exercise activity levels of older adults, as well as perceived factor s that enhance or inhibit their exercise levels. For the present study only the 11 item Motivation subscale will be used to assess the level of motivation to engage in physical activity for each participant. Instructions on the PFEAOAS are to indicate the degree to which an individual agrees with each statement using a Likert type scale, ranging from 1 ( strongly disagree ) to 4 ( strongly agree ) A Subscal e scores are calculated for the PFEAOAS by summing the items of each respective subscale. Higher scores on the Motivation subscale indicate higher levels of motivation to engage in physical activity. Melillo et al. (1997) found that in a sample of 61 commu nity dwelling adults (mean age = 68.5), the Motivation subscale had test retest reliability of .585, internal consistency of .88, and significant predictive validity of exercise frequency (Spearman Rank Order Correlation Coefficient = .224, p = .028).
37 Copi ng Responses Inventory The Coping Responses Inventory (CRI; Moos, Brennan, Schutte, & Moos, 2006; item subscales, however only the two subscales that assess cognitive and behavioral app roach coping (i.e., Problem Solving and Positive Reappraisal) are used in the present study. These two subscales were used because they represent the types of coping that have been found in the literature to be the most adaptive for the population being st udied presently. Instructions on the CRI are to think about the most important problem or stressful situation that the individual has faced in the last 12 months, and to select the response that best represents how often the individual has engaged in each listed behavior in connection with the named problem or stressful situation. A 4 point behavior frequency rating scale ranging from 1 ( not at all ) to 4 ( fairly often ) is provided. A sample item from the Problem u wanted Subscale scores are calculated for this instrument by obtaining the sum of scores for each coping subscale. Among a sample of 297 older adults, Moos et al. (2006) found that for the Problem Solving and Positive Reappraisal subscale scores were 0.66 and 0.74, respectively. Perceived Health Competence Scale The Perceived Health Competence Scale (PHCS; Smith, Wallston, & Smith, 1995 ; see Appendix F) is an 8 item scale designed to assess health self efficacy, which is the degree to which an individual believes he/she is capable of effectively influencing her/his health outco mes. Individuals are instructed to indicate their level of agreement
38 with each statement using a Likert type scale, ranging from 1 ( disagree very much ) to 5 ( agree very much health as well as samples (Smith et al.), as well as with older adult populations (Cronbach alpha = 0.84; Marks & Lutgendorf, 1999). Health Promotion Activities of Older Adults Measure The Health Promo tion Activities of Older Adults Measure (HPAOAM; Padula, 1997; see Appendix G) is a 44 item instrument specifically designed to assess frequency of engagement in health promoting behaviors among older adults. The HPAOAM is made up of five subscales that pe rtain to health, but only two will be used in the current study: Exercise (5 items) and Collaborative Health Management/Injury Prevention (15 items). The latter subscale will serve as a measure of health responsibility in this study. Instructions for th is instrument are to report how often an individual engages in each behavior on a 4 point behavior frequency rating scale ranging from 1 (never) to 4 20 min on a regula questions under each subscale. Higher s cores indicate more positive health practices. Reliability for the subscales that will be used in this study has been demonstrated in Padula, 1997).
39 Short Form Health Su rvey 12 The Short Form Health Survey (SF 12; Ware, Kosinski, & Keller, 1996; see Appendix H) is a shortened version of the well researched and validated SF 36 (Ware et al., 1994), a 36 item instrument that assesses physical and mental functioning on eight subscales (i.e., physical functioning, role limitations as a result of physical health problems, bodily pain, general health, vitality [energy/fatigue], social functioning, role limitations as a result of emotional problems, and mental health [psychologica l distress and psychological well being]). The SF 12 is comprised of two subscales: Mental Component Summary and Physical Component Summary. The SF 12 has achieved multiple R squares of 0.911 and 0.918 in predicting the Physical and Mental Component Summar y scores of the SF 36 (Ware et al., 1996 ). A sample set of items on the Mental Component Summary subscale asks individuals to respond to questions regarding how they have felt over the previous four weeks on a 5 point Likert type scale ranging from 1 ( all of the time ) to 5 ( none of the time sample set of items on the Physical Component Summary subscale asks individuals to respond to questions regarding how much of the time they ha ve had problems with work or other daily activities as a result of their physical health on a 5 point Likert type scale ranging from 1 ( all of the time ) to 5 ( none of the time ). A sample question on this section asks how much of the time an individual felt that due to physical health problems they Internal consistency with an older adult sample for the SF 12 subscales has been shown to be .80 (physical health component) and .73 (mental health component) (Peel, Bartl ett, & Marshall, 2007) Internal consistency for this scale as a whole has also been
40 found among older adults (.82, .86; Taylor Piliae et al., 2010). Test retest reliability has also been high (.86 .89; Ware, Kosinski, & Keller, 1996). Strong construct v alidity has also been established by finding significant correlations between the physical component score and physical health and chronic illness, and between the mental component score and mental health and chronic illness (Resnick & Nahm, 2001). Montrea l Cognitive Assessment The Montreal Cognitive Assessment ( (MoCA; Nasreddine et al., 2005 ; see Appendix I) is a 30 point, 10 minute, 1 page cognitive screening tool that assesses mild cognitive impairment. This instrument assesses eight cognitive domains, i ncluding short term memory, visuospatial abilities, attention, concentration, working memory, language, orientation to time and place, and executive functioning. In a sample of 94 older adults, Nasreddine et al. (2005) found a Cronbach high test retest reliability (correlation coefficient of 0.92), as well as a high correlation (0.87) with scores on the M ini Mental S tatus E xamination (MMSE; a well validated and researched cognitive screening tool). The MoCA has been demonstrated to have optimal sensitivity and specificity to identifying mild cognitive impairment (96% and 95%, respectively) with a cut off score of 23 (Luis, Keegan, & Mullan, 2009; Lee et al., 2008). Therefore, in the present study, participants with a MoCA score less than 23 were excluded. Procedure Following approval of the present study by the University of Florida (UF) Institutional Review Board (IRB), culturally diverse adults between the ages of 65 and 75 years old were recruited to be participants. The participation c riteria for the present study are as follows: (a) being between the ages of 65 and 75 and (b) being able to read and speak English.
41 All participants completed an Informed Consent Form (ICF; see Appendix A) that outlines the following: (a) the purpose of the study, (b) what participation would involve, (c) the required time commitment for completing the assessment battery and the brief cognitive screening interview, (d) any possible risks and benefits to being a participant in the study, (e) the participat ion incentive which included an invitation to a free workshop on exercise and aging and a free booklet on exercising and aging, and (f) procedures to protect the confidentiality of all provided information. The ICF also stated that study participation is voluntary and that participants have the right to withdraw at any point during the study, without penalty. The present study involved two procedural phases: (a) the participant recruitment phase and (b) the research enrollment and data collection phase. Both of these procedural phases were implemented by trained graduate and undergraduate research assistants. These research assistants were trained in the following: (a) the purpose and protocol for the proposed study, (b) culturally sensitive strategies fo r recruiting culturally diverse older adults (e.g., spending as much time explaining the purpose and protocol of the project to potential participants as is needed, using large font on recruitment otherwise, using clear, short sentences that are familiar and comfortable to culturally diverse older adults, and using pictures or graphics that display culturally diverse adults on recruiting materials), and (c) culturally sensi tive strategies for collecting data from culturally diverse older adults (e.g., assisting participants with completing the questionnaires, allowing participants enough time to complete the questionnaires and take breaks as necessary, and using large font o n the questionnaires).
42 The participant recruitment strategies that were used include: (a) publishing advertisements in local newspapers; (c) posting flyers about the study at local businesses (e.g., libraries in various neighborhoods, and gyms), a selec tion of churches that were culturally and religiously diverse, and recreational facilities that target older adults; (d) contacting leaders of local organizations that serve older adult groups and working with them to recruit groups of older adults from th eir organizations; (e) inviting friends and family members who fit the criteria to participate in the study; and (f) tabling at the aforementioned sites. Tabling involved setting up a table where there were flyers specifying what participation in the study would involve, the participation compensation, participation criteria, the procedures for enrolling in the study, and a telephone number and email address to contact for more information about the study. The trained research assistants stood near these t ables, gave out the flyers to individuals who passed by the table, and asked these individuals to sign up to participate in the study and to receive a reminder call about the study enrollment and data collection sessions at a nearby community center. Indi viduals who were given flyers but did not enroll in the study were told to consider calling later to learn more about the study and hopefully enroll later by telephone. Participant recruitment lasted nine months. The enrollment and data collection phase to ok place at locations convenient to the recruited participants (e.g., local libraries, homes of participants, public locations with private areas) or at the research lab of the Principal Investigator. Participants scheduled their individual enrollment and data collection time by telephone, email, or at the tabling event. A small culturally diverse team of research assistants (N =
43 approximately 3) were on sight at each enrollment/data collection session to execute study procedures and answer questions and gi ve instructions. Upon arrival at an enrollment/data collection site, participants in the present study engaged in the following enrollment and data collection activities: (a) read and signed an informed consent form (ICF) indicating agreement to participa te in the study, (b) completed a pre coded DDQ and the assessment battery without placing a name on these documents so as to ensure confidentiality of the provided data; and (c) participated in the interview for the brief cognitive screening tool with a tr ained researcher. Data collection took place on several days over a nine month period. As compensation for participating in the study all participants were given a booklet on exercise and aging from the National Institutes on Aging and were invited to a f ree workshop to be held at a later date following completion of the study. It took approximately 15 to 30 minutes for the participants to complete the entire AB and 10 minutes for participants to complete the cognitive screening interview. Table 3 1. Demog raphic characteristics of participants Demographic variables N % Sex Male 32 33.7 Female 63 66.3 Race/ethnicity African American/Black 16 16.8 Non Hispanic White/Caucasian 79 83.2 Education level Less than high school 1 1.1 High school gradu ate 10 10.5 Some post high school 22 23.2 Completed post high school degree 62 65.3 Employment Full time 8 8.4 Part time 20 21.1
44 Table 3 1. Continued Demographic variables N % Employment Unemployed 67 70.5 Spouse/partner status Partner o r spouse 72 75.8 No partner or spouse 23 24.2 Living situation With partner 69 72.6 Alone 21 22.1 Other 5 5.3 Residential setting In an older living community 7 7.4 Not in an older living community 88 92.6 Annual household income Less than $25,000 5 5.3 $25,000 $49,999 24 25.3 $50,000 $74,999 23 24.2 $75,000 and over 35 36.8 Unreported 8 8.4
45 CHAPTER 4 RESULTS This chapter presents the results of the analyses conducted to address the hypotheses and research questions for the pres ent study. First, the descriptive data for the major variables in this study are reported. Second, reliabili ties alpha reliability coefficients) of the scores for each of the instruments that participants completed in this study are pre sented. Third, the results of a preliminary correlation analysis on all variables of interest are presented and discussed. Fourth, the results of the hierarchical regression analys i s that was conducted to address the first hypothesis is presente d and discussed. Fifth, the results of the analyses of covariance (ANCOVAs) that were conducted to address the second hypothesis and the first and second r esearch questions are presented and discussed. Descriptive Data for all Major Variables Initially, t ests of normality were run on each of the predictor variables ( i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy ) as well as the outcome variable (i.e., physical activity) to verify that they were normally distributed and appropriate for parametric tests. Additionally, descriptive data each study variable were determined. These descriptive data are presented i n Table 4 1. Reliability of Instruments As discussed further in this chapter, for the purposes of this study, the Problem Solving coping subscale and the Positive Reappraisal coping subscale of the Coping Responses Inventory ( CRI ) were combined to create t he adaptive coping subscale.
