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Novicki, Emily Koby.
Evaluating the get into fitness today (gift) program :
h [electronic resource] /
b weight loss and the roles of education and empowerment
by Emily Koby Novicki.
[Tampa, Fla] :
University of South Florida,
Title from PDF of title page.
Document formatted into pages; contains 177 pages.
(M.A.)--University of South Florida, 2011.
Includes bibliographical references.
Text (Electronic thesis) in PDF format.
ABSTRACT: This study investigated the effects of Get Into Fitness Today (GIFT), a health program for adults that promotes balanced nutrition, physical activity, and weight loss through weekly meetings that provide education and social support. In addition to investigating the effects of GIFT, this evaluation sought to better understand explanatory models used by participants and program staff, and the roles of education and empowerment in weight loss and health education. This mixed methods, case study evaluation consisted of quantitative analysis of existing program records for 664 participants, 40 hours of participant observation of class sessions with ten GIFT groups, and follow-up interviews with 17 participants of three case study groups. Supplementary sources of information included a community health focus group and nearly 1000 goal forms completed by participants. Through analysis and triangulation of the multiple data sources, it was found that participants who complete the program are highly satisfied and have positive outcomes, but only about one-third of participants finish the program. The data suggests that at least some participants stop attending because they do not find the educational material to be novel or the classes to be especially engaging. While both staff and participants share the dominant, individualistic explanatory model of obesity, a new model that is strengths-based, focused on health rather than weight, and aims to empower individuals within structural constraints may be more appropriate.
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Baer, Roberta .
x Health Education
t USF Electronic Theses and Dissertations.
Evaluating the Get Into Fitness Today (GIFT) Program: Weight Loss and the Roles of Education and Empowerment by Emily Koby Novicki A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts Department of Anthropology College of Arts and Sciences University of South Florida Major Professor: Roberta Baer, Ph.D. Rita DeBate, Ph.D. David Himmelgreen, Ph.D. Date of Approval: April 26, 2011 Keywords: obesity, diet, physical activity, medical anthrop ology, public health Copyright 2011, Emily Koby Novicki
Acknowledgments This work would not have been possible without the sup port of many. I would like thank my advisor, Dr. Roberta Baer, for her prompt a nd insightful comments on early drafts and support throughout this long process. My commi ttee members also made vital contributions, and so I would like to thank Dr. Rita D eBate for her valuable guidance on both the technical report and thesis, and Dr. David Hi mmelgreen for bringing in a muchneeded biological anthropological perspective. I am ind ebted to Barbara Roberts and the rest of the staff of the Community Health Division of Hillsborough County Health Department for allowing me to be an unconventional i ntern and providing such a wonderful opportunity. I would also like to thank my parents, Tom and Sheryl Koby, for their support of all my professional and academic endea vors. Special recognition goes to my husband, Brian Novicki, who acted as a daily sounding board, proofreader and wellspring of encouragement, and on many occasions picked u p the slack when there just werenÂ’t enough hours in the day. Above all, I am deeply grateful to the Community Health Advisors who graciously welcomed me into their cla sses and the participants of GIFT, who selflessly shared their stories and forever ch anged the way I think about weight and weight loss. To all of the above, I extend heartfelt thanks.
i Table of Contents List of Tables ..................................... ................................................... .......................... iv List of Figures .................................... ................................................... ........................... v Abstract ........................................... ................................................... ........................... vii Chapter 1: Introduction ........................... ................................................... ...................... 1 Introduction ...................................... ................................................... ................. 1 Program Description ............................... ................................................... .......... 2 Program History ................................... ................................................... ............. 4 Anthropological Issues .............................. ................................................... ........ 6 Research Questions ................................. ................................................... ........ 8 Research Setting ................................... ................................................... ........... 9 Outline ......................................... ................................................... ................... 10 Summary .......................................... ................................................... .............. 12 Chapter 2: Literature Review ...................... ................................................... ................ 13 Introduction ...................................... ................................................... ............... 13 Public Health Model ............................... ................................................... ......... 15 Basic Tenets ...................................... ................................................... 15 Strategies for Weight Loss ........................ ............................................. 16 Ideological Underpinnings ........................ .............................................. 20 Transition within Public Health ................... ............................................. 23 Biocultural Model ................................. ................................................... ........... 23 Biomedical Model................................... ................................................... ......... 27 Critical Anthropology Model ....................... ................................................... ..... 30 Medicalization ................................... ................................................... .. 30 Individualistic .................................. ................................................... ..... 31 Characterization as an Epidemic .................. .......................................... 32 Promotion of Obesity for Monetary Profit ......... ....................................... 33 Stigmatization, Particularly of Women, Minorities a nd the Poor .............. 33 Normalization of Disordered Eating ............... ......................................... 35 Fat Acceptance Model ............................... ................................................... ..... 35 Reactions and Responses to Explanatory Models ........ ..................................... 38 Conclusion ......................................... ................................................... ............. 39 Chapter 3: Methodology ............................ ................................................... ................. 41 Introduction ...................................... ................................................... ............... 41 Research Questions ................................. ................................................... ...... 41 Institutional Review Board ........................ ................................................... ....... 42 Mixed Methods .................................... ................................................... ........... 43 Data Collection ................................... ................................................... ............ 44
ii Quantitative Analysis of Existing Program Records ... ............................. 44 Participant Observation ........................... ............................................... 45 Semi-Structured Interviews........................ ............................................. 46 Supplemental Sources of Information ............... ...................................... 50 Analysis Plan ..................................... ................................................... ............. 50 Quantitative Analysis of Existing Program Records ... ............................. 50 Participant Observation ........................... ............................................... 54 Semi-structured Interviews ........................ ............................................. 54 Supplemental Sources of Information ............... ...................................... 56 Triangulation .................................... ................................................... ............... 56 Conclusion ......................................... ................................................... ............. 57 Chapter 4: Results ................................. ................................................... ..................... 58 Introduction ...................................... ................................................... ............... 58 Quantitative Analysis ............................. ................................................... ......... 58 Population Reached ............................... ................................................ 58 Beginning BMI and Waist Circumference ............. .................................. 59 Attendance ....................................... ................................................... ... 61 Change in Weight ................................ ................................................... 67 Change in Waist Circumference ...................... ....................................... 72 Change in Knowledge ............................. ............................................... 74 Fruit and Vegetable Consumption .................. ........................................ 80 Physical Activity ................................... ................................................... 82 Program Satisfaction ............................. ................................................. 8 6 Other Outcomes ................................... .................................................. 89 Participant Observation ............................ ................................................... ....... 90 Semi-Structured Interviews ........................ ................................................... ..... 95 Background and General Thoughts ................... ..................................... 95 Feedback on Program Elements ...................... ...................................... 98 Changes Made due to Participation ................ ...................................... 105 Friends and Family ............................... ................................................ 10 9 Suggestions for Improving GIFT ................... ........................................ 111 Supplementary Sources of information ............... ............................................. 112 Goal Forms and Weekly Action Plans ............... ................................... 112 Community Health Focus Group ...................... .................................... 116 Conclusion ......................................... ................................................... ........... 118 Chapter 5: Discussion ................................ ................................................... .............. 119 Introduction ...................................... ................................................... ............. 119 Effects of GIFT ................................... ................................................... ........... 119 Weight Change.................................... ................................................. 1 19 Food Diaries .................................... ................................................... .. 120 Other Changes ................................... .................................................. 121 Ripple Effects ................................... ................................................... 122 Satisfaction ..................................... ................................................... ... 123 Meeting (and Failing to Meet) ParticipantsÂ’ Needs .. ......................................... 123 Meeting Needs ................................... .................................................. 123 Failure to Meet Needs ........................... ............................................... 124 Non-Completion .................................. ................................................. 1 25 Explanatory Models ............................... ................................................... ....... 126 Empowerment ...................................... ................................................... ......... 130
iii Further Connections to the Literature ............. .................................................. 131 Implications for Public Health and Anthropology .... .......................................... 132 Limitations....................................... ................................................... .............. 134 Recommendations ................................... ................................................... ..... 135 Recommendations for GIFT .......................... ....................................... 135 Broader Recommendations .......................... ........................................ 137 Conclusion ......................................... ................................................... ........... 139 References ......................................... ................................................... ...................... 140 Appendices ......................................... ................................................... ..................... 152 Appendix A: Florida Department of Health IRB Deter mination ......................... 153 Appendix B: Knowledge Pre-Test ................... ................................................. 1 55 Appendix C: Where Am I? Form ..................... ................................................. 1 56 Appendix D: Commitment and Contract to Change (Curr ent Version) .............. 157 Appendix E: Client Screening Form ................. ................................................ 15 8 Appendix F: Evaluation Form (Current Version) ..... .......................................... 159 Appendix G: Food Diary and Weekly Action Plan...... ....................................... 156 Appendix H: Full Interview Guide ................. ................................................... 161 Appendix I: Abridged Interview Guide ............. ................................................. 1 63 Appendix J: Suggested Weekly Progress Form .......... ..................................... 164 Appendix K: Suggested Revised Evaluation Form ..... ...................................... 166 Appendix L: Suggested Replacement for Week 1 Goal Fo rm........................... 168
iv List of Tables Table 1: Demographic Characteristics of GIFT Participan ts ........................................... 59 Table 2: Key for Knowledge Item Analysis (Figure 13) .................................................. 78 Table 3: FisherÂ’s Exact Tests by Question .............. ................................................... .... 79 Table 4: Percentage of Correct Answers on Preand Post tests .................................... 80
v List of Figures Figure 1: Beginning Body Mass Index (BMI) ........... ................................................... .... 60 Figure 2: Attendance by Week ....................... ................................................... ............ 61 Figure 3: Number of Classes Attended ................. ................................................... ...... 62 Figure 4: Entry into GIFT ......................... ................................................... ................... 63 Figure 5: Percentage of Classes Attended .............. ................................................... ... 64 Figure 6:Entry Point of Participants by Completion S tatus ............................................. 66 Figure 7: Last Week Attended by Non-Completers ..... ................................................... 66 Figure 8: Change in Weight ........................ ................................................... ................ 67 Figure 9: Food Diary Completion by Weight Change St atus .......................................... 70 Figure 10: Food Diary Completion Tertiles and Weight Change Status ......................... 71 Figure 11: Change in Waist Circumference ............. ................................................... ... 73 Figure 12: Knowledge Pretest Results ................ ................................................... ........ 75 Figure 13: Distribution of Knowledge Sum Scores for Pretest ........................................ 76 Figure 14: Distribution of Knowledge Sum Scores for Posttest ...................................... 77 Figure 15: Item Analysis for Knowledge Questionnaire .................................................. 78 Figure 16: Beginning Fruit and Vegetable Consumption as Measured by Pretest .......... 81 Figure 17: Beginning Physical Activity Level as Measured by Pretest ........................... 83 Figure 18: Physical Activity Participation as Measured b y Where Am I? Form............... 84 Figure 19: Beginning Physical Activity Level as Measured by Where Am I? Form ......... 85 Figure 20: Satisfaction with CHAs as Measured by the E valuation Form ....................... 87 Figure 21: Ratings of GIFT Lessons ................... ................................................... ........ 88
vi Figure 22: Feedback on Program Elements ............ ................................................... ... 89 Figure 23: Goals Chosen by Participants ............. ................................................... ..... 113
vii Abstract This study investigated the effects of Get Into Fitness To day (GIFT), a health program for adults that promotes balanced nutrition, physical activity, and weight loss through weekly meetings that provide education and so cial support. In addition to investigating the effects of GIFT, this evaluation sou ght to better understand explanatory models used by participants and program staff, and the roles of education and empowerment in weight loss and health education. This m ixed methods, case study evaluation consisted of quantitative analysis of existing program records for 664 participants, 40 hours of participant observation of cla ss sessions with ten GIFT groups, and follow-up interviews with 17 participants of thre e case study groups. Supplementary sources of information included a community health focus group and nearly 1000 goal forms completed by participants. Through analysis and tri angulation of the multiple data sources, it was found that participants who complete the program are highly satisfied and have positive outcomes, but only about one-third o f participants finish the program. The data suggests that at least some participants stop att ending because they do not find the educational material to be novel or the classe s to be especially engaging. While both staff and participants share the dominant, individ ualistic explanatory model of obesity, a new model that is strengths-based, focused on health rather than weight, and aims to empower individuals within structural constraint s may be more appropriate.
1 Chapter 1: Introduction Introduction It widely acknowledged that an unprecedented proporti on of the population of the United States is overweight and obese (Flegal, et al. 2010). The Â“obesity epidemicÂ”, as this phenomenon is referred to in both the popular a nd academic press, has evoked a range of responses among public health professionals, jou rnalists, medical professionals and lay people, ranging from Â“sin taxesÂ” on sugary bev erages and snack foods to the size acceptance movement (Brownell and Frieden 2009; Gi lman 2008; Moffat 2010; Saguy and Riley 2005). This project focused on explorin g the effects of Get Into Fitness Today (GIFT), a program run by Hillsborough County H ealth Department (HCHD) that promotes balanced nutrition, fitness and weight loss amo ng adults. This study was conducted using an anthropological perspective, since many aspects of obesity and weight loss are inextricably linked to culture Â– food p references and social customs, body size preferences, explanatory models of obesity, a mong others. The anthropological perspective provides valuable insights in to how obesity is constructed as both a medical and social problem, and the best strateg ies for programs like GIFT to use in order to help participants become healthier. GIFT aims to improve behaviors related to overweight and obesity, which in turn is related to a host of health problems. Obesity result s from a caloric imbalance in which too many calories are consumed through food and not eno ugh are burned through physical exertion, leading to surplus in calories that r esults in weight gain (Centers for Disease Control and Prevention 2009b). Overweight ind ividuals are at an increased risk
2 for type II diabetes, coronary heart disease, some types of cancers, hypertension, stroke, osteoarthritis, liver and gallbladder disease, sleep apnea, and respiratory problems, among others (Centers for Disease Control an d Prevention 2009c). Further, excess weight is associated with knee, hip and back pain (An dersen, et al. 2003; Shiri, et al. 2009). The prevalence of obesity has more than doubled since th e 1960s, but has appeared to leveled off in 2003-2004 (National Cent er for Health Statistics 2010). Despite this, the prevalence of obesity in Hillsborough County is 24.8%, well above the Healthy People 2010 goal of 15% (Florida CHARTS 200 7; U.S. Department of Health and Human Services 2000). Another 39.4% of adults are overweight; almost two-thirds of all adults in the county are either overweight or obese. GIFT seeks to help adults in Hillsborough County attain a healthy weight through increased knowledge of BMI, increased fruit and vegetable consumption and increased p hysical activity in order to prevent chronic diseases associated with overweight and o besity, namely type II diabetes. According to the 2007 Behavioral Risk Factor S urveillance Survey data, only 26.1% of adults in Hillsborough County eat five serv ings of fruits and vegetables daily, 27.4% engage in no leisure-time physical activity and on ly 33.7% met moderate physical activity recommendations (Florida CHARTS 2007). Program Description GIFT classes meet weekly for one hour at workplaces, commu nity centers, libraries, churches, coffee shops and private homes. A tra ined Community Health Advisor (CHA) leads each group; some are paid employee s, but others are volunteers. Each class consists of three twenty-minute segments: a lesson on a health topic, social support, and exercise. The lessons cover new topic each week regarding fitness, nutrition, or diabetes prevention and teach skills li ke reading food labels and controlling
3 portions. During the social support portion of the class, participants share information, ideas and encouragement. In addition to setting overal l goals for the six weeks, participants also set a smaller, more specific goal for each week. Progress (or lack thereof) towards weekly goals is discussed among participa nts, and goals for the coming week are shared (to increase accountability). The final portion of the class is a physical activity chosen by the CHA, taking into account limitat ions of the physical space and the abilities of participants. Activities vary greatly; exa mples include taking a group walk, stretching, doing a workout DVD and learning strength and flexibility moves. Goal setting is an important aspect of the program. In Week 1 participants set medium-term goals (usually the six weeks of the program session) for themselves using a checklist of possible goals on a form called the Commit ment and Contract to Change. Some flexibility is built in to the goal setting, how ever, as the Â“otherÂ” option allows participants to write in their own goal. They are al so encouraged to set a reward for themselves for meeting their goals (a Â“positive rewardÂ” ) and some kind of punishment if they do not (a Â“negative rewardÂ”). Each week (includ ing Week 1), participants create an action plan, which is essentially a short-term goal settin g exercise. In their action plan, participants write out what their small goal is for e ach week (such as eating an additional vegetable daily or only drinking more water), why t hey have this goal, when they will accomplish it, what impediments they face, and how the y will overcome those impediments. Participants are also highly encouraged to keep a food diary on a form provided by the program. The form includes spaces to mark of the number of fruits and vegetables eaten, glasses of water imbibed and minutes of physical activity completed, in addition to space to write out foods eaten for brea kfast, lunch and dinner. Participants weigh in each week, but their weight is not publicly a nnounced. Rather, it is recorded on their food diary, which is then submitted by CHAs to HC HD for monitoring purposes. If
4 groups are particularly passionate, they can continue bey ond the six weeks and move into an extended 24-week curriculum. New CHAs are often recruited from among successful participants. Program History The program originates with a community health assessme nt conducted in 20062007 that found, in line with epidemiological statist ics, the general public perceived overweight and obesity to be the largest health probl em facing their community. However, the survey data also revealed what staff calle d Â“a disconnectÂ” between what the public viewed as the most pressing health problems an d what they perceived as the riskiest behaviors. In other words, people felt that o besity was an imminent problem, but did not cite sedentary lifestyles and poor diet as most i mportant risk behaviors to address (Hillsborough County Health Department 2006-20 07). Using this information, the leadership at HCHD decided that an education progr am was necessary in order to both reduce obesity (and therefore chronic diseases) and address this disconnect between cause and consequence. Originally they envisioned a community-based initiat ive called Â“Neighborhood by NeighborhoodÂ” in which health department staff would train interested individuals, who would then pass along the information through their social networks. The inspiration came from a recent program in conjunction with beauty sa lons and barbershops in which barbers and stylists would distribute educational cards about stroke and heart disease to their clients. During this same time period, HCHD subm itted an unsuccessful grant proposal for a weight loss program for African-American and Hispanic women ages 1836 called Â“Fit and FabulousÂ” that utilized the Transth eoretical Model and social support. Feeling both program concepts had merit, they pulled e lements from both to create
5 GIFT. They soon decided on the basics of the program: a focus on nutrition and physical activity, a lesson each week and a personal log. They also decided to recruit lay health advisors, who they called Â“Community Health AdvisorsÂ” (CHAs) and received a grant from the Office of Minority Health for their training. They originally envisioned 20 CHAs, but qui ckly realized that it was extremely difficult to find individuals in each neighborhood th at were willing to teach the classes without compensation. Changing tactics, they decided to allocate general funds to the program and hire five ethnically and linguistically di verse CHAs to teach the classes. In the beginning, CHAs were responsible for finding a site and recruiting participants in addition to teaching the classes. At first they focused o n specific zip codes deemed most at need, but have since expanded eligibility to all r esidents of Hillsborough County. Participants also used to receive incentives like gift car ds, visors, and water bottles for participating, but now that the program is well estab lished, they no longer spend money on incentives and spend very little on advertising. The program director feels that word of mouth generated by the success of their participants h as become their advertising (Cindy Hardy, Personal communication, 7/30/10). Today, most participants come from one of two sources: workplace wellness initiatives and doctor referrals. HCHD has had considerab le success marketing GIFT among employers, since there is no cost to employers (aside from printing the program materials) and employees can participate during their lunch hour or immediately before or after work (thus maintaining productivity). Emplo yees are asked to volunteer to receive training and teach the weekly classes to their co -workers. Doctor referrals are the other main source of participants. HCHD developed their own referral pad after learning that scholarly literature indicates that pati ents are more likely to follow-up on a referral if they are given an official piece of paper They have forged partnerships with doctors in the Tampa Bay area and regularly receive r eferrals from several practices.