46 calculated for each of the five predictor variable subscales/scales and the outcome variable subscale Results indicated that for each of th ese subscales/scales the the researcher constructed Health Self Praise Questionnaire (which assesses health self praise) 89 ; the adaptive coping subscale (which was created by combining the P roblem Solving and ; the Motivation subscale of the Physical Fitness and Exercise Activity of Older Adults Scale (PFEAOAS; which assesses health motivation) 2; the C oll aborative Health Management/Injury P revention subscale of the Health Promotion Activities of Older Adults Measure (HPAOAM; which assesses health responsibility), 82; the Perceived Health Competence Scale (which assesses health self efficacy), 8 ; and the E xercise subscale of the HPAOAM (which assesses engagement in physical activity), 94 These results provide support for using the chosen subscales to assess the personal and cognitive variables of interest in this study and support for using the chosen subscale to assess level of engagement in physical activity in this study of older adults. Results of the Preliminary Pearson Correlation Analysis associations among each of the investigated predictor variables ( i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy ) and the investigated outcome variable (i.e., physical activity). This correlation analysis is pres ented in Table 4 2
47 Health Self Empowerment Theory Variable Associations The initial analysis showed that Problem Solving coping and Positive Reappraisal coping were highly correlated with one another ( r = .6 6 p < .001). Given the h igh correlation as well as previous literature supporting the collapse of two highly correlated coping style variables that are assessing two forms of active coping (Nicolotti et al., 2003), a combined coping style ( adaptive coping) was created by summing these two coping style variables. As such, throughout the rest of the analyses the adaptive coping variable will be used in place of the Positive Reappraisal and Problem Solving coping variables. Health self praise had significant positive correlations with adaptive coping ( r = 0.45, p < .001), health self efficacy ( r = 0.44, p < .001), and health motivation ( r = .50, p < .001). Health motivation had significant positive correlations with health self efficacy ( r = 0.38, p < .001) and adaptive coping ( r = 0.49, p < .001). Health self efficacy had significant positive correlations with adaptive coping ( r = 0.34, p < .001) and health responsibility ( r = 0.27, p < 01). Associations between Theory Variables and Physical Activity Variable The preliminary Pearso ysis indicated that the variable of engagement in physical activity (i.e., the health promoting lifestyle behavior variable of interest in this study) had significant positive correlations with each of the HSET based predictor variables Specifically, the following correlations were found between each predictor variable and the variable of engagement in physical activity: health self praise ( r = 0.77, p < .001), adaptive coping ( r = 0.43, p < .001), health self efficacy ( r = 0.51, p < .0 01), health motivation ( r = 0.46, p < .001), and health responsibility ( r = 0.28, p < .01).
48 Results of the Analyses to Test Hypothesis 1 Examining the Relationship between the Health Self Empowerment Theory Variables and Engagement in Physical Activity The first hypothesis stated that the health self empowerment theory (HSET) based personal and cognitive variables (i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy) would positively predict engageme nt in physical activity. In order to test this hypothesis a hierarchical regression analys i s was run with engagement in physical activity as the outcome variable. The predictor variables in the analysis were the HSET based personal and cognitive variables ( i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy ). Prior to entering the predictor variables into the regression, the physical health component and mental health component variables of the Shor t Form Health Survey 12 (SF 12) and the education variable were entered into the first block of the model in order to control for physical health, mental health, and level of education. This analys is allowed for examination of the influence of the HSET b ased variables on level of engagement in physical activity while controlling for mental and physical health and education level. Table 4 4 presents regression weights for each of the predictors in this model. The hierarchical regression model to examine w hether the HSET based variables predict engagement in exercise while controlling for physical health, mental health, and education level was significant, F ( 5,77 ) = 22.10 p < .001, R 2 = 0.63 ; adjusted R 2 = 0.59. In step 1, physical health, mental health, a nd education were included in the model. These variables together had a significant impact on engagement in physical activity ( F [3,82] = 2.86 p < .05, R 2 = 0.09 ; adjusted R 2 = 0.06). Adding the HSET based variables in blo ck 2 had an additional significant impact on
49 engagement in physical activity R 2 = 0 53. Specifically, the HSET based variables accounted for 54% of the total variance in engagement in physical activity. Health responsibility and health self praise were the only significant independent pr edictors of engagement in physical activity. Health responsibility 21 p < .01) accounted for 29.7 % of the variance in engagement in physical activity Health self praise 62 p < .0 0 1) accounted for 62.9% of the variance in engagement in phys ical activity. These findings provide partial support for hypothesis one, which stated that the HSET based personal and cognitive variables ( i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy ) wil l positively predict engagement in physical activity. While the theory variables together were significant predictors of engagement in physical activity, only health responsibility and health self praise were shown to be significant independent predictors of engagement in physical activity. Results of the Analyses to Test Hypothesi s 2 Examining the Relationship between Engagement in Physical Activity and Sex T o test the second hypothesis which stated that men will engage in significantly more physical activity than women, an analysis of covariance (ANCOVA) was run with engagement in physical activity as the dependent variable and sex as the independent variable Additionally, physical health, mental health, and education level were entered significant (p > .05), indica ting homogeneity of variance. Result of the ANCOVA indicated that level of engagement in physical activity did not vary significantly by sex, F(1,86) = 1.22, p = 0.27. The dependent variable (i.e.,
50 engagement in physical activity) had a significant positi ve association with the covariates physical health, F(1,86) = 5.10, p < .05; mental health, F(1,86) = 5.88, p < .05; education, F(1,86) = 6.39, p < 05. These findings do not provide support for hypothesis two. Results of the Analyses to Address Research Qu estions 1 and 2 Relationships between the Personal and Cognitive Variables and Race/Ethnicity and Sex To address the first research question, which asks whether the investigated health self empowerment theory (HSET) based variables differ in association w ith sex and/or race/ethnicity, five separate analyses of covariance (ANCOVAs) were run. This type of analysis was used due to the correlations among the five HSET based variables not being significant enough to warrant the use of a multivariate analysis of covariance (MANCOVA). In each ANCOVA, a different HSET based variable (i.e., health motivation, health self praise, adaptive coping, health responsibility, or health self efficacy) was the dependent variable, sex and race/ethnicity were the independent v ariables, and physical health, mental health, and education level were the covariates. In order to control for familywise Type I error, a Bonferroni correction procedure was used for each ANCOVA. The first ANCOVA had adaptive coping as the dependent variab le. In order to significant (p > .05), indicating homogeneity of variance. Results of this ANCOVA indicated that adaptive coping did not vary significantly by sex, F(1,83) = 3.93, p = 0.05, or race/ethnicity, F(1,83) = 0.57, p = 0.45.