6 When a patient is referred, a HCHD staff member calls h im or her, explains the program and invites them to join a GIFT group. It should be n oted that participants also learn of the program through word-of-mouth and a radio comme rcial aired on a station popular among African-Americans. Other aspects of the program have also undergone chang es over time. The program began with six lessons, but eventually expanded to 24 weeks worth of lessons (approximately six months). The educational materials h ave been improved over time through feedback of participants and CHAs, but the dire ctor feels that the lessons are now Â“finishedÂ” and they have moved beyond asking part icipants Â“What do you need?Â” (Cindy Hardy, Personal communication, 7/30/10). The p rogram has also moved away from a more open-door policy of encouraging participan ts to bring friends and family. Feeling that the classes were being treated as Â“social h ourÂ” rather than a serious commitment and that the extra participants were dilut ing their aggregate results, the leadership at HCDH has enacted a strict Â“no visitorsÂ” pol icy. Anthropological Issues Obesity has captured the attention of journalists, academ ic researchers, public health professionals, industry executives, and lay people alike. Various groups United States simultaneously view the obesity phenomenon as a medical, social, political and moral problem. In such a contested space, the need for a n anthropological approach is clear, in order to ensure that the program is sensitive to the needs and perspectives of its participants in order to be the most effective. S ince there are several explanatory models of obesity currently in use, it is critical to det ermine whether the explanatory model underlying the program corresponds with the mod el (or models) used by participants. Kleinman (1978) first introduced explanatory models as a way to describe the very different ways in which doctors and patients co nceptualize the acquisition and
7 treatment of diseases, but the crux of his idea is broad ly applicable to interactions between the public and health care professionals of many stripes. These concepts will be more fully explored in the next chapter. Anthropology also has much to contribute to evaluation, thanks to it emphasis on local, contextual knowledge. In fact, evaluation anthr opology is considered an emerging subfield of applied anthropology (Butler 2005; Copel and-Carson 2005). Often evaluations are simple preand post-tests designed to uncover whether a program has achieved specific, narrow, pre-determined objectives. Whi le preand post-tests certainly have a role in evaluation, the ethnographic, qualita tive approach of anthropology provide a more comprehensive, nuanced view of program effects of than can be detected through preand posttests alone (Britan 1978; Patton 2005). Case studies, a technique used in this study, are highlighted as a particularly g ood way to apply anthropological methods to evaluation (Butler 2005). Participant ob servation, direct observation, and semi-structured interviews were also utilized in this p roject to achieve a more nuanced understanding of the achievements of GIFT and its oppor tunities for improvement. In additional to enriching evaluation methodological ly, anthropology has made several important conceptual contributions. One is the id ea of Â“comparative study of how people evaluate that is, the ways of knowing, being and valuing ex hibited by different societies and cultures overallÂ” (emphasis original) (Cope land-Carson 2005: 8). Others have also praised anthropologyÂ’s sensitivity to values, b ringing attention to both the values of diverse stakeholders and values held by evaluat ors that underpin scientific endeavors (Butler 2005; Patton 2005). Finally, evalua tion has also been positively impacted by anthropologyÂ’s reflections and debates about representation within writings and presentations, since evaluators too have difficulty representing multiple and sometimes divergent perspectives among stakeholders (Patton 2005). As Patton (2005: 37) explains, Â“AnthropologyÂ’s insistence on being clear a bout whose perspective is being
8 presented has influenced evaluationÂ’s struggle with thi s complex methodological, analytical, reporting, political and values-laden chal lenge.Â” Research Questions The following research questions guided the research proce ss: 1. What are the effects of the program? 2. In what ways does the program meet (or fail to mee t) the needs of the intended audience? 3. How does the conceptual model of weight loss employed by the program correspond to the conceptual model used by participants? W hat implications does this have for the program? 4. What are the roles of education and advocacy within the program? Instead of taking the traditional route of testing f or specific hypotheses, I have taken what is known as a goal-free approach (McKenzie an d Smeltzer 2001; Patton 1979; Scriven 1991). Rather than entering the study with specific, preconceived objectives the program should accomplish, a goal-free ap proach instead searches for all program effects (McKenzie and Smeltzer 2001; Scriven 1991). This approach was chosen to avoid overlooking positive program effects or a reas in need of improvement due to overly narrow criteria for program success. This w as particularly appropriate in this instance, as the program manager only tracks five variables for quarterly reports to the state: 1) number of GIFT groups, 2) number of pa rticipants, 3) total pounds lost, 4) number of participants with self-reported increase in f ruit and vegetable consumption and 5) number of participants with self-reported increa se in physical activity. In the absence of specific objectives or targets for the program, a goal-free approach is highly appropriate.
9 Research Setting This research was conducted through an internship with Hi llsborough County Health Department (HCHD) from July-December 2010. HCH D is a state agency operating under the Florida Department of Health in partnership with the county government whose mission is to Â“promote, protect, and i mprove the health of all people of FloridaÂ” (Hilsborough County Health Department 20 10). To this end, the HCHD provides a wide range of clinical services, conducts epidem iological surveillance, and monitors environmental health hazards, among other se rvices and supports. Rather than one central office, the agency is broken up among severa l offices located in various parts of the county. My internship with the Community Health Division took place at their offices just outside of Ybor City and later in Spring Hill, both in Tampa. Although I was occasionally asked to help with GIFT activities, I was gi ven a great deal of autonomy in my internship. I spent the vast majority of my time in dependently working on evaluation activities, but being in the thick of the programÂ’s d ay to day operations was illuminating. Over the course of my internship I also had several opp ortunities to interact directly with ten different GIFT groups. As part of a larger workplace wellness initiative, a white-collar service agency created a GIFT group for each lunch period in all seven of its branches, and I was asked to assist with the beginning and ending measurements (weight, BMI waist size, body fat percentage) at three branches (a total of 7 groups). This took me from urban areas of Hillsborough County in Tampa to more rural areas in the perimeter of the county. One of these seven groups allowed me to observe every session and served as one of my case study GIFT groups. Th is group, which I will henceforth refer to as the Â“workplace groupÂ”, was locate d at in an office building in downtown Tampa. I also the opportunity to observe wha t the program staff refer to as Â“community groupsÂ”: a group that met at a community cen ter (which I will call the Â“community center groupÂ”) and another that took place a t a public library (the Â“library
10 groupÂ”), both in low-income neighborhoods. While all classes took place in wellappointed conference rooms, the workplace group was compo sed of ethnically diverse and well-educated white collar workers taking part in a workplace wellness initiative, while the community center and library groups were alm ost entirely African-American and Hispanic women with varying levels of education who were referred to the program by their doctors. The participants of these various groups do not make up one community, in fact quite the contrary. The program seeks to serve all of Hi llsborough County, a diverse, large, and populous geographic area. The variety in t he research setting regard to both socio-economic status and geography is thus appropriate a nd can even be seen as a strength of the research. Outline The next chapter will provide an overview of literatu re regarding obesity. Several social scientists have noted that obesity is a contested space in which various entities are engaged in Â“framing warsÂ”. This chapter will expa nd upon their work and describe five explanatory models seen in the literature and po pular press that provide different perspectives on the causes and solutions of obesity. The fi ve models include the dominant public health model, biocultural model, biom edical model, critical anthropological model and fat acceptance model. The wa ys in which women individuals adopt, transform, combine or reject models will be inv estigated. Chapter 3 describes the methodology used in this stud y in detail. A pragmatic, mixed-methods approach was taken to capitalize on exi sting program records while also expanding knowledge of participantsÂ’ perspectives on an d experiences with the program. Three main methods were used in this study: q uantitative analysis of existing program records, participant observation of three case s tudy GIFT groups, and semi-
11 structured follow-up interviews with participants. Thi s chapter will describe in detail how the research was carried out, including sampling and recr uitment strategies, data management and the analysis plan. Also included are the research context and research questions. Chapter 4 presents the results from the analysis of the data collected for this study, organized according to methodology and theme. T his includes quantitative analysis of a database of 664 participants on weight cha nge, waist circumference change, food diary completion, attendance, change in kn owledge, fruit and vegetable consumption, physical activity and participant satisfaction. Also covered are themes emerging from the 40 hours of participant observation about CHAs, explanatory models and challenges faced by participants. The results from the 17 semi-structured interviews are also discussed, including history of dieting, feedback on elements of the program, changes made due to participating in the program and suggestions for improving GIFT. Finally, the analysis of supplemental sources of inform ation, namely the goal forms, is presented. Chapter 5 offers a synthesis of the findings and makes connections to the literature discussed in Chapter 2, organized by research question. First the effects of GIFT are outlined, followed by a discussion of how the program meets and fails to meet participants needs. The explanatory models used by the program staff and participants are articulated, and finally roles of empowerment and education are explored. This chapter also includes implications for both public health and anthropology. It concludes with recommendations specifically for GIFT and broader recommendations for health promotion efforts regarding obesity.
12 Summary This chapter has provided a broad overview of this stu dy, including the setting and population. A description of the program was prov ided, along with an account of the development and evolution of GIFT. The anthropologi cal aspects of this work were detailed, a topic which will be more fully explored i n the discussion. Finally, a brief summary of the research approach, methodology and resear ch questions were provided. Subsequent chapters will cover in greater de tail the scientific literature informing this study, and its methodology and results. The final chapter will include a discussion of the findings, their implications and recommen dations for future health promotion programs.
13 Chapter 2: Literature Review Introduction On the surface, obesity seems like a rather cut and dry medical issue, a condition created by a caloric imbalance in which too many calorie s are consumed through food and not enough are burned through physical exertion, leading to surplus in calories that results in weight gain (Centers for Disease Control an d Prevention 2009b). According to recent estimates, 32.2% of adult men and 35.5% of wom en in the United States are obese, but prevalence rates appear to have leveled off after rising significantly during the 1980s and 1990s (Flegal, et al. 2010). Predictions are dire: one projection found that all American adults will be obese by 2048 and another foun d that life expectancy may decline for the first time in two centuries because of o besity (Flegal, et al. 2010; Olshansky, et al. 2005). However, a closer examination of scientific and popular literature shows that obesity is conceptualized in several different ways amon g academics and lay people alike. This study has thus adapted Kleinman et al (197 8)Â’s assertion that doctors and patients can have very different explanatory models of disease; in order to achieve the best health outcomes doctors and patients must together negotiate a shared model. As Chaufan (2004:260) explains, Â“Explanatory frameworks matter because societies shape their public policies and decide the use of their resource s depending on what they see as the source and cause of their problems.Â” Kwan (2009) e choes this sentiment and adds that because frameworks prescribe solutions, they have the power to either reduce or exacerbate social inequalities.
14 In the case of GIFT, the program may utilize one expl anatory model, while participants may use one or more alternative models. I f there is conflict between the models, the program may need to change in order to ach ieve a shared model acceptable to both program staff and participants. The explanatory models used by participants may very well be different, since weight loss efforts are complex, unique and individual in nature (Adams 2008). Further, women ar e not a homogenous group and accept, reinforce and resist societal pressures regarding w eight in different ways (Germov and Williams 1999). Other researchers studying the social construction of obe sity have also investigated explanatory models. One such example comes from Sobal (1995), who takes a historical approach. He argues that first a mor al model was used in which individuals were blamed for their weight and punished as a mechanism of social control, but this was replaced by a medical model in the postwar era in which obesity became a disease. More recently, the fat acceptance movement has so ught to demedicalize obesity and bring attention to fat discrimination and body acceptance, leading to a political discrimination model. Although Sobal presents them as sequential, he acknowledges that all three still operate today. A seco nd classification system comes from, Stinson (2001)Â’s ethnography of a weight loss pr ogram that bears striking resemblance to GIFT. She found five explanatory frame works simultaneously at work: 1) self-help, in which lifestyle changes result in improved health and weight loss, 2) work, in which the body is seen as a malleable substance that can be molded through discipline and hard work, 3) religion, in which religious langua ge of temptation, sin, guilt and sacrifice is prominent, 4) addiction, as exemplified by OvereaterÂ’s Anonymous, and 5) feminism, which is often faint and co-opted. In practice, however, the frames of religion, addiction and feminism are often translated into the l anguage of self-help and work, which most closely fit dominant cultural values.
15 Saguy and Riley (2005) take a very different approa ch. They argue that four groups (antiobesity researchers, antiobesity activists, fat acceptance researchers, and fat acceptance activists) are currently engaged in Â“frami ng contestsÂ” over the causes and consequences of obesity. Finally, Kwan (2009) explo res three cultural frames regarding obesity: a medical frame (represented by the CDC), social justice frame (represented by the National Association to Advance Fat Acceptance or NAAFA), and market choice frame (represented by the Center for Con sumer Freedom). These previous works informed this study to varying degrees, but ultimately I developed a unique set of explanatory models in the literature re garding obesity. Five models have been identified and will be explored: the dominant public health model, a biocultural anthropological model, a biomedical model, a critical a nthropological model, and the fat acceptance model. Finally, the ways in which individuals adopt, transform, combine or reject models will be investigated. Public Health Model Basic Tenets The public health model is the dominant explanatory m odel used in the United States by professionals and lay people alike. The majo r tenant of this model is that being overweight is unhealthy (Stinson 2001). As discussed in Chapter 1, overweight individuals are at an increased risk for type II diabet es, coronary heart disease, some types of cancers, hypertension, stroke, osteoarthritis, l iver and gallbladder disease, sleep apnea, and respiratory problems, among others (Ce nters for Disease Control and Prevention 2009c). Further, excess weight is associated w ith knee, hip and back pain (Andersen, et al. 2003; Shiri, et al. 2009). It is du e to these health issues, and the high prevalence of overweight and obesity described above t hat obesity is seen as a major health problem, an epidemic even, in both scientific a nd news media publications (Office
16 of the Surgeon General 2001; Saguy and Almeling 200 8). There is a serious sense of urgency felt among public health professionals to take a ction regarding the most serious health issue facing the nation (Saguy and Almeling 200 8; Saguy and Riley 2005). The determination of overweight and obesity, and the refore who needs help, is generally made using body mass index (BMI). BMI is a he ight-to-weight ratio based on age and sex that provides a rough indicator of body fa t percentage (Centers for Disease Control and Prevention 2009a). For most adults, a BM I of 18.5 to 24.9 is considered a healthy weight, 25.0 to 29.9 is overweight, and anyt hing above 30.0 is considered obese (Centers for Disease Control and Prevention 2009a). O verweight and obese individuals are highly encouraged to reach a BMI in the healthy r ange (18.5-24.9) in order to reduce their risk for chronic diseases (Centers for Disease Con trol and Prevention 2009c). Weight loss is promoted in order to improve health, n ot to improve appearance or conform with the societal preference for thinness (Kwan 2 009). Recent literature suggests, however, that overweight p eople do not need to achieve a BMI under 25 in order to experience health benefits. Indeed, one popular standard within public health for Â“successfulÂ” weight lo ss is losing of initial body weight and maintaining that loss for at least one year (Win g and Hill 2001; Wing and Phelan 2005). Modest weight loss of 5-10% of initial body we ight can help prevent hypertension and type II diabetes, and may improve lipid, glucose a nd blood pressure levels (Blackburn 1995; Goldstein 1992b; Oster, et al. 1999 ; Vidal 2002b). Whether overweight and obese individuals should aim for a 10% weight loss or a BMI under 25 has not been entirely resolved in this model. Strategies for Weight Loss The dominant public health paradigm posits that obesity is caused by caloric overconsumption and insufficient physical activity, and t herefore, individuals must
17 overcome their condition through a combination of diet and exercise. Although weight loss can also be achieved through drugs or surgery, for mo st people it requires a Â“lifestyle changeÂ” (McKinley 1999). This lifestyle chan ge is presented as a permanent modification of eating and activity levels, in contrast with time-limited dieting (Stinson 2001). The Centers for Disease Control and Prevention (CDC) recommend that individuals use the food pyramids (which are tailored f or age, sex and activity level) as an aid in attaining Â“caloric balanceÂ”; increased consumpti on of fruits and vegetables is heavily encouraged (Centers for Disease Control and Pr evention 2011b; Centers for Disease Control and Prevention 2011d; United States De partment of Agriculture 2011). Regarding physical activity, the CDC recommends that peo ple ages 18-64 engage in 150 minutes of moderate physical activity or 75 minutes of vigorous physical activity weekly, plus muscle-strengthening activities two or mor e days per week (Centers for Disease Control and Prevention 2010). Weight loss shoul d occur slowly, with 1-2 pounds per week considered optimal (Centers for Disease Control and Prevention 2011e). Education also play a critical role in reducing obesity since it is perceived that many simply do not know how to eat more healthfully or are aware of the importance of exercise (Austin 1999; Saguy and Riley 2005; Stinson 20 01). The idea is that once people have the necessary knowledge, they can make wise r choices and replace bad habits with good ones (Stinson 2001). Strategizing ab out the smartest choices is thus an important tool for weight loss (Stinson 2001). Despite evidence that theory-based behavior change programs are more successful than knowle dge-based programs, education remains to be perceived as an indispensible com ponent of weight loss (Cullen, et al. 2001). Along with education, a number of tools and aids for weight loss are promoted in conjunction with the Â“eat less, exercise moreÂ” mantra by the CDC and are utilized in
18 GIFT. The first is finding social support, often accompli shed through joining a group of others who are also trying to lose weight. The popula rity of support groups is tied to the broader self-help movement, which is in turn fueled by values of individualism and selfimprovement (Stinson 2001). Support groups are characte rized by the lack of a professional leader or facilitator; participation costs l ittle or nothing (Davison and Pennebaker 2000). According to Stinson (2001) support group benefits are t hreefold. First, they provide a sense of community and the kind of psychologi cal and emotional support that individuals do not receive in their current relationshi ps. Second, through improved coping strategies and receipt of positive reinforcement, individuals may experience increased self-esteem. Finally, they are a potential si te for social change. Although most support groups operate on an individual level, some h ave become more involved in the broader political and social issues facing their group (St inson 2001). Regarding the efficacy of support groups, Davison and Pennebaker (2000 ) provide a simple metric: participation. They point out that, Â“Groups without value cease to be groups. Members vote with their feetÂ” (Davison and Pennebaker 2000: 206). High turnover and large membership can diminish the effectiveness of support grou ps, since it takes time for participants to become familiar with each other and fe el comfortable sharing (Stinson 2001). Competitive feelings among participants can al so impede their effectiveness, this is particularly true for women and weight loss (Stinson 2001). The second strategy, recording food intake in a Â“food diaryÂ”, is also encouraged by the CDC as a weight loss aid (Centers for Disease Cont rol and Prevention 2011c). The idea behind food diaries that all food intake mu st be recorded in detail in order to promote awareness of eating habits (and thereby avoid Â“mindless eatingÂ”) and improve self-efficacy (Centers for Disease Control and Preventio n 2011c; Mossavar-Rahmani, et al. 2004; Stinson 2001). Many studies have shown that f ood diaries promote weight loss