51 test of equality of error variances was significant (p < .05), indicating non ho mogeneity of variance. In order to achieve homogeneity of variance, transformations were done to the health responsibility variable; however none of the transformations resulted in acceptable homogeneity of variance. Thus, consistent with Tabachnik and Fid ell (2007), Results of the ANCOVA revealed that health responsibility did not vary significantly by sex, F(1,85) = 2.32, p = 0.31, or race/ethnicity, F(1,85) = 2.30, p = 0.13. The third ANCOVA had health self test of equality of error variances was non significant (p > .05), indicating homogeneity of variance. Results of the ANCOVA indicated that health self praise did not var y significantly by sex, F(1,87) = 0.65, p = 0.42, or race/ethnicity, F(1,87) = 0.01, p = 0.92. The fourth ANCOVA had health self test of equality of error variances was non significant (p > .05), indicating homo geneity of variance. Results of this ANCOVA indicated that health self efficacy did not vary significantly by sex, F(1,87) = 0.31, p = 0.58, or race/ethnicity, F(1,87) = 0.75, p = 0.39. The fifth ANCOVA had health motivation as the dependent variable. Lev test of equality of error variances was non significant (p > .05), indicating homogeneity of variance. Results of this ANCOVA indicate that health motivation did not vary significantly by sex, F(1,86) = 0.48, p = 0.49, or race/ethnicity, F(1,86) = 0 .35, p = 0.56. Relationships between Engagement in Physical Activity and Race/Ethnicity To address the second research question, which asks whether engagement in physical activity differs in association with race/ethnicity, an analysis of covariance (ANCOV A) was performed. In this ANCOVA the variable engagement in physical
52 activity was entered as the dependent variable and race/ethnicity was entered as the independent variable. Additionally, physical health, mental health, and education were entered as cov significant (p > .05), indicating homogeneity of variance. Results of the ANCOVA indicate that level of engagement i n physical activity did not vary significantly by race/ethnicity, F(1,86) = 0.34, p = 0.56. The dependent variable (i.e., engagement in physical activity) had a significant positive association with the covariates physical health, F(1,86) = 4.22, p < .05; mental health, F(1,86) = 5.76, p < .05; and education, F(1,86) = 5.81, p < 05. Table 4 1. Means and standard deviations for the variables of study for the total sample and for each sex and race Variable N Mean Range SD Total sample Self praise 95 2.9 0 (1.00 4.00) 0.78 Health motivation 94 36.62 (25.00 44.00) 4.01 Health self efficacy 95 29.99 (18.00 40.00) 5.14 Health responsibility 93 46.77 (35.00 58.00) 6.19 Problem solving coping 83 20.87 (14.00 24.00) 2.48 Positive reappraisal copin g 92 19.68 (11.00 24.00) 3.47 Exercise 93 14.82 (5.00 20.00) 4.31 SF 12 physical component 95 49.44 (21.42 61.91) 9.31 SF 12 mental component 95 54.04 (9.86 68.19) 8.82 Males Self praise 32 2.83 (1.17 4.00) 0.78 Health motivation 31 36. 48 (29.00 42.00) 3.59 Health self efficacy 32 29.69 (18.00 40.00) 5.33 Health responsibility 32 45.19 (37.00 56.00) 5.70 Problem solving coping 29 20.34 (14.00 24.00) 2.11 Positive reappraisal coping 31 18.61 (11.00 24.00) 3.32 Exercise 32 14.25 (5.00 20.00) 4.36 SF 12 physical component 32 50.20 (32.94 58.38) 7.55 SF 12 mental component 32 53.40 (33.67 68.19) 7.79 Females Self praise 63 2.93 (1.00 4.00) 0.79 Heal th motivation 63 36.68 (25.00 44.00) 4.23 Health self efficacy 63 30.14 (18.00 40.00) 5.07 Health responsibility 61 47.61 (35.00 58.00) 6.32
53 Table 4 study for the total sample Predictor variables Outcome variable Se lf praise Motivation Self efficacy Adaptive coping Health r espon s. Physical activity Predictor variables Self praise -------0.50** 0.44** 0.45** 0.04 0.77** Motivation 0.50** -------0.38** 0.49** 0.03 0.46** Self efficacy 0.44** 0.38** -------0.34** 0.27* 0.51** Adaptive coping 0.45** 0.49** 0.34** -------0.18 0.43** Health r espons 0.04 0.03 0.27* 0.18 -------0.28* Outcome variable 0.77** 0.46** 0.51** 0.42** 0.28* -------Physical activity p < .01. ** p < .001. Table 4 1. Continued Variable N Mean Range SD Females Problem solving coping 54 21.15 (14.00 24.00) 2.63 Positive reappraisal coping 61 20.22 (11.00 24.00) 3.44 Exercise 61 15.11 (5.00 20.00) 4.29 SF 12 physical component 63 49.06 (21.42 61.91) 10.13 SF 12 mental component 63 54.37 (9.86 67.77) 9.34 African American/Black Self praise 16 2.74 (1.67 3.67) 0.67 Health motivation 16 35.56 (31.0 0 42.00) 3.01 Health self efficacy 16 29.63 (23.00 37.00) 4.15 Health responsibility 16 49.00 (42.00 58.00) 4.53 Problem solving coping 15 20.20 (15.00 24.00) 2.51 Positive reappraisal coping 16 19.75 (11.00 24.00) 4.01 Exercise 16 13.63 (5. 00 19.00) 4.18 SF 12 physical component 16 46.66 (23.01 60.09) 11.50 SF 12 mental component 16 50.35 (9.86 68.19) 15.00 Non Hispanic White Self praise 79 2.93 (1.00 4.00) 0.80 Health motivation 78 36.83 (25.00 44.00) 4.17 Health self ef ficacy 79 30.06 (18.00 40.00) 5.33 Health responsibility 77 46.31 (35.00 58.00) 6.41 Problem solving coping 68 21.01 (14.00 24.00) 2.46 Positive reappraisal coping 76 19.67 (11.00 24.00) 3.37 Exercise 77 15.06 (5.00 20.00) 4.32 SF 12 physica l component 79 50.01 (21.42 61.91) 8.78 SF 12 mental component 79 54.79 (31.33 65.82) 6.86
54 Table 4 3 Unstandardized beta weights (B), standard error coefficients of beta weights, physical activity from all investigated predictor variables Predictor Variables B SE B Education level 0.75 0.43 0.12 Physical health component 0.30 0.04 0.07 Mental health component 0.02 0.04 0.05 Self praise 3.50 0.49 0.62** Motivation 0.11 0.09 0.11 Self efficac y 0.12 0.08 0.15 Adaptive coping 0.02 0.06 0.02 Health responsibility 0.14 0.05 0.21* Note: R 2 = .63. p = .01 ** p < .001.
55 CHAPTER 5 DISCUSSION This chapter includes a summary and interpretations of the results of this study and a discussion of its limitations and strengths Additionally this chapter includes directions for future research and a discussion of the implications of this study for counseling psychologists. Summary of the Results The purpose of the present study was to investigate the relationships between the h ealth self empowerment theory (HSET) based personal and cognitive variables (i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy) and engagement in physical activity among culturally diverse older a dults between the ages of 65 and 75. Additionally, whether the investigated HSET based personal and cognitive variables and engagement in physical activity differed by sex and/or race/ethnicity was examined. Preliminary Analysis correlation analysis revealed that both coping style subscales of the Coping Response Inventory (CRI; i.e., Problem Solving coping and Positive Reappraisal coping) had significant positive associations with one another. Given this significant correlation and previous relevant research literature (Nicolotti et al., 2003), the two named coping styles were combined into one coping style variable (i.e., adaptive coping). Specifically, Nicolotti et al. found that two coping styles (i.e., active coping styles an d support seeking coping) were significantly associated with one another and both were significantly associated with improved emotional and behavioral
56 adjustment among children and adolescents. Thus, in that study, the two coping styles were combined into one variable. Significant positive associations were found between each of the investigated HSET based personal and cognitive variables and engagement in physical activity, which is unsurprising given the hypothesis in this study that all of these variabl es would predict engagement in physical activity. Significant positive associations were also found among several of the HSET based personal and cognitive variables. Specifically, health self praise, health motivation, health self efficacy, and adaptive co ping all had significant positive associations with one another. Given that these variables have all been shown to be characteristic of individuals who are working to improve health, it is not surprising that they are correlated. Health responsibility onl y had a significant positive association with health self efficacy. It is unsurprising that health responsibility and health self efficacy had significant positive associations given that if an individual believes he or she has control over her/his health (i.e., has increased health self efficacy) he/she may also be more likely to believe that he/she has control over whether or not he/she engages in specific behaviors that can lead to improved health (i.e., behaviors of health responsibility). Additionally, individuals with low health self efficacy may feel as if no matter what precautionary behaviors they engage in (e.g., asking the pharmacist questions about medication), they will still not have control over their health, thus they may have low health self efficacy and low health responsibility. It is surprising; however, that health responsibility did not have significant positive associations with some of the other HSET based personal and cognitive variables.
57 Specifically, given that health motivation wa s assessed using a tool that evaluates how motivated an individual is to engage in physical activity, and given that engagement in physical activity is in itself a behavior of health responsibility, it would seem possible that an individual who scores high on health motivation would also have a higher level of health responsibility. One explanation for this finding may be that overall health responsibility may not be associated with motivation to engage in physical activity. Specifically, there may be indiv iduals who are highly motivated to engage in physical activity but do not believe they have the discipline or physical capability. Additionally, individuals who are highly motivated to engage in physical activity may be motivated for reasons that are unrel ated to personal health responsibility such as the fact that their spouse or children routinely engage in physical activity. Finally, it may be that individuals who have high levels of health responsibility believe that engaging in health responsibility be taking extra precautions to enhance safety) is their way of taking care of their health, rather than engaging in other behaviors such as physical activity. Thus, their motivation for engaging in exercise behaviors may not be elevated to the same degree as their level of health responsibility. Hypotheses One The first research hypothesis in the present study stated that the health self empowerment theory (HSET) based personal and cogn itive variables (i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy) would positively predict engagement in physical activity in a sample of adults between the age of 65 and 75. In order to examine whether the HSET based personal
58 and cognitive variables would predict engagement in physical activity, a hierarchical regression analysis was performed. It was found that when controlling for education level and physical and mental health, health responsi bility and health self praise were the only statistically significant predictors of level of engagement in physical activity. The finding that health responsibility is a significant predictor of engagement in physical activity is consistent with the litera ture, which suggests that the construct of health responsibility is a greater predictor of engagement in physical activity than the constructs of education or motivation (Coulson, Strang, Marino, & Minichiello, 2004). Specifically, these researchers sugges t that health responsibility is a more impactful construct than education or motivation because it involves an individual not only having the intention to improve their health, but it also involves an individual being aware of how they can improve their he alth. It is also not surprising that health responsibility was a significant predictor of engagement in physical activity given that (a) the relationship between the HSET based variables and engagement in physical activity has been established using sampl es of younger adults (Tucker et al., 2009; Grandoit, 2010; Tucker et al., 2011 ), and (b) research suggests that older adults tend to engage in behaviors of health responsibility significantly more than younger adults (Becker & Arnold, 2004; Walker, Volkan, Sechrist, & Pender, 1988). The finding that health self praise was a significant predictor of engagement in physical activity and accounted for 62.9% of the variance in engagement in physical activity supports previous research demonstrating that the cons truct of self praise has a
59 positive significant relationship with a number of positive emotional and behavioral Hamilton, Scott, & MacDougall, 2007; Epton & Harris, 2008). It may be that of all the investigated personal and cognitive variables, health self praise (i.e., positive feedback that an individual gives herself or himself following engagement in a desired behavior) is most directly related to engaging in a behavior becaus e in order for health self praise to take place, the behavior of physical activity must take place. Thus, engagement in physical activity is an essential aspect of being able to engage in health self praise, which strengthens the relationship between self praise and engagement in physical activity. The finding that the three remaining HSET based personal and cognitive variables (i.e., health self efficacy, adaptive coping, and health motivation) did not predict engagement in physical activity was surprisin g given the literature suggesting that among older adults (a) engagement in physical activity has repeatedly been found to have significant positive associations with health self efficacy (Elavsky et al., 2005; Kirk, MacMillan, & Webster, 2010; Rimal, 2001 ) and health motivation (Cousins, 2000; Jimenez Beatty Navarro et al., 2007; Lucas et al., 2000) and (b) individuals who perceive themselves as having coping skills have been found to be more likely to engage in physical activity (Bergland, Thorsen, & Lola nd, 2010). Though these variables have been shown to be associated with engagement in physical activity, the present study is the first one to test all of the HSET based variables as predictors of engagement in physical activity among older adults. Thus, o ne explanation for the lack of significant findings is that when all five variables are included, health self efficacy,
60 adaptive coping, and health motivation may be less significant than health responsibility and health self praise. Additionally, while th e instruments used to assess health self efficacy, adaptive coping, and health motivation have been validated with samples of older adults, there may be important aspects of these variables that are not being assessed by these assessments. Hypotheses Two The second research hypothesis in this study posited that men will engage in significantly more physical activity than women. Contrary to this hypothesis, however, results indicated that there was no relationship between sex and engagement in physical acti vity. This is particularly surprising given the consistent research indicating that among older adults, males engage in significantly more exercise than females. One potential explanation for the finding of no significant sex related differences in engagem ent in physical activity is that there were significantly fewer men than women participating in this study, which may have made it more difficult to assess sex differences. In sum, hypothesis one was partially supported by the present study, while hypothes is two was not supported at all. Research Question One The first research question addressed in the present study asked if the health self empowerment theory (HSET) based personal and cognitive variables (i.e., health motivation, health self praise, adapti ve coping, health responsibility, and health self efficacy) differ in association with sex and/or race/ethnicity. Results revealed no significant sex or race/ethnicity effects in association with any of the HSET based personal and cognitive variables.
61 The research findings from investigating the first research question suggest that among the participating culturally diverse sample of older adults there are no significant race/ethnicity differences in the levels of the investigated HSET based personal and c ognitive variables. These findings are not surprising given that not much research has investigated race/ethnicity differences in the HSET based variables. In fact, among the research that has been done, only health self efficacy has been found to differ i n association with race/ethnicity. Specifically, White adults were found to report higher levels of health self efficacy than Black and Hispanic adults (Callaghan, 2005). One explanation for not finding race/ethnicity differences in health self efficacy in the present study is that the small number of African American/Black participants in this study was not sufficient to detect such differences. Additionally, given that the African American/Black participants and the white participants in this study did no t differ significantly by income and that African American/Black individuals typically have lower incomes than whites, it is possible that the race/ethnicity differences found in earlier studies had more to do with income differences than racial/ethnic dif ferences in level of health self efficacy. Additionally, among the culturally diverse sample of older adults in the present study, there were no significant sex differences in the levels of the HSET based personal and cognitive variables investigated. Th is finding is not surprising, given that there is a lack of consistent research findings from investigations of differences in the HSET based variables in association with sex. Specifically, research investigating sex differences in all five of these varia bles (i.e., health responsibility, health self efficacy, adaptive coping, health motivation, and health self praise) among older adults has
62 either been inconsistent or has not been done. Thus, the findings of the present study are important in that they ad d to the literature on the use of personal and cognitive variables and sex differences among older adults by suggesting that males and females do not differ with regard to the level of each of the HSET based variables. Research Question Two The second rese arch question addressed in the present study asked if level of engagement in physical activity differs in association with race/ethnicity. Results of the analysis to address this question indicated that there were no significant main effects of race/ethni city on level of engagement in physical activity when controlling for education level and mental and physical health. The finding of no significant differences in level of engagement in physical activity in association with race/ethnicity is not surprising given that (a) there is a lack of published research investigating this association among older adults, (b) one research study indicating that white older adults may engage in more physical activity than African American older adults also indicates that t he relationship may lose significance when education level is controlled for (Clark, 1995), and (c) education level is controlled for in the present study. Additionally, these findings are consistent with research indicating that racial/ethnic differences in level of engagement in physical activity appear to be greatest during middle adulthood and become less disparate as adults age (August & Sorkin, 2011). It may be that, when physical and mental health status and education level are controlled for, adults who are between the ages of 65 and 75 face similar barriers and motivators to engaging in physical activity, thus eliminating any potential race/ethnicity and sex differences in association with engagement in physical activity.
63 Limitations and Strengths a nd Future Directions Though this st udy is important and contributes to the research literature on personal and cognitive variables that influence engagement in physical activity among culturally diverse older adults it also ha s some noteworthy limitatio ns. One limitation is the small sample for this study particularly the small sample of African American/Black participants The sample size in the present study is in part the result of the well documented difficulty involved with recruiting older adult community members (particularly older adult community members who are racial/ethnic minorities) to be research participant s (Coleman et al., 1997; Moreno John et al., 2004; Mody et al., 2008) Additionally, including a cognitive assessment (i.e., the Mon treal Cognitive Assessment) that needed to be completed in person by a trained researcher made it more difficult to recruit participants because participants were not able to complete the assessment remotely. The cognitive assessment itself also deterred m any participants from participating thus resulting in a significant number of participants who fit the eligibility criteria but were not able to be included in the study Participants who were deterred by the cognitive assessment gave reasons such as not wanting to feel like they were being tested and feeling intimidated by certain aspects of the assessment (e.g., questions assessing memory, questions involving some level of mathematical ability). Future studies similar to the present study need to includ e large numbers of older adults in each of the major racial/ethnic groups in the US as well as more participants who identify as male In s uch studies differences in the investigated variables in association with race/ethnicity and sex can be more reliab ly examined than was the case in the present study.
64 Use of v olunteer participants who were recruited using various recruitment strategies at multiple sites that older adults would be located i s also a study limitatio n. This participant recruitment appro ach resulted in a non representative sample of older adults and thus limits generalizability of the results of this study. It is important to note that the recruitment strategies used in the present study are commonly used to recruit older adult participan ts for research studies given the difficulty with recruiting such participants. Despite the aforementioned limitations, this study provides important findings. First, the present study is the first to use the health self empowerment theory (HSET) to ex amine the personal and cognitive variables that predict engagement in physical activity among a culturally diverse sample of older adults. Given that the results provided some support for using HSET to understand the physical activity behaviors of older ad ults, this study supports further examination of the relationships between the HSET based variables and level of engagement in physical activity among older adults. Additionally, if the finding in this study that health self praise and health responsibilit y significantly predict level of engagement in physical activity is supported in future research with more diverse and representative samples, it may be important for interventions to promote physical activity among older adults to include a focus on promo ting these two personal/cognitive variables. Finally, given that the present study partially supports the use of HSET in understanding level of engagement in one type of health promoting behavior (i.e., engagement in physical activity) among older adults, future research should investigate the relationships among the HSET based variables
65 and engagement in other health promoting behaviors, such as engagement in healthy eating and stress management. Implications for Counseling Psychologists A primary goal of counseling psychologists is to engage in and address social justice issues through research and practice. Additionally, a core aspect of counseling psychology is conducting culturally sensitive research and implementing and evaluating interventions that a re culturally sensitive. The present study relates to both of these integral aspects of counseling psychology. Because older adults are particularly vulnerable to the conditions of overweight and obesity that come with not engaging in health promoting l ifestyle behaviors (e.g., not engaging in physical activity) and given that older adults often have less power or perceive that they have less power than younger adults, the empowerment and social justice orientations of counseling psychologists render the m to be well suited for conducting research and interventions to foster health promoting behaviors among older adults. Furthermore, investigating strategies to increase health promoting behaviors among vulnerable populations is consistent with the focus o f counseling psychology on health promotion and illness prevention rather than on mental illness. Additionally, given the definition of successful aging (avoidance of disability, maintenance of physical functioning, and active engagement with life) as wel l as the goal of counseling psychologists to promote this type of health, it is clear that research similar to the present study is relevant to those in the field of counseling psychology. Thus, it is appropriate and necessary for counseling psychologists to assume leadership in promoting cognitive and personal variables that are associated with physical activity and other health promoting behaviors to facilitate health and thus help eliminate health
66 disparities that plague our nation in general and dispro portionately impact its older adults. Given the focus of counseling psychologists on development across the lifespan, it is also clearly relevant for counseling psychologists to be investigating the personal and cognitive variables that influence the hea lth of older adults. Furthermore, the training that counseling psychologists have in conducting multicultural assessments and research makes them ideal for conducting research with culturally diverse samples as well as more vulnerable samples such as the s ample of older adults in the present study. Conclusions The present study examined the following among culturally diverse older adults: (a) the relationships between the health self empowerment theory (HSET) based personal and cognitive variables (i.e., health motivation, health self praise, adaptive coping, health responsibility, and health self efficacy) and engagement in physical activity, (b) sex and race/ethnicity differences in the HSET based personal and cognitive variables, and (c) sex and race/et hnicity differences in engagement in physical activity. Results of this study suggest that when controlling for physical and mental health and education level, the HSET based variables collectively predict engagement in physical activity, with health resp onsibility and health self praise being the only significant individual predictors. Additionally, results indicated that there were no sex and/or race/ethnicity differences in level of engagement in physical activity or in any of the HSET based personal a nd cognitive variables, when controlling for physical and mental health and education level.
67 It is recommended that future research investigate the relationships examined in this study in a larger representative sample of culturally diverse older adults. Additionally, future research should examine the relationships between the HSET based variables and level of engagement in other health promoting behaviors besides engagement in physical activity (e.g., engagement in healthy eating, engagement in stress ma nagement strategies). Such future research has potential for identifying personal and cognitive variables such as health self praise and health responsibility that can be promoted among older adults to increase their engagement in physical activity and oth er health promoting behaviors. Counseling psychologists have the multicultural counseling training and social justice orientation needed to empower older individuals with the cognitive and personal strengths that will be found or validated in future resea rch similar to the present study to be associated with engaging in physical activity. If the findings in the present study are validated in future similar research with larger representative samples, support will be provided for counseling psychologists a nd others to test the effects of interventions to promote health responsibility and health self praise on engagement in physical activity among culturally diverse older adults.