19 across a number of paper and digital formats, although the quality of self-monitoring may impact weight loss success (Baker and Kirschenbaum 1993; Bou telle, et al. 1999; Boutelle and Kirschenbaum 1998; Guare, et al. 1989; H elsel, et al. 2007; Kruger, et al. 2006; Yon, et al. 2007). A high level of detail an d completeness is seen by some as critical, while other studies suggest it is the process of se lf-monitoring, rather than the level of detail, that is important because accuracy of se lf-monitoring is often poor (Baker and Kirschenbaum 1993; Goris, et al. 2000; Helsel, et a l. 2007; Shay, et al. 2009). The third strategy, goal setting, is widespread despit e limited evidence on effectiveness (Cullen, et al. 2001; Shilts, et al. 200 4). Most research on goal setting has been conducted in workplace and sports settings, where r esearchers have found that goals that are specific, proximate (short-term), and di fficult yet achievable are the most effective (Shilts, et al. 2004). Feedback (knowledge of oneÂ’s progress) and rewards are also critical components (Shilts, et al. 2004). However, reviews of goal setting in dietary and physical activity behavior change studies found that there is insufficient evidence to determine if these findings hold true for health beh aviors (Cullen, et al. 2001; Shilts, et al. 2004). The authors of both reviews do conclude tha t there is sufficient evidence to recommend using goal setting as part of behavior chang e programs, even though the most effective goal setting strategies for health beha viors are unknown (Cullen, et al. 2001; Shilts, et al. 2004). A final common strategy for weight loss is self-weighing usually weekly, in order to reinforce incremental progress and drawing attentio n to weight. This technique is less commonly utilized, however, and it not currently endo rsed by the CDC (Centers for Disease Control and Prevention 2011c; Linde, et al. 20 05).There has been some concern raised about negative psychological ramifications, namely reduced body satisfaction (Welsh, et al. 2009). However, the evide nce suggests that a weekly weigh-in
20 is a beneficial practice that promotes greater weight lo ss without psychological harm (Linde, et al. 2005; O'Neil and Brown 2005; VanWorm er, et al. 2009; Welsh, et al. 2009). Ideological Underpinnings Even though the path to weight loss is made clear in th is model, accumulated scientific evidence shows that most diets fail. Studies show that between 75-95% are unable to maintain their weight loss (Garner and Wool ey 1991; Goodrick and Foreyt 1991; Kramer, et al. 1989; National Heart 1998; Stu nkard and McClaren-Hume 1959; Wing and Phelan 2005). This is often interpreted by public health professionals and the public at large as evidence that people are not truly committed to lifestyle changes rather than a flaw in the Â“eat less, exercise moreÂ” approach ( Saguy and Riley 2005; Stinson 2001). One example of this is a fact sheet produced by the Office of the Surgeon General that advises people to Â“Make fitness a priorit yÂ….COMMIT TO ITÂ” (emphasis original) (Office of the Surgeon General 2007). This model is overwhelmingly individualistic (Honeycutt 1999; McKinley 1999; Ritenbaugh 1982; Sobal 1999; Stinson 2001). This is bo rn out in the language used. Obesity is seen as risk factor for a number of secondary diseases rather than a state of being or a disease in and of itself. Risk factors are caused by individual choices and behavior, making obesity similar in this respect to smok ing (Saguy and Riley 2005; Stinson 2001). Â“Like cigarette smokers who contract cancer obese persons are assumed to have gotten what they asked forÂ” (Stinson 20 01: 176). Ultimately blame is placed squarely on the obese individual for any and a ll ill health (Kwan 2009). In addition to the focus on the individual, this model also has moralistic overtones. Excess body weight has traditionally been see n in moral terms as an indicator of sloth and gluttony (Saguy and Almeling 2 008). Overweight and obese people are viewed as being unable to control their desires, wh ich is ultimately a moral failure
21 (McKinley 1999; Sobal 1999). Food itself is moralized and divided into Â“goodÂ” and Â“badÂ”, sacred and profane (Stinson 2001). Some have even argu ed that the pursuit of health has become a moral end in itself (Saguy and Almeling 2 008). It is therefore not surprising that religious language is also used by diete rs as a metaphor to describe their experiences, with guilt, sacrifice and temptation frequ ently surfacing as themes (Stinson 2001). The fundamental tenants of this model stem from prom inent underlying cultural values (Austin 1999; de Vries 2007; Stinson 2001). For example, the belief that weight loss requires dedication and hard work stems from the cul tural value of a self-made person and a strong (Protestant) work ethic (de Vries 20 07; Stinson 2001). Further, in the United States the body is seen as a material object that can be Â“molded into the desired size and shape, if you only spend enough time, use the right tools, apply the correct techniques, and work at it hard enoughÂ” (Stinso n 2001: 52-53). Emphasis on willpower reflects the Western tendency to separate min d from body. The body is Â“instinct, physical urges, drives and troublesome emotion s that continually threaten to run amokÂ”, and must be tamed by the rational mind (G ilman 2008; Stinson 2001: 169). The use of weight and BMI to as the marker of a Â“good bodyÂ” comes from a high level of rationalization; Americans are Â“enamored of quantifica tion and calculabilityÂ” (Austin 1999; Stinson 2001: 117). It is through the rationali zation of the body that ideal universal weight ranges are constructed and the relationship bet ween weight and health is measured and quantified. Finally, part of the appeal of dieting comes from a powerful cultural narrative Stinson calls the Â“before-and-after storyÂ”, in which an deficient protagonist overcomes challenges through willpower, wor k and determination and emerges from his or her trials as a triumphant and im proved person (Stinson 2001: 195). In practice, this construction of obesity is strongly negat ive. In addition to being viewed as indulgent, overweight and obese people are perceived as lazy, unattractive,
22 unsuccessful, less competent and lacking in self-control or willpower (Germov and Williams 1999; Kolata 2007; Maddox, et al. 1968; McKi nley 1999; Stinson 2001). Because of these biases, overweight individuals face consid erable stigma. In their comprehensive review of the literature regarding stig ma and obesity, Puhl and Heuer (2009) found inequities in workplaces, educational inst itutions and healthcare settings due to weight bias. Additionally stigmatization is pe rvasive in the media and is even found in close personal relationships (romantic partners, family members and friends). The authors point out that weight bias has increased su bstantially over the past decade, is rarely challenged in Western society, and results in de creased quality of life for overweight and obese individuals. For their part, pub lic health professionals see it as their duty to raise awareness about the consequences of ob esity, even if that means exacerbating stigma (Saguy and Riley 2005). One such pu blic health researcher is quoted in an interview as saying, Â“We donÂ’t want to h ave discrimination, but I think that canÂ’t possibly be used as an excuse to censor information ab out theÂ…cold reality of excessive overweightÂ” (Saguy and Riley 2005: 885-886). Stigmatization is even seen by some public health professionals as a justifiable way to motivate individuals to adopt healthier behaviors (Puhl and Heuer 2010). Despite the pervasive nature of this model, Moffat (2 010) points out that public health experts are not worried about panic and alar mism but rather apathy among the public. They are concerned that obesity has become Â“norma lizedÂ”; larger body sizes have become so prevalent that we, as a society, have for gotten what normal bodies look like. Â“Thus, the normal range of variation, or bell curve, has been skewed to the right, and with this shift there has been a decline in our abi lity to recognize obesityÂ” (Moffat 2010: 9). Further evidence of this concern is seen in a recent study which found that both men and women are less likely to self-classify as ov erweight on the most recent National Health and Nutrition Examination Survey (NH ANES) than the one prior, which
23 the authors interpreted as evidence of a Â“generationa l shiftÂ” towards larger body weight norms (Burke, et al. 2010). Transition within Public Health It should be noted that while there is a great deal of emphasis on awareness and personal responsibility in the public health model, the re is an increasing recognition within public health of structural and environmental issues that contribute to obesity. These factors include: increased portion sizes in restauran ts; widespread advertising of convenience foods; a lack of sidewalks, bike lanes and po or street connectivity; the greater expense of fresh produce compared to processed foo ds; and Â“food desertsÂ” (areas where only those with the means to pay for pr ivate or public transportation can access the inexpensive and varied food found at supermark ets) (Cardello 2009; Cummins and MacIntyre 2006; Saelens, et al. 2003; Ulij aszek 2007; White 2007; Wrigley 2002). Environmental and community-based inte rventions such as community gardens are increasingly being implemented (Economos an d Irish-Hauser 2007). Still, individual failures (i.e. sedentary leisure activities and poor dietary choices) are popularly seen as the biggest contributors to obesity (Boyce 2007 ; Henderson and Kelley 2005; Pereira 2006; Saguy and Riley 2005; U.S. Department of Labor 2008). Biocultural Model The second model is the biocultural anthropological v iew. It points out that humans have an evolutionary preference for energy den se foods, namely those that contain large quantities of fat and/or sugar (Maziak, e t al. 2008; Ulijasek and Lofink 2006). Up until very recently, extra adipose tissue was considered desirable, since it provided a source of energy during times of scarcity and famine. Further, female fertility is linked to body fat, making sufficient stores energy (in the form of adipose tissue) a
24 reproductive advantage. Now that food is more plenti ful, inexpensive and aggressively marketed than ever before, this preference is deleteri ous (Gilman 2008; Ulijasek and Lofink 2006). Or as Cardello (2009: 144) succinctly descri bes the situation, there is Â“too much high-calorie food thatÂ’s marketed too effectively to too many who canÂ’t resist.Â” This dietary shift towards increased consumption of energy-de nse food and decreased physical activity is sometimes described a nutrition transit ion (Ulijasek and Lofink 2006). However, despite these clear shifts, Â“how food use is str uctured socially and culturally has been slow to adjust to changing patterns of food secu rity, as have perceptions of appropriate body size for health and beauty, which h as contributed to the emergence of obesity in various societiesÂ” (Ulijasek and Lofink 2006: 3 39). There are many social, cultural and environmental fact ors that contribute to the current Â“obesogenic environmentÂ”. Reasons for decreased p hysical activity include: the separation of housing and retail areas in communities, which discourages walking; use of automobiles as the primary mode of transportation; fewer jobs that require heavy labor and more sedentary service sector and technology occu pations; and the popularity of television, video games and the internet as leisure activities (Boyce 2007; French, et al. 2001; Ulijasek and Lofink 2006). Factors related to diet include: consumption of sugar-sweetened beverages like soft drinks and food jui ces; consumption of caloriedense micronutrient poor food such as fast food and many snack foods; larger portion sizes; more snacking and fewer structured meals; increa sed time constraints and the resulting reliance on convenience food; affordability and access to healthy food; and food deserts (Brown, et al. 2007; Daggett and Rigdon 2006; Nielson and Popkin 2003; Pereira 2006; Prentice and Jebb 2003; Ulijasek and Lofi nk 2006). Many of these factors are beginning to be acknowledged in the public healt h model; the difference is that the public health model tends to promote individual solut ions while the biocultural model