68 APPENDIX A INFORMED CONSENT FORM
69 APPENDIX B DEMOGRAPHIC DATA QUESTIONNAIRE DEMOGRAPHIC DATA QUE STIONNAIRE Directions : Please answer each of the questions in this questionnaire by filling in the blank or completely filling in the circle ( O) beside the answer you choose like this: What is your age? _________ What is your r ace? (Fill in the circle by the one, two, or three races that apply to you.) O African American / Black O Caucasian / White / European American O Other _________________________________ What is your sex? O Female O Male What is your current relat ionship status? O I have a spouse or partner O I do not have a spouse or partner Where do you currently live? O Alone in a house or apartment O In a home or apartment with my spouse/partner O Other: ______________ Do you currently live in an old er living community? O Yes O No What is your employment status? O I work full time O I work part time O I do not work
70 What is the highest level of education that you have completed ? O Less than high school O Completed high school O Some training beyond high school O Completed post high school What is your annual household income level? O Below $25,000 O $25,000 to $49,999 O $50,0000 to $74,000 O $75,000 or more
71 APPENDIX C HEALTH SELF PRAISE QUESTIONNAIRE Direct ions: How often do you praise yourself for each of the behaviors listed below? Please tell us by filling in the circle below the answer you choose like this: How often do you praise yourself, think positively about yourself, or feel good about yoursel Never Sometimes Often Always Does Not Apply 1. exercise (like walking, swimming, or riding a bicycle)? O O O O O 2. try to be more active than usual (like taking the stairs instead of the elevator)? O O O O O 3. exercise for about 15 20 minutes on a regular basis? O O O O O 4. participate in some kind of exercise to maintain and/or improve your health? O O O O O 5. exercise in order to maintain/reduce your body weight? O O O O O 6. plan exercise as a part of your life? O O O O O
72 APPENDIX D PHYSICAL FITNESS AND EXERCISE ACTIVITY OF OLDER ADULTS SCALE MOTIVATION SUBSCALE Directions : Please read each statement carefully. Indicate the degree to which you agree or disagr ee with the statement by filling in the circle below the answer you choose, like this: Strongly Disagree Disagree Agree Strongly Agree 1. I prefer to be in a scheduled exercise program. O O O O 2. I feel better when I am active. O O O O 3. Exercising gives me more energy. O O O O 4. Exercising gives me a sense of accomplishment. O O O O 5. Exercising keeps my mind active O O O O 6. Exercise is good for my heart. O O O O 7. Exercise helps my spirits O O O O 8. I exercise to keep myself healthy. O O O O 9. I want to exercise when I want, not when someone tells me. O O O O 10. I feel better when I am active. O O O O 11. I prefer to exercise with others. O O O O
73 A PPENDIX E COPING RESPONSES INVENTORY PROBLEM SOLVING AND POSITIVE REAPPRAISAL SUBSCALES Directions : Think about the most important problem or stressful situation you have experienced in the last 12 months (for example, troubles with a relative or friend or the illness or death of a relative or friend). Read each statement carefully and fill in the circle below that best measures how often you engaged in that behavior in connection with this problem or stressful situation. Not at all Once or Twice Someti mes Fairly often 1. Did you tell yourself things to make yourself feel better? O O O O 2. Did you make a plan of action and follow it? O O O O 3. Did you remind yourself how much worse things could be? O O O O 4. Did you know what had to be done and try hard to make things work? O O O O 5. Did you try to see the good side of the situation? O O O O 6. Did you decide what you wanted and try hard to get it? O O O O 7. Did you think about how you were much better off tha n other people with similar problems? O O O O 8. Did you try at least two different ways to solve the problem? O O O O 9. Did you try to tell yourself that things would get better? O O O O 10. Did you try to learn to do more thing s on your own? O O O O 11. Did you think about how this event could change your life in a positive way? O O O O
74 12. Did you take things a day at a time, one step at a time? O O O O Adapted and reproduced by special permi ssion of the Publisher, Psychological Assessment Resources, Inc., 16204 North Florida Avenue, Lutz, Florida 33549, from the Coping Responses Inventory Adult Form by Rudolf H. Moos, Ph.D., Copyright 1993 by PAR, Inc. Further reproduction is prohibited wit hout permission of PAR, Inc.
75 APPENDIX F PERCEIVED HEALTH COMPETENCE SCALE Directions : Please respond to the following statements by filling in the circle below the answer you choose like this: Choose the answer which best describes how you feel about your ability to manage your health. Strongly Disagree Disagree Neutral Agree Strongly Agree 1 It is difficult for me to find effective solutions for my health that come my way. O O O O O 2 I find efforts to change things I e about my health are ineffective. O O O O O 3 I handle myself well with respect to my health. O O O O O 4 I am able to do things for my health as well as most other people. O O O O O 5 I succeed in the projects I undertake to improve my health. O O O O O 6 Typically, my plans for my O O O O O 7 No matter how hard I try, my I would like. O O O O O 8 I am generally able to accomplish my goals with regard to my health. O O O O O
76 APPENDIX G HEALTH PROMOTION ACTIVITIES OF OLDER ADULTS MEASURE EXERCISE AND COLLABORATIVE HEALTH MANAGEMENT/INJURY PREVENTION SUBSCALES Directions : Please read each statement c arefully, and then fill in the circle below the answer circle the response that best measures how often you complete those activities. Always Frequently Occasionally Never 1 Perform some form of exercise (i.e., walking, golfing, dancing, swimming, aero bics) 2 to 3 times a week. O O O O 2 Visit a physician on a regular basis. O O O O 3 Ask health professionals how to better manage my health. O O O O 4 Inspect home for safety hazards O O O O 5 Exercise for about 15 20 minutes on a regular basis. O O O O 6 Obtain eye exams on a regular basis. O O O O 7. Clarify unclear health information with health professionals. O O O O 8. Participate in some kind of exercise to maintain and/or improv e my health. O O O O 9. Have blood pressure checked regularly. O O O O 10. Plan exercise as a part of my life. O O O O 11. Ask pharmacist questions about medications. O O O O
77 12. Have cholesterol checked on a regular bas is. O O O O 13. Exercise (i.e., walking, golfing, dancing, swimming, aerobics, bicycling) in order to maintain/reduce my body weight. O O O O 1 4 Contact the doctor when experiencing unusual body symptoms or changes. O O O O 15 Take prescribed medications as ordered by doctor/health professional. O O O O 16 Watch TV programs about health. O O O O 17 Discuss health concerns with family/significant others O O O O 18 Check with physician/pharmacist about medication side effects. O O O O 19 Inspect walkways (i.e., stairs, hallways) for adequate lighting. O O O O 20 Secure mats and throw rugs at home to prevent injury. O O O O
78 APPENDIX H SHORT FORM HEALTH SURVEY 12 Your Health and We ll Being This survey asks for your views about your health. This information will help keep track of how you feel and how well you are able to do your usual activities. Thank you for completing this survey! For each of the following questions, please m ark an in the one box that best describes your answer. 1. In general, would you say your health is: 2. The following questions are about activities you might do during a typical day. Does your health now limit you in these activities? If so, how much? Yes, limited a lot Yes, limited a little No, not limited at all a Moderate activities such as moving a table, pushing a vacuum cleaner, bowling, or playing golf ............................. 1 .............. 2 ............. 3 b C limbing several flights of stairs ................................ ............. 1 .............. 2 ............. 3 Excellent Very good Good Fair Poor 1 2 3 4 5
79 3. During th e past 4 weeks how much of the time have you had any of the following problems with your work or other regular daily activities as a result of your physical health ? 4. During the past 4 weeks how much of the time have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious)? 5. During the past 4 weeks how much did pain interfere with your normal work (including both work outside the home and housework)? Not at all A little bit Moderately Quite a bit Extremely 1 2 3 4 5 All of the time Most of the time Some of the time A little of the time None of the time a Accomplished less than you would like ................................ ...... 1 ............. 2 .............. 3 .............. 4 ............. 5 b Were limited in the kind of work or other activities .................. 1 ............. 2 .............. 3 .............. 4 ............. 5 All of the time Most of the time Some of the time A little of the time None of the time a Accomplished less than y ou would like ................................ ...... 1 ............. 2 .............. 3 .............. 4 ............. 5 b Did work or other activities less carefully than usual ................ 1 ............. 2 .............. 3 .............. 4 ............. 5
80 6. These questions are about how you feel and how things have been with you during the past 4 weeks For each question, please give the one answer that comes closest to the way you have been feeling. How much of the time during the past 4 weeks 7. During the past 4 weeks how much of the time has your physical health or emotional problems interfered with your social activities (l ike visiting with friends, relatives, etc.)? Thank you for completing these questions! SF 12v2 Health Survey 1994, 2002 Medical Outcomes Trust and QualityMetric Incorporated. All rights reserved. SF 12 is a registered trademark of Medical Outcomes Trust. (SF 12v2 Health Survey Standard, Unite d States (English)) All of the time Most of the time Some of the time A little of the time None of the time a Have you felt calm and peaceful? ................................ ........ 1 .............. 2 .............. 3 .............. 4 .............. 5 b Did you have a lot of energy? ....... 1 .............. 2 .............. 3 .............. 4 .............. 5 c Have you felt downhear ted and depressed? ............................... 1 .............. 2 .............. 3 .............. 4 .............. 5 All of the time Most of the time Some of the time A little of the time None of the time 1 2 3 4 5
81 APPENDIX I MONTREAL COGNITIVE ASSESSMENT
85 REFERENCES Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting behavior Englewood Cliffs, NJ: Prentice Hall. Ajzen, I., & Madden, T. J. (1986). Prediction of goal directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22 453 474. doi: 10.1016/0022 1031(86)90045 4 Allen, R. S., Phillips, L. L., Pekmezi, D., Crowther, M. R., & Prentice Dunn, S. (2009) Living well with living wills: Application of protection motivation theory to living wills among older Caucasian and African American adults. Clinical Gerontologist, 32 (1), 44 59. doi: 10.1080/07317110802474643 Ammouri, A. A., Neuberger, G., Nashwan, A J., & Al Ha j, A. M. ( 2007 ). Determinants of self reported physical activity among Jordanian adults. Journal of Nursing Scholarship, 39 (4), 342 348. doi: 10.1111/j.1547 5069.2007.00191.x Arcury, T. A., Quandt, S. A., & Bell, R. A. (2001). Staying health y: The salience and meaning of health maintenance behaviors among rural older adults in North Carolina. Social Science and Medicine, 53 (11), 1541 1556. doi: 10.1016/S0277 9536(00)00442 1 Arras, R. E., Ogletree, R. J., & Welsheimer, K. J. (2006). Health p romoting behaviors in men age 45 and above. (1), 65 79. doi: 10.3149/jmh.0501.65 August, K. J., & Sorkin, D. H. (2011). Racial/ethnic disparities in exercise and dietary behaviors of middle aged and older adults. J ournal of General Internal Medicine, 26 (3), 245 250. doi: 10.1007/s11606 010 1514 7 Ayotte, B.J., Margett, J.A., Hicks Patrick, J. (2010). Physical activity in middle aged and young old adults: The roles of self efficacy, barriers, outcome expectancies, self regulatory behaviors and social support. Journal of Health Psychology, 15 (2), 173 185. doi: 10.1177/1359105309342283. Bandura, A. (1991). Social cognitive theory of self regulation. Organizational Behavior and Decision Processes, 50 248 287. Bandu ra, A. (1997). Self efficacy: The exercise of control New York: W. H. Freeman & Co. Batsis, J. A., Clark, M. M., Grothe, K., Lopez Jimenez, F., Collazo Clavell, M. L., Somers, V. K., & Sarr, M. G. (2009). Self efficacy after bariatric surgery for obesity. A population based cohort study. Appetite, 52 (3), 637 645. doi: 10.1016/j.appet.2009.02.017
86 Becker, C. M., & Arnold, W. (20 04 ). Health promoting behaviors of older Americans versus young and middle aged adults. Educational Gerontology, 30 (10), 835 844 doi: 10.1080/03601270490507277 Bergland, A., Thorsen, K., & Loland, N. ( 2010 ). The relationship between coping, self esteem and health on outdoor walking ability among older adults in Norway. Ageing and Society, 30 949 964. Beverly, E. A., & Wray, L. A. (2010). The role of collective efficacy in exercise adherence: A qualitative study of spousal support and Type 2 diabetes management. Health Education Research, 25 (2), 211 223. doi: 10.1093/her/cyn032 Brawley, L. R., Rejeski, W. J., & King, A. C. ( 20 03 ). Promoting physical activity for older adults: The challenges for changing behavior. American Journal for Preventive Medicine, 25 (3), 172 183. doi: 10.1016/S0749 3797(03)00182 X Buman, M. P., Yasova, D., & Giacobbi, P. R. (2010) Descriptive and nar rative reports of barriers and motivators to physical activity in sedentary older adults. Psychology of Sport and Exercise, 11 223 230. Calder, N., & Aitken, R. (2008). An exploratory study of the influences that comprise the sun protection of young ad ults. International Journal of Consumer Studies, 32 (6), 579 587. doi: 10.1111/j.1470 6431.2008.00699.x Callaghan, D. (2005). Healthy behaviors, self efficacy, self care, and basic conditioning factors in older adults. Journal of Community Health Nursing, 22 (3), 169 178. Caragata, G. E., Tuokko, H., & Damini, A. ( 2009 ). Fit to drive: A pilot study to improve the physical fitness of older drivers. Activities, Adaptation, and Ageing, 33 (4), 240 255. doi: 10.1080/01924780903349080 Carroll, D. L. ( 1995 ). T he importance of self efficacy expectations in elderly patients recovering from coronary artery bypass surgery. Heart & Lung, 24 50 59. Centers for Disease Control and Prevention. (2010, June). Defining overweight and obesity. National Center for Chron ic Disease Prevention and Health Promotion Retrieved from http://www.cdc.gov/obesity/defining.html Centers for Disease Control and Prevention. (2009, May). NCHS data on obesity. National Center for Health Statistics Retrieved from http://obesity.procon.o rg/sourcefiles/NCHSDataOnObesity.pdf Centers for Disease Control and Prevention (2011, December). National Center for Chronic Disease Prevention and Health Promotion. Retrieved from http://www.cdc.gov/arthritis/pa_overview.htm
87 Chad, K. E., Reeder, B. A., H arrison, E. L., Ashworth, N. L., Sheppard, S. M., Schultz, S. L., . Lawson, J. A. (2005). Profile of physical activity levels in community dwelling older adults. Medicine & Science in Sports & Exercise, 37 (10), 1774 1784. Chastin, S. F. M., Ferrioll i, E., Stephens, N. A., Fearon, K. C., & Greig, C. (2011). Relationship between sedentary behaviour, physical activity, muscle quality and body composition in healthy older adults. Age and Ageing Advance online publication. doi: 10.1093/ageing/afr075 Chen S. H., Acton, G., & Shao, J. H. (2010). Relationships among nutritional self efficacy, health locus of control and nutritional status in older Taiwanese adults. Journal of Clinical Nursing, 19 (15 16), 2117 2127. doi: 10.1111/j.1365 2702.2009.03186.x Ch en, Y. C., Wu, H. P., Hwang, S. J., & Li, I. C. (2010). Exploring the components of metabolic syndrome with respect to sex difference and its relationship to health promoting lifestyle behavior: A study in Taiwanese urban communities. Journal of Clinical N ursing, 19 (21 22), 3031 3041. doi: 10.1111/j.1365 2702.2010.03280.x Clark, D.O. (1995). Racial and educational differences in physical activity among older adults. Gerontologist, 35 (4), 472 480. Retrieved from http://gerontologist.oxfordjournals.org/look up/pmid?view=long&pmid=7557517 Clark, D. O., & Nothwehr, F. (1999). Exercise self efficacy and its correlates among socioeconomically disadvantaged older adults. Health Education and Behavior, 26 535 546. doi: 10.1177/109019819902600410 Coleman, E.A., T yll, L., LaCroix, A.Z., Allen, C., Leveille, S.G., Wallace, J.I.,. . Wagner, E.H. (1997). Recruiting African American older adults for a community based health promotion intervention: Which strategies are effective? American Journal of Preventive Medicin e, 13 51 56. Coulson, I., Strang, V., Marino, R., & Minichiello, V. ( 2004 ). Knowledge and lifestyle behaviors of healthy older adults related to modifying the onset of vascular dementia. Archives of Gerontology & Geriatrics, 39 43 58. Cousins, S. O. ( 2000 ). Grounding theory in self referent thinking: Conceptualizing motivation for older adult physical activity. Psychology of Sport and Exercise, 4 (2), 81 100. doi: 10.1016/S1469 0292(01)00030 9 Cross, S. E., & Markus, H. (1991). Possible selves across the life span. Human Development, 34 230 255. doi: 10.1159/000277058 physical activity. American Journal of Health Behavior, 32 (6), 570 582.
88 Daviglus, M. L., J. (2003). Body mass index in middle age and health related quality of life in older age. Archives of Internal Medicine, 163 (20), 2448 2455. Retrieved from www.archinternmed.com Davis, C., Fox, J., Brewer, H., & Ratusny, D. (1995). Motivations to exercise as a function of personality characteristics, age, and sex Personality and Individual Differences, 19 165 174. doi: de Silva Sanigorski, A. M., Bell, A. C., Kremer, P., Nich ols, M., Crellin, M., Smith, . Swinburn, B. A. (2010). Reducing obesity in early childhood: Results from Romp & Chomp, an Australian community wide intervention program. American Journal of Clinical Nutrition 91 (4), 831 840. doi: 10.3945/ajcn.2009.288 26 Duffy, M. E. (1993). Determinants of health promoting lifestyles in older persons. Journal of Nursing Scholarship, 25 (1), 23 28. doi: 10.1111/j.1547 5069.1993.tb00749.x Elavsky S., McAuley, E., Motl, R. W., Konopack, J. F., Marquez, D. X., Hu, L., . Diener, E. (2005). Physical activity enhances long term quality of life in older adults: Efficacy, esteem, and affective influences. Annals of Behavioral Medicine, 30 (2), 138 145. doi: 10.1207/s15324796abm3002_6 Epton, T., & Harris, P. R. (2008). Sel f affirmation promotes health behavior change. Health Psychology, 27 746 752. Finch, H. (1997). Physical activity at our age: Qualitative research among older people London, UK: Health Education Authority. Flegal, K. M., Carroll, M. D., Ogden, C. L., & Curtin, L. R. (2010). Prevalence and trends in obesity among US adults, 1999 2008. Journal of the American Medical Association, 303 (3), 235 241. doi: 10.1001/jama.2009.2014 Flegal, K. M., Carroll, M. D., Ogden, C. L., & Johnson, C. L. (2002). Prevale nce and trends in obesity among US adults, 1999 2000. Journal of the American Medical Association, 288 1723 1727. doi: 10.1001/jama.288.14.1723 Folkman, S., & Lazarus, R. S. (1980). An analysis of coping in a middle aged community sample. Journal of H ealth and Social Behavior, 21 (3), 219 239. Retrieved from http://www.jstor.org/stable/2136617 Folkman, S., Lazarus, R. S., Pimley, S., & Novacek, J. (1987). Age differences in stress and coping processes. Psychology and Aging 2(2), 171 184. doi Galvi n, J. E., Fu, Q., Nguyen, J. T., Glasheen, C., & Scharff, D. P. (2008). Psychosocial Dementia, 4 (5), 353 360. doi: 10.1016/j.jalz.2007.09.005