25 takes a multi-level approach that alters the environm ent in order to trigger individual behavior changes. The biocultural model also acknowledges that ideal body size varies across populations in terms of both aesthetics and health. It is well documented that ideal body shape and size varies considerably cross-culturally (Demar est and Allan 2000; Dutton, et al. 2004; Parker, et al. 1995; Parker and Keim 2 004). However, Gilman (2008: 3) points out that, Â“Each age, culture and tradition has d efined acceptable weight for itself, and yet all have a point beyond which excess weight is u nacceptable, unhealthy, ugly or corrupting.Â” Regarding health, despite the adoption o f universal BMI categorizations of overweight and obesity by the World Health Organizat ion, the relationship between morbidity and BMI varies across populations (Ulijasek an d Lofink 2006; World Health Organization 2011). For example, studies have show t hat some Chinese and South Asian populations experience increased risk for chronic di sease than European populations (Ulijasek and Lofink 2006). Within the United States the ideal body size has becom e smaller over the past century both medically and socially, particularly for wom en. Both Boero (2007) and Rittenbaugh (1982) trace the origin of obesity as a di sease back to life insurance height and weight tables. Insurance companies, acting upon the common knowledge that extremely overweight individuals are more likely to h ave poor health, begin charging obese clients higher rates. In order to facilitate this, they created charts to determine Â“idealÂ” weights (Ritenbaugh 1982). Over time, these st andards have fallen so that the ideal height/weight ratio is lower than it was a hund red or even fifty years ago (Boero 2007; Ritenbaugh 1982). Rittenbaugh (1982) ultimate ly argues that the obesity epidemic has been Â“createdÂ” by insurance company charts and the lo wered standards for ideal weight. Since RittenbaughÂ’s work, the standard for a he althy weight fell again, from a BMI less than 27.8 to less than 25.0, making an estimate d 29 million Americans
26 overweight overnight (Squires 1998). In the social sphe re, Kolata (2007) traces the social history of the ideal female body, starting with the transition from the voluptuous Gibson Girl in the late nineteenth century to slimmer flappers in the 1920s. Spurred on by the growing availability of bathroom scales, fulllength mirrors and photography, the ideal woman became slimmer and slimmer over the course o f the twentieth century (Kolata 2007). Despite societal and biomedical preference for slimness, m any using this model have pointed out that being moderately overweight h as health benefits (Campos 2004; Cogan 1999; Harrington, et al. 2009; Kolata 2007; R itenbaugh 1982; Ulijasek and Lofink 2006; Ulijaszek 2007). The relationship between BMI a nd morbidity/mortality is usually U or J shaped, with increased risk of infectious disease a t the lower range, and increased mortality and chronic disease risk at the upper range (Ulijasek and Lofink 2006). In fact, being moderately overweight (defined as a BMI betwee n 24 and 27) reduces mortality (Cogan 1999). Evidence also suggests that overweight and obese individuals who are somewhat active and maintain a steady weight but do no t diet are healthier than dieters over the long-term (de Vries 2007). Further, a recent meta-analysis found that the evidence does not support advising weight loss for overw eight and obese individuals who are otherwise healthy, although exercise and a bal anced diet are always beneficial (Harrington, et al. 2009). Evidence does suggest, howev er, that cyclical dieting (also called yo-yo dieting) is very harmful. Cyclical dieting refers to a cycle of weight loss and regain that is typical of dieting (particularly fad di ets) and causes physical and psychological harm (Campos 2004; Cogan 1999). Finally, many using this model have also taken issue wi th the validity of BMI measurements since it doesnÂ’t distinguish between fat and lean mass (Burkhauser and Cawley 2008). Additionally, it is less accurate for some groups (such as African Americans), which leads to misclassification using the establi shed Â“universalÂ” categories
27 described above (Burkhauser and Cawley 2008). Further, BMI was intended by its creators to be used at the population level, not for i ndividual diagnosis (Keys, et al. 1972). No alternative is clearly agreed-upon, but re search shows that anthropometric measures like skinfolds taken by experienced practition ers are more accurate (Nevill, et al. 2006). Other alternatives include total body fat, percent body fat, waist circumference and waist-to-hip ratio (Burkhauser and Cawley 2008). According to de Vries (2007), accumulated scientific evidence seems to suggest that fat distribution, diet and fitness are factors in developing secondary diseases rather than the amount of body fat, suggesting that hip-waist ratio may be of more use th an BMI. Biomedical Model The biomedical model focuses on the genetic and physiolo gical causes of obesity and minimizes the role of individual behavior choices. It has a great deal of overlap with the biocultural perspective regarding th e role of genetics and human evolutionary preferences for high-fat foods (called th e Â“thrifty genotypeÂ” in the biomedical model). Unlike the biocultural model, however, users o f the biomedical model tend to minimize the role of individual choices and behaviors. S ocietal expectations, cultural traditions and the built environment play a very li mited role; environmental factors are only important in that they have some influence on th e expression of genes (Cummings and Schwartz 2003; Friedman 2004; Kolata 2007). As Fr iedman (2004: 563) explains, Â“Although environmental factors contribute to changes i n the incidence of obesity over time, individual differences in weight are largely a ttributable to genetic factors.Â” Heritability of obesity is estimated to be 50-90%, mea ning most of the variance of obesity is attributable to genes (Friedman 2004). Thi s indicates that obesity is more strongly inherited than breast cancer, schizophrenia or h eart disease (Cummings and Schwartz 2003: 454; Friedman 2004; Kolata 2007). In this model, obesity is seen as an
28 inherited disease, rather than a personal choice or chara cter flaw (Cummings and Schwartz 2003). Evidence for this position is drawn from a few landmar k studies (Cummings and Schwartz 2003; Friedman 2004; Kolata 2007). Researcher s who compared the weight class (thin, median, overweight, and obese) of 504 adul t Danish adoptees with their biological and adoptive parents found that there was a strong relationship between the weight class of the adoptees and their biological parent s and no relation with their adoptive parents. The results suggested that childhood family environment has little or no effect on weight in adulthood (Stunkard, et al. 1 986). A study of 25,000 fraternal and identical twins, some of whom were reared together and some apart found that identical twins had very similar BMIs regardless of whether they h ad been reared together or apart. Greater variation was seen in the BMIs of frate rnal twins, who only share some genes (Stunkard, et al. 1990). Another study found that even when the amount of additional calories consumed is controlled, identical tw ins gain nearly identical amounts of weight, but the amount of weight gained across pa irs varied dramatically (Bouchard, et al. 1990).Other studies with twins and research show ing clustering of obesity within families have provided further evidence of a strong g enetic component of obesity (Cummings and Schwartz 2003; Friedman 2004; Kolata 2 007). The biomedical perspective also points out that body wei ght is regulated by the homeostatic system, which maintains weight within a narro w range, generally 10 Â– 20 pounds (Cummings and Schwartz 2003; Friedman 2004). C ertain genes are responsible for balancing energy intake against energy expenditur e. Despite variance in day to day eating and activity levels, this balance is maintained over the course of days and weeks; weight is remarkably stable (Cummings and Schwartz 2003) When obese people lose weight, the body responds by decreasing the metabolism ( thereby conserving energy) and increasing hunger. These biological drives are the r eason that most people regain
29 the weight they lose despite their best efforts (Cum mings and Schwartz 2003; Friedman 2004). The impact of this phenomenon on dieters is be st explained by Friedman (2003: 857): Â“Those who doubt the power of basic drives, however, mi ght note that although one can hold oneÂ’s breath, this conscious act is soon overcome by the compulsion to breathe. The feeling of hunger is intense and, if not as potent as the drive to breath e, is probably no less powerful than the drive to drink when one is thi rsty. This is the feeling the obese must resist after they have lost a sig nificant amount of weight. The power of this drive is illustra ted by the fact that, whatever oneÂ’s motivation, dieting is generally ineffective in achieving significant weight loss over the long term.Â” Maintaining a modest weight loss of approximately 10 pounds is possible, but once outside of the bodyÂ’s narrow comfort zone (often called a Â“set pointÂ”), weight loss becomes very difficult to maintain (Friedman 2003; Ko lata 2007). Only those who are able to maintain constant vigilance are able to keep o ff large amounts of weight longterm (Campos 2004; Kolata 2007). In recent years, the focus within this model has turned to understanding the pathways between the body and the brain and within t he brain that determine when and how much we eat (Kolata 2007). Many of these studies a re undertaken with mice and rats in laboratories to better understand how the bo dy signals hunger and satiety. These scientists believe Â“fat people are fat because their dri ve to eat is very different from the drive in thin peopleÂ”; essentially, hunger is not the same experience for everyone (Kolata 2007: 168). Hormones that play a role in body weight and food intake, such as leptin and ghrelin, are currently under study. Leptin Â“is a med iator of long-term regulation of energy balance, suppressing food intake and thereby inducing we ight lossÂ”, and ghrelin appears to play a role in initiating eating (Klok and Drent 2007: 3). Research has now established that obese individuals are leptin-resistant, but the ex act relationship between the leptin and ghrelin systems and obesity is not yet completely und erstood (Klok and Drent 2007).
30 It is hoped that better understanding these hormonal p rocesses will lead to therapeutic interventions for obese people (Klok and Drent 2007; K olata 2007). Critical Anthropology Model The critical anthropological perspective is a reaction to the dominant public health model. Critiques include: the medicalization a nd individualization of obesity; the common practice of describing obesity as an Â“epidemicÂ”; th e promotion of obesity as a health problem for profit; the stigmatization of mi norities, women and the poor; and the normalization of disordered eating, among other crit icisms. This model does not comment on the etiology of obesity, but rather the wa y it is socially constructed. Medicalization One criticism is the way in which obesity has been medical ized despite the lack of clear evidence for a link between mortality and exce ss weight (Boero 2007; de Vries 2007; Germov and Williams 1999; Harrington, et al. 2 009; McKinley 1999). In fact, the medicalization of obesity is so well entrenched that thi nness has become synonymous with health (Germov and Williams 1999; McKinley 1999) Rittenbaugh (1982) argues that obesity is a Â“culture-bound syndromeÂ”, in essence a Wester n folk illness that does not exist in other parts of the world. She explains, Â“the changing biomedical standards [for body size] have paralleled changing cultural values, ra ther than the accumulation of biomedical knowledgeÂ” (Ritenbaugh 1982: 357). More r ecently Chaufan (2004) delved into the social construction of diabetes (which has many parallels with obesity) and points out that social failures are often veiled as perso nal failures by constructing them as medical problems. Chaufan concludes, Â“Indeed, calling something a Â‘medicalÂ’ problem because it affects the body shows a narrow under standing of causation, as much public health research has historically shownÂ” (Chauf an 2004: 266).
31 Interestingly, several authors note a subtle shift in th e literature from obesity being described as risk factor for disease to obesity be ing a disease in and of itself (de Vries 2007; Gilman 2008; Kolata 2007; Moffat 2010; S aguy and Riley 2005). On a pragmatic level, Moffat (2010) notes that defining ob esity as a disease allows for treatment to be covered by medical insurance. However, some have argued that change in terminology signals a shift away from assigning individual responsibility and an expansion of the purview of medicine (de Vries 2007 ; Saguy and Riley 2005). The obese thus become patients that must be cured; they are expected to undergo treatment, be it dieting or surgery (de Vries 2007; M offat 2010). Overweight becomes a state of being that individuals are Â“not expected to w ant to be in and cannot possibly enjoyÂ” (de Vries 2007: 62). However, the implication s of this shift may be overblown, since there are many diseases that have a clear biological etiology that are still seen as the result of individual behavior choices, such as sexuall y transmitted infections (Saguy and Riley 2005). Although there is disagreement about the manner or degree to which obesity has been medicalized, there is no doubt that is has become a medical issue (Boero 2007). Individualistic Several social scientists have pointed out that the indiv idualistic Â“eat less, exercise moreÂ” mantra is problematic because it masks socie tal contributions (the built environment, social class differences, etc) an d prevents people from questioning or examining the stigmatization of obesit y (Boero 2007; Saguy and Almeling 2008; Stinson 2001). Others have questioned the utility of behavior change messages not on the grounds of victim-blaming, bu t that these messages fail to address peopleÂ’s lived experiences (Austin 1999; Warin, et al. 2008). Warin and colleagues (2008: 98) point out that, in m ost behavior change
32 interventions Â“food, bodies and eating are disembodied and disengaged from the social contexts in which people live their lives.Â” In the ir ethnographic study of 30 Australian mothers from lower and upper socioeconomic ba ckgrounds, the women saw being a mother as their primary identity a nd linked food to their role as a mother and nurturer. The strong relational compon ent of mothering conflicts with the individualistic health messages that encouraging them to eat less and move more. Further, analysis by socioeconomic status (SES ) revealed that women of higher SES faced greater challenges in accessing safe places to be active and purchasing healthy food. Warin and colleague s conclude that the gendered and economic aspects of obesity cannot be ignore d when developing public health messages and programs. Obesity is a Â“comple x social issueÂ” that cannot be resolved through simplistic and individualisti c messages (Warin, et al. 2008: 108). Characterization as an Epidemic The high prevalence of obesity is often characterized as an Â“epidemicÂ” by news stories, scientific publications, and reports issued by pro minent health organizations (Gilman 2008; Moffat 2010; Saguy and Riley 2005). A nthropologists and other social scientists have taken issue with this descriptor, arguing that it invokes a sense of moral panic, fear and chaos and further legitimizes the ind ividualization and medicalization of obesity (Boero 2007; de Vries 2007; Gilman 2008; Moff at 2010; Saguy and Riley 2005). Moffat (2010) takes a different approach, and critici zes the use of the term Â“epidemicÂ” not for its fear-mongering properties, but its lack o f usefulness fr om a public health perspective. Strategies that have hi storically worked for epidemics of infectious diseases required swift and straigh tforward action, but obesity
33 will require thoughtful, multifaceted interventions. The Â“quick fixÂ” mentality of an epidemic is therefore counterproductive. Promotion of Obesity for Monetary Profit Many have pointed out that there are a multitude o f entities that have a vested financial interest in sustaining the idea that obesity is an enormous health problem, including weight loss, pharmaceutical, medical, insurance, fitness, apparel, fashion, food, and diet industries (Boero 2007; Germov and Wil liams 1999; Gilman 2008; Kolata 2007; Sobal 1999). Others have noted that research cent ers and academic departments have also benefitted from the grant money available to study obesity, and thus have professional interests to protect (Kolata 2007; Moffat 2010). That is not to say that all of these researchers are deceitful. As Kolata (2007: 190) p uts it: Â“Â…when your support, and your money, comes from making sure that the growing number of obese and overweight people is a m ajor public health priority, there may be at least subtle pressures to emph asize the dire consequences of weight gain and the importance of losing weight, whether or not the science fully backs these claims.Â” Moffat (2010) issues a reminder, however that in our capitalistic healthcare system, profit is garnered from many diseases and condit ions; obesity is hardly unique in this regard. Stigmatization, Particularly of Women, Minorities and the Poor As described earlier, there is a great deal of stigmati zation associated with obesity. Because women are held more strictly to the thi n ideal, they experience more stigma than men and have a higher incidence of eating disorders (Austin 1999; Boero 2007; Saguy and Almeling 2008; Saguy and Riley 2005) Within some minority groups, such as African-American and Puerto Rican woman, there h as been less body
34 dissatisfaction due to different conceptions of the ide al body, there is evidence that this is diminishing (Saguy and Almeling 2008; Stinson 2001) Minorities and people of low socioeconomic status are disp roportionately likely to be overweight and thus face stigmatization (Ernsberge r and Kolestsky 1999; Sobal and Stunkard 1989; Wang and Beydoun 2007). Obesity is bot h a cause and effect of poverty: weight stigma and discrimination can lead to low-wage w ork or unemployment and thus cause poverty, and low-income individuals have lower di etary quality and fewer places to be physically active, which contribute to weight gain (D armon and Drewnowski 2008; Ernsberger and Kolestsky 1999). Despite the clear inverse relationship between socioeconomic status and weight and the many studies on redu ced access to both safe places to be physically active and affordable healthy fo ods in low-income neighborhoods, the poor are still blamed for their weight (Saguy and Riley 2005). In their interviews with antiobesity researchers, Saguy and Riley (2005) found that while they recognized structural issues affecting low-income and mi nority groups, they tended to fall back on behavioral issues when discussing solutions. Within this context, overweight and obese individuals can reduce the considerable stigma levied against them by professing tha t they are too large (called Â“fat talkÂ”) and taking steps to lose weight (McKinley 1999; Nichter 2000). Ritenbaugh (1982) calls dieting a sick-role behavior because engaging in i t brings individuals in line with social norms and earns them praise. Similarly, Gilman (2008: 6-7) calls dieting Â“a process by which the individual claims control over her bo dy and thus shows her ability to understand her role in society.Â” It is therefore n ot surprising that body dissatisfaction has become normative in the United States (Germov and Williams 1999; McKinley 1999).