89 Gardiner, P. A., Healy, G. N., Eaki n, E. G., Clark, B. K., Dunstan, D. W., Shaw, J. E., . Owen, N. (2011). Associations between television viewing time and overall sitting time with the metabolic syndrome in older men and women: The Australian diabetes obesity and lifestyle study. Jour nal of American Geriatrics Society, 59 (5), 788 796. doi: 10.1111/j.1532 5415.2011.03390.x Gilchrist, L. D., Schinke, S. P., Bobo, J. K., & Snow, W. H. ( 1986 ). Self control skills for preventing smoking. Addictive Behaviors, 11 169 174. Glass, T. A., Rasmussen, M. D., & Schwartz, B. S. (2006). Neighborhoods and obesity in older adults: The Baltimore memory study. American Journal of Preventive Medicine, 31 (6), 455 463. doi: 10.1016/j.amepre.2006.07.028 Goldman, N., Turra, C., Rosero Bixby, L., Weir, D., & Crimmins, E. (2011). Do biological measures mediate the relationship between education and health? A comparative study. Social Science & Medicine, 72 (2), 307 315. doi: 10.1016/j.socscimed.2010.11.004 Grandoit, D. J. (2010). Relationships among health self empowerment theory variables, health promoting behaviors, and BMI in a sample of culturally diverse adults. Greaney, M. L., Lees, F. D., Greene, G. W., & Clark, P. G. (2004). What older adults find useful for maintaining healthy eating and exercise habits. Journal of Nutrition for the Elderly, 24 (2), 19 35. Grembowski, D., Patrick, D., Diehr, P., Durham, M., Beresford, S., Kay, E., & Hecht, J. (1993). Self efficacy and health be havior among older adults. Journal of Health and Social Behavior, 34 89 104. Retrieved from http://www.jstor.org/stable/2137237 Hamilton, R. A., Scott, D., & MacDougall, M. P. ( 2007 ). Assessing the effectiveness of self talk interventions on endurance p erformance. Journal of Applied Sport Psychology, 19 226 239. Haq, M. B., & Griffin, M. (1996). Health motivation: Key to health promoting behavior? The Nurse Practitioner, 21 (11), 155 156. Haskell, W.L., Blair, S.N., & Hill, J.O. (2009). Physical ac tivity: Health outcomes and importance for public health policy. Preventive Medicine, 49 280 282. Retrieved from http://www.activelivingresearch.org/files/2_PM2009_Haskell.pdf Heckhausen, J. ( 1997 ). Developmental regulation across adulthood: Primary and s econdary control of age related challenges. Developmental Psychology, 33 (1), 176 187. doi: 10.1037/0012 16184.108.40.206
90 Heckhausen, J. ( 1999 ). Developmental regulation in adulthood: Age normative and sociostructural constraints as adaptive challenge s. NY: Cambridge University Press Heckhausen J., & Shulz, R. ( 1995 ). A life span theory of control. Psychological Review, 102 (2), 284 304. doi: 10.1037/0033 295X.102.2.284 Jackson, K. M, & Aiken, L. S. (2000). A psychosocial model of sun protection and sunbat hing in young women: The impact of health beliefs, attitudes, norms, and self efficacy for sun protection. Health Psychology, 19 (5), 469 478. doi: 10.103TO0278 6I220.127.116.119 ies and body mass index. Journal of Aging and Health, 20 (2), 217 234. doi: 10.1177/0898264307310466 Jenkins, L. S., & Gortner, S. R. (1998). Correlates of self efficacy expectation and prediction of walking behavior in cardiac surgery elders. Annals of B ehavioral Medicine, 20 (2), 99 103. doi: 10.1007/BF02884455 Jimenez Beatty Navarro, J. E., Graupera Sanz, J. L., del Castillo, J. M., Izquierdo, A. C., & Rodriguez, M. M. (2007). Motivational factors and physician advice for physical activity in older urb an adults. Journal of Ageing and Physical Activity, 15 (3), 241 256. Kalavar, J., Kolt, G. S., Giles, L. C., & Driver, R. P. (2004). Physical activity in older Asian Indians living in the United States: barriers and motives. Activities, Adaptation and Ag eing, 29 (1), 47 67. Kaplan, M. S., Huguet, N., Newsom, J. T., McFarland, B. H., & Lindsay, J. (2003). Prevalence and correlates of overweight and obesity among older adults: Findings from the Canadian national population health survey. Journals of Geron tology: Series A, 58 (11), M1018 M1030. doi: 10.1093/gerona/58.11.M1018 King, A. C. (2001). Interventions to promote physical activity by older adults. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 56 36 46. doi: 10.10 93/gerona/56.suppl_2.36 King, A. C., Pruitt, L. A., Phillips, W., Oka, R., Rodenburg, A., & Haskell, W. L. (2000). Comparative effects of two physical activity programs on measured and perceived physical functioning and other health related quality of life outcomes in older adults. Journal of Gerontology, 55 (2), 74 83. Kirk, A., MacMillan, F., & Webster, N. ( 2010 ). Application of the transtheoretical model to physical activity in older adults with Type 2 diabetes and/or cardiovascular disease. Psychology of Sport and Exercise, 11 (4), 320 324. doi: 10.1016/j.psychsport.2010.03.001
91 Klug, C., Toobert, D. J., & Fogerty, M. (2008). Healthy changes for living with diabetes: An evidenced based community diabetes self management program. Diabetes Education, 34 ( 6), 1053 1061. 10.1177/0145721708325886 Kruger, J., Ham, S. A., & Prohaska, T. R. (2009). Behavioral risk factors associated with overweight and obesity among older adults: The 2005 national health interview survey. Preventing Chronic Disease: Public Hea lth Research, Practice, and Policy, 6 (1). Retrieved from: http://www.cdc.gov/pcd/issues/2009/jan/07_0183.htm Kwong, E. W., & Kwan, A. Y. (2007). Participation in health promoting behavior: Influences on community dwelling older Chinese people. Journal of A dvanced Nursing, 57 (5), 522 534. doi: 10.1111/j.1365 2648.2006.04132.x Lazarus, R., & Folkman, S. (1984). Stress, appraisal, and coping New York: Springer. Lee, J. Y., Lee, D. W., Cho, S. J., Na, D. L., Hong, J. J., Kim, S. K., . Maeng, J. C. (2008 ). Brief screening for mild cognitive impairment in elderly outpatient clinic: Validation of the Korean version of the Montreal Cognitive Assessment. Journal of Geriatric Psychiatry and Neurology, 21 (2), 104 110. doi: 10.1177/0891988708316855 Lees, F. D. Clark, P. G., Nigg, C. R., & Newman, P. (2005). Barriers to exercise behavior among older adults: A focus group study. Journal of Aging and Physical Activity, 13 (1), 22 33. doi: Levasseur, M., St Cyr Tribble, D., & Desrosiers, J. (2009). Meaning of qu ality of life for oldr adults: Importance of human functioning components. Archives of Gerontology and Geriatrics, 49 (2), 91 100. doi: 10.1016/j.archger.2008.08.013 ratings, and behaviors. Nursin g Research, 53 (3), 198 206. doi: 10.1097/00006199 200405000 00007 Lopez Garcia, E., Banegas Banegas, J. R., Gutierrez Fisac, J. L., Perez Regadera, A. G., Diez Ganan, L., & Rodriguez Artalejo, F. R., (2003). Relation between body weight and health relate d quality of life among the elderly in Spain. International Journal of Obesity, 27 701 709. doi: 10.1038/sj.ijo.0802275 Lucas, J. A., Orshan, S. A., & Cook, F. ( 2000 ). Determinants of health promoting behavior among women ages 65 and above living in the community. Research and Theory for Nursing Practice, 14 (1), 77 100. Luis, C. A., Keegan, A. P., & Mullan, M. (2009). Cross validation of the Montreal Cognitive Assessment in community dwelling older adults residing in the Southeastern US. International Journal of Geriatric Psychiatry, 24 197 201. doi: 10.1002/gps.2101
92 Maddux, J. E., & Rogers, R. W. (1983). Protection motivation and self efficacy: A revised theory of fear appeals and attitude change. Journal of Experimental Social Psychology, 19 (5), 4 69 479. doi: 10.1016/0022 1031(83)90023 9 Marks, G. R., & Lutgendorf, S. K. (1999). Perceived health competence and personality factors differentially predict health behaviors in older adults. Journal of Aging and Health, 11 (2), 221 239. doi: 10.1177/0 89826439901100205 McAuley E., & Blissmer, B. ( 2000 ). Self efficacy determinants and consequences of physical activity. Exercise and Sport Sciences Reviews, 28 (2), 85 88. McAuley, E., Morris, K. S., Motl, R. W., Hu, L., Konopack, J. F., & Elavsky, S. ( 2 007 ). Long term follow up of physical activity behavior in older adults. Health Psychology, 26 (3), 375 380. doi: 10.1037/0278 618.104.22.1685 McCartney, N., Hicks, A.L., Martin, J., & Webber, C.E. (1995). Long term resistance training in the elderly: Effec ts on dynamic strength, exercise capacity, muscle, and bone. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 50 (2), B97 104. Retrieved from http://biomedgerontology.oxfordjournals.org/content/50A/2/B97.long McIlvane, J. M. (2007). Disentangling the effects of race and SES on arthritis related symptoms, coping, and well being in African American and White women. Aging and Mental Health 11(5), 556 569. Mody, L., Miller, D.K., McGloin, J.M., Freeman, M., Marcantonio, E.R., Magaziner, J., & Studenski, S. (2008). Recruitment and retention of older adults in aging research. Journal of the American Geriatrics Society, 56 (12), 2340 2348. doi: 10.1111/j.1532 5415.2008.02015.x Mokdad, A. H., Bowman, B. A., Ford, E. S., Vinicor, F., Marks, J. S., & Koplan, J. P. (2001). The continuing epidemics of obesity in the United States. Journal of the American Medical Association, 286 1195 1200. Mokdad, A. H., Serdula, M .K., Dietz, W. H., Bowman, B. A., Marks, J. S., & Koplan, J. P. (1999 ). The spread of the obesity epidemic in the United States, 1991 1998. Journal of the American Medical Association, 282 (15), 19 22. with negative life events: Comm on processes of managing health, interpersonal, and financial/work stressors. International Journal of Aging and Human Development, 62 (1), 39 59. Moreno John, G., Gachie, A., Fleming, C.M., Napoles Springer, A, Mutran, E., Manson, S.M., & Perez Stable, E.J. (2004). Ethnic minority older adults participating in clinical research: Developing trust. Journal of Aging and Health, 16 (5), 93S 123S. doi: 10.1177/0898264304268151
93 Morowatisharifabad, M. A., Ghofranipour, F., Heidarnia, A., Ruchi, G. B., & Ehrampou sh, M. H. (2006). Self efficacy and health promotion behaviors of older adults in Iran. Social Behavior and Personality, 34 (7), 759 768. Mottus, R., Johnson, W., Murray, C., Wolf, M.S., Starr, J.M., & Deary, I.J. (2013). Towards understanding the links between health literacy and physical health. Health Psychology Advance online publication. Retrieved from http://uh7qf6fd4h.search.serialssolutions.com.lp.hscl.ufl.edu/?V=1.0&pmid=2343 7854 National Center for Health Statistics. (2010). Health, United Stat es, 2009: With special feature on medical technology. Retrieved from http://www.cdc.gov/nchs/data/hus/hus09.pdf#executivesummary Newsom, J. T., Kaplan, M. S., Huguet, N., & McFarland, B. (2004). Health behaviors in a representative sample of older Canadian s: Prevalences, reported change, motivation to change, and perceived barriers. The Gerontologist, 44 193 205. Nicolotti, L., El conflict and their adjustment and physical health: Vulne rability and protective functions. Journal of Family Psychology, 17 (3), 315 326. doi: 10.1037/0893 322.214.171.1245 n, M. L., Buikstra, E., Fallon, T., & Hegney, D. ( 2009 ). Strategies for success: A toolbox of coping strategies used by breastfeeding wom en. Journal of Clinical Nursing, 18 (11), 1574 1582. doi: 10.1111/j.1365 2702.2008.02667.x A. ( 1985 ). Self efficacy and health. Behaviour Research and Therapy, 23 (4), 437 451. doi: 10.1016/0005 7967(85)90172 X Padula, C. A. (1997). Development of the health promotion activities of older adults measure. Public Health Nursing, 14 (2), 123 128. Padula, C. A., & Sullivan, M. (2006). Long behaviors: Identifying factors that impact decision making. Journal of G erontological Nursing 32(10), 37 47. Pender, N. J. (1996). Health promotion in nursing practice (3 rd E d.). Stamford, CT: Appleton & Lange. Penedo,F.J., & Dahn, J.R. (2005). Exercise and well being: A review of mental and physical health benefits associ ated with physical activity. Current Opinion in Psychiatry, 18 (2), 189 193. Retrieved from http://journals.lww.com/co psychiatry/pages/default.aspx Purnell, J. Q., Katz, M. L., Andersen, B. L., & Bennett, N. ( 2010 ). Social and cultural factors are related to perceived colorectal screening benefits and intentions in
94 African Americans. Journal of Behavioral Medicine, 33 (1), 24 34. doi: 10.1007/s10865 009 9231 6 Richman, R. M., Loughnan, G. T., Droulers, A. M., Steinbeck, K. S., & Caterson, I. D. ( 2001 ). Sel f efficacy in relation to eating behavior among obese and non obese women. International Journal of Obesity, 25 (6), 907 913. Retrieved from http://www.nature.com/ijo/journal/v25/n6/abs/0801606a.html Riebe, D., Blissmer, B. J., Greaney, M. L., Garber, C. E., Lees, F. D., & Clark, P. G. (2009). The relationship between obesity, physical activity, and physical function in older adults. Journal of Aging and Health, 21 (8), 1159 1178. doi: 10.1177/0898264309350076 Rimal, R. N. (2001). Longitudinal influences of knowledge and self efficacy on exercise behavior: Tests of a mutual reinforcement model. Journal of Health Psychology, 6 (1), 31 46. doi: 10.1177/135910530100600103 Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social learning theory and the health belief model. Health Education and Behavior, 15 (2), 175 183. doi: 10.1177/109019818801500203 Rowe, J. W., & Kahn, R. L. (1997). Successful aging. The Gerontologist, 37 (4), 433 440. doi: 10.1093/geront/37.4.433 Sachs Ericsson, N., Burns, A. B ., Gordon, K. H., Eckel, L. A., Wonderlich, S. A., Crosby, R. D., & Blazer, D. G. (2007). Body mass index and depressive symptoms in older adults: The moderating roles of race, sex, and socioeconomic status. American Journal of Geriatric Psychiatry, 15 (9), 815 825. doi: 10.1097/JGP.0b013e3180a725d6 Schaie K.W. & Willis, S. L. (2002). Adult development and aging (5th Ed.). Upper Saddle River, NJ : Prentice Hall. Schmiege, S. J., Aiken, L. S., Sander, J. L., & Gerend, M. A. (2007). Osteoporosis prevention among young women: Psychosocial models of calcium consumption and weight bearing exercise. Health Psychology, 26 (5), 577 587. doi: 10.1037/0278 6126.96.36.1997 Schoenborn, C. A., Vickerie, J. L., & Powell Griner, E. (2006). Health characteristics of adult s 55 years of age and over: United States, 2000 2003. Advance data from vital and health statistics (No. 370) Hyattsville: National Center for Health Statistics. Shawler C., & Logsdon, D. ( 2008 ). Living vigilant lives with chronic illness: Stories fro m older low income minority women. Health Care for Women International, 29 76 84. doi: 10.1080/07399330701723863
95 Smith, J., & Baltes, M. M. (1998). The role of sex in very old age: Profiles of functioning and everyday life patterns. Psychology and Agein g, 13 (4), 676 695. doi: 10.1037/0882 79188.8.131.526 Smith, M. S., Wallston, K. A., & Smith, C. A. (1995). The development and validation of the Perceived Competence Scale. Health Education Research, 10 (1), 51 64. doi: 10.1093/her/10.1.51 Song, R., June K. J., Kim, C. G., & Jeon, M. Y. (2004). Comparisons of motivation, health behaviors, and functional status among elders in residential homes in Korea. Public Health Nursing, 21 (4), 361 371. doi: 10.1111/j.0737 1209.2004.21410.x Swartz, A., Strath, S., Parker, S., Miller, N., & Cieslik, L. (2007). Ambulatory activity and body mass index in White and non White older adults. Journal of Physical Activity and Health, 4 (3), 294 304. Tabachnik, B. G. & Fidell, L. S. (2007). Using multivariate statistics (5 th ed.). Boston, MA: Pearson. Tucker, C. M., Butler, A. M., Loyuk, I. S., Desmond, F. F., & Surrency, S. L. (2009). Predictors of a health promoting lifestyle and behaviors among low income African American mothers and White mothers of chronically ill chi ldren. Journal of the National Medical Association, 101 (2), 103 110. Tucker, C. M., Daly, K., & Herman, K. C. (2009). Customized mental health counseling: Bridging the gap between mental and physical health for racial and ethnic minorities In J. G. Pon terotto, J. M. Casas, L. A. Suzuki, & C. M. Alexander, Handbook of multicultural counseling (4 th edition). Thousand Oaks, CA: Sage. Tucker, C. M., Rice, K. G., Hou, W., Kaye, L. B., Nolan, S. E. M., Grandoit, D. J., . Desmond, F. F. (2011). Development of the Motivators and Barriers to Health Smart Behaviors Inventory. Psychological Assessment, 23 (2), 487 503. doi: 10.1037/a0022299 US Department of Health and Human Services, Healthy people 2010: Understanding and Improving Health 2nd ed. US Governmen t Printing Office, Washington DC; 2000. Vincent, G.K., & Grayson, V. A. (2010). The older population in the United States: 2010 to 2050. Current Population Reports Retrieved from the U.S. Census Bureau, U.S. Department of Commerce website: http://www.cen sus.gov/prod/2010pubs/p25 1138.pdf Walker, S. N., & Hill Polerecky, D. M. (1996). Psychometric evaluation of the Health Promoting Lifestyle Profile II. (Unpublished manuscript). University of Nebraska Medical Center, Lincoln, NE. Retrieved from
96 http://deep blue.lib.umich.edu/bitstream/2027.42/85349/2/HPLP_II Dimensions.pdf Walker, S. N., Sechrist, K. R., & Pender, N. J. (1987). The Health Promoting Lifestyle Profile: Development and psychometric characterizations. Nursing Research, 36 (2), 76 81. Walker, S N., Volkan, K., Sechrist, K. R., & Pender, N. J. (1988). Health promoting life styles of older adults: Comparisons with young and middle aged adults, correlates and patterns. Advanced Nursing Science, 11 76 90. Walsemann, K. M., & Ailshire, J. A. (2 011). BMI trajectories during the transition to older adulthood: Persistent, widening, or diminishing disparities by ethnicity and education? Research on Aging, 33 (3), 286 311. doi: 10.1177/0164027511399104 Wang, Y. & Beydoun, M. (2007). The obesity epid emic in the United States sex age, socioeconomic, racial/ethnic, and geographic characteristics: A systematic review and meta regression analysis. Epidemiological Reviews, 29 (1), 6 28. doi: 10.1093/epirev/mxm007 Wan g Y. C., Colditz, G. A., & Kuntz, K M. ( 2007 ). Forecasting the obesity epidemic in the aging U.S. population. Obesity, 15 (11), 2855 2865. doi: 10.1038/oby.2007.339 Warziski, M., Sereika, S. M., Styn, M. A., Music, E., & Burke, L. E. ( 2008 ). Changes in self efficacy and dietary adherence: The impact on weight loss in the PREFER study. Journal of Behavioral Medicine, 31 (1), 81 92. Wiesmann, U., & Hannich, H. J. ( 2011 ). Salutogenic perspectives on health maintenance: The role of resistance resources and meaningfulness. The Journal of Gere ntopsychology and Geriatric Psychiatry, 24 (3), 127 135. Wilcox, S., Der Ananian, C., Abbott, J., Vrazel, J., Ramsey, C., Sharpe, P. A., & Brady, T. (2006). Perceived exercise barriers, enablers, and benefits among exercising and nonexercising adults wit h arthritis: Results from a qualitative study. Arthritis Care & Research, 55 (4), 616 627. doi: 10.1002/art.22098 Williams, D. M., Anderson, E. S., & Wi n nett, R. A. ( 2005 ). A review of the outcome expectancy construct in physical activity research. Annals of Behavioral Medicine, 29 (1), 70 79. doi: 10.1207/s15324796abm2901_10 Worthington C., & Myers, T. ( 2003 ). Factors underlying anxiety in HIV testing: Risk perceptions, stigma, and the patient provider power dynamic. Qualitative Health Research, 13 (5), 636 655. doi: 10.1177/1049732303013005004
97 Greenland, P. (2004). BMI and health related quality of life in adults 65 years and older. Obesity Research, 12 69 76. doi: 10 .1038/oby.2004.10
98 BIOGRAPHICAL SKETCH Sarah Nolan was born in New York, New York and grew up in the New York suburb of Maplewood, New Jersey. In 2001, Sarah graduated from Columbia High School and moved to North Carolina to pursue a Bachelor of Science in p sychology at Davidson College. In 2005, after graduating from Davidson, Sarah went on to Lynchburg College, in Virginia, to pursue a Master of Education in c ommunity c ounseling. While at Lynchburg, Sarah interned as a counselor at The Alliance for F amilies and Children, a United Way funded organization aimed at serving low income families and children. Additionally, Sarah worked with a team of researchers in the Education D epartment on an intervention project aimed at helping overweight young adult s lose weight and maintain weight loss. After graduating from Lynchburg in 2008, Sarah moved to Gainesville, Florida, to pursue her Doctor of Philosophy in c ounseling p sychology at the University of Florida. She is in her fifth year of the program and he r research interests include health disparities among low income minorities and other marginalized and oppressed groups. Sarah is currently on her pre doctoral internship at the University of Florida Counseling and Wellness Center.