35 Normalization of Disordered Eating Several social scientists have pointed out that in our qu est for thinness, our relationship with food has become less healthy (Austin 1 999; Boero 2007; Cogan 1999). Hunger has been separated from appetite; the emotion al (and pleasurable) aspects of eating are downplayed in favor of assuaging the physio logical hunger in the most calorically efficient manner possible (Cogan 1999; Stinso n 2001). Foods are thus labeled Â“goodÂ” and Â“badÂ” not based on taste or enjoyment, bu t in terms of their caloric content (Stinson 2001). These unhealthy attitudes toward food have been normalized by both the media and nutritional public health (Austin 1999) An analysis of articles in the New York Times on obesity found that by and large, successful dieters are praised for their iron will and constant vigilance regarding both caloric intake and expenditure, traits usually associated with eating disorders (Boero 2007). Th e tools that make such vigilance possible are the Â“scientific progressÂ” of ration alizing and quantifying food (Austin 1999). Austin (1999) argues the invention of ca lories and nutrition labels, rather than being helpful, are tools that promote Â“magical t hinkingÂ” about the amount of control we have over our bodies and our weight and sustain ea ting disorders. Fat Acceptance Model The first, the fat acceptance movement, consists of a numb er of size acceptance groups, lay activists, and size acceptance researchers. The most notably and visible size acceptance group is the National Association to Advance Fat Acceptance (NAAFA). NAAFA characterizes itself as a human rights organizati on and maintains that fat acceptance is a social and political issue rather than a he alth issue (Saguy and Riley 2005; Sobal 1999). The organization advocates for the rights of fat people and are working to make height and weight protected from discr imination in the same way as race or religion (Kwan 2009; Saguy and Riley 2005). It should be noted that fat activists
36 have reclaimed the term Â“fatÂ”, much like the civil rig hts movement reclaimed Â“blackÂ” and gay rights advocates have reclaimed Â“queerÂ”(Kwan 2009; Saguy and Riley 2005). Fat activists see fat as a form of diversity and feel there are multiple causes of fat including genetics, metabolism and dieting history (Kwa n 2009; Saguy and Riley 2005). Weight, for the most part is not within individual con trol and much credence is given to genetic explanations and the Â“set pointÂ” phenomenon de scribed in the biomedical model (Saguy and Riley 2005). They do not see being fat as a health risk or disease, so the high prevalence (or Â“epidemicÂ”) is not a concern (Saguy and Riley 2005). Activists also spurn Â“what they consider to be artificially contrived m eanings associated with BMI. The BMIÂ’s importance lies not with its ability to predict go od or poor health, but instead how others use this number and its meanings to label, stigma tize and discriminateÂ” (Kwan 2009: 38). In order to provide evidence for their views, fat act ivists and researchers often cite the same studies as obesity researchers but come to ve ry different conclusions (Saguy and Riley 2005). For example, those in the fa t acceptance camp see the high failure rate of diets as evidence that weight is out of their control (Saguy and Riley 2005). Indeed, dieting is seen as dangerous (both physically an d emotionally), and surgery and drugs are viewed as risky and ineffective (Kwan 2009; Saguy and Riley 2005). Another example comes from Campos et al (2006) who use existing literature to disprove many of the common claims about obesity, arguing that the Â“ epidemicÂ” is a statistical artifact, the evidence that high BMI causes health problems is ove rstated, and that there are no safe and effective tools for weight loss (but many harm ful ones). Fat acceptance researchers also tend to point out, like the biocultural anthropologists, that being overweight can be protecti ve and that being underweight is actually riskier (Campos, et al. 2006; Ernsberger and K olestsky 1999). Except at statistical extremes (BMI in upper 30s), BMI is a poor p redictor of mortality. They critique
37 the studies that show a positive relationship between B MI and mortality, pointing out that they fail to control for confounding factors like fitne ss, exercise, diet quality, weight cycling, diet drug use, economic status, or family histo ry. The studies that do control for confounders use self-report data of questionable reliab ility (Campos, et al. 2006). As for the studies that show a 5 to 10% weight loss has beneficial effect, Campos (2004: 111) has this to say: "Time and time again, the pattern of these stories d oes not change: Formerly sedentary people become physically active, start eating healthier diets, lose little or no weight, and enjoy drastic improvements in health. Somehow, the moral of these stories almost al ways becomes some variation on Â‘losing just 10 pounds can cut the ri sk of developing X in half.Â’" Essentially, it is the increased exercise and improved die t that produces these positive results, and the weight loss is just a by-product (Campos 2004). However, some fat acceptance researchers are wary of rep lacing emphasis on weight with fitness and nutrition, and feel that att ention should instead be given to other factors like violence, prejudice, social isolation and materialism that detract from health (Saguy and Riley 2005). For their part, fat activists are also skeptical of this Â“fit but fatÂ” approach and feel that it still contains the type of moralizing that fat activists work against (Saguy and Riley 2005). Fat activists offer different explanations for why stud ies show that obese people have poor health outcomes. They point to neglectful he alth care, as many healthcare facilities are not equipped to accommodate people over 350 pounds (Saguy and Riley 2005). Additionally, fat activists draw on their person al experiences that doctors assume that all health problems they experience are due to their weight and do not fully investigate ailments (Saguy and Riley 2005). Further, they argue that fat people do not seek care because they want to avoid being admonished abo ut their weight (Kwan 2009; Saguy and Riley 2005). Another argument is that repe ated cycles of weight loss and
38 gain account for the increased risk of morbidity and m ortality among the obese (Ernsberger and Kolestsky 1999). Finally, fat activists offer many of the same critiques that critical anthropologists do. They also point out that a fixation on dieting a nd weight has contributed to disordered eating and promotes anorexia (Campos 2004 ; Saguy and Riley 2005). Campos (2004) agrees that people, especially women, di et not to improve their health but to escape the stigma and discrimination associated with obesity. Finally, fact activists also suggest that obesity researchers and the diet industri es experience a conflict of interest (Saguy and Riley 2005). However, fat activist s are much more oppositional than social scientists, referring to obesity researchers as the Â“f at mafiaÂ” (Saguy and Riley 2005). According to Kwan (2009: 40), Â“NAAFA considers it s opponents to be narrowminded, biased and essentially bad researchers who do not conduct objective research.Â” Fat activists also suggest that government panels are b iased, claiming that rather than qualified epidemiologists, researchers who run weightloss clinics or receive money from pharmaceutical companies are included (Campos, et al. 20 06; Ernsberger and Kolestsky 1999). Reactions and Responses to Explanatory Models Individuals accept, reject, modify and combine these five competing models. It seems that most women accept societal pressures to become thi n and use the public health framework as the path to weight loss. In Stinson (2001)Â’s ethnography of a commercial weight loss group, she noted that women talk ed about the stigmatization and the hurt and shame they have felt, but they chose to deal with it by conforming to societal expectations and losing weight. A qualitative study of 25 low-income white women had very similar findings, with women attemptin g to lose weight to incur social benefits rather than health benefits (Parker and Kei m 2004). However, not all obese
39 individuals accept the dominant public health model. Fo r example, Honeycutt (1999) interviewed eighty-six women and found three types of responses to societal pressure to be thin: Â“fat bustersÂ” who seek to lose weight and con form to societal expectations, Â“equivocatorsÂ” who accept their body as it is, and Â“fa t boostersÂ” who advocate for fat acceptance. Warin and colleages (2008) found that a number of asp ects of traditional public health programs did not reflect the way in which the w omen embodied obesity. For example, although they all had BMIs above 30, none o f them considered themselves obese and used alternate descriptors like Â“chubbyÂ”, Â“fat Â” and Â“big-bonedÂ” to distance themselves the stigma of obesity. A study of men in t he United Kingdom similarly found that men did not identify with BMI categories, instea d feeling that you could be heavy while still being healthy and fit, and that universal standards are of limited value because every body is different (Monaghan 2007). Conclusion Several social scientists have noted that obesity is a conte sted space in which various entities have defined causes and provided accompa nying solutions to obesity in very divergent ways. This chapter has expanded upon pre vious work regarding explanatory models of obesity and describes five explan atory models seen in the literature and popular press. The five models are: the dominant public health model, biocultural model, biomedical model, critical anthropol ogical model and fat acceptance model. The ways in which individuals adopt, transform combine or reject models was also briefly explored. It should be noted that there is a considerable amount of overlap in these models, and that the perspectives of researchers, public h ealth professionals and lay individuals do not necessarily fit neatly within these categories. For example, public
40 health professionals Puhl and Heuer (2010) argue passion ately against the stigma and fear that calling obesity an Â“epidemicÂ” has created a nd offer many of the same criticisms as medical anthropologists. These models simply provide a framework from which to explore the possible explanations for the high prevale nce for obesity and to think critically about appropriate responses.
41 Chapter 3: Methodology Introduction Like other social scientists, evaluators have multitude t heoretical lenses, methodological approaches and data collection techniques from which to chose when designing evaluation studies. As an applied researcher, I have chosen to take a pragmatic orientation in this study. In contrast to const ructivism and postpositivism, pragmatism problem centered, pluralistic and focused on real world problems and their solutions (Creswell and Plano Clark 2007). As part of t his pragmatic stance, a mixed methods approach was taken that sought to capitalize on existing program records while also expanding knowledge of participantsÂ’ perspectives on and experiences with the program. To this end, three main methods were used in this study: quantitative analysis of existing program records, participant observation of three case study GIFT groups, and semi-structured follow-up interviews with participan ts. This chapter will describe in detail how the research was carried out, including sampli ng and recruitment strategies, data management and the analysis plan. Also included ar e the research context and overarching research questions. Research Questions Four main questions guided the research process, allowi ng me to not only provide feedback to program staff, but also to investi gate theoretical anthropological issues of interest: 1. In what ways does the program meet (or fail to mee t) the needs of the intended audience?
42 2. How does the conceptual model of weight loss employed by the program correspond to the conceptual model used by participants? W hat implications does this have for the program? 3. What are the roles of education and empowerment w ithin the program? 4. What are the effects of the program? Institutional Review Board The Florida Department of Health (DOH) Institutiona l Review Board (IRB) determined that this evaluation did not constitute re search as they define it in June 2010, and was thus exempted from IRB monitoring. The letter of determination is found in Appendix A. The University of South Florida IRB has a n agreement to honor the decisions of the DOH IRB for cross-agency projects such as t his one, and thus this study was also exempted from USF IRB monitoring. A few small changes (mostly deletions) were made to the interview guide and a third case stu dy group was added, but as the changes did not change the intent or methodology of t he research, I did not need to submit a modification or reapply for approval. Although informed consent was not technically required, I still was open with participants about the research during my observations b y introducing myself as an intern with HCHD doing an evaluation of the GIFT pr ograms. I explained that I was there to learn more about how the program works firsthand, and so I would be taking a few notes during class, but I would not be using anyoneÂ’s na me or reveal the location of the group. I emphasized that my research was not on their p ersonal progress (or lack thereof) but in how the group members interacted with each other and how well the program met their needs. Participants were given the opportunity to object to my presence, but no objections were raised. Before each interview, I discussed the tenants of infor med consent verbally. I let each participant know that I was a HCHD intern and USF student doing an research
43 study to understand the experiences of people who have recently been in GIFT in order to make the program better. I promised each participan t that their identity would be kept confidential and that their name would not be used in my report. Additionally, I let them know that they could skip any question they felt unco mfortable with or end the interview at any time, and there would be no negative conseque nces for choosing not to participate. Participants verbally gave their consent t o participate, but no written document was signed. Mixed Methods According to (Creswell and Plano Clark 2007), mixed m ethods research can be viewed as both a methodology with underlying philosop hical assumptions and as a method for data collection. My use focuses on the latter : the collection, analysis and integration of qualitative and quantitative data wi thin a single study (Creswell and Plano Clark 2007). The biggest benefit of taking a mixed me thods approach is that each methodology helps compensate for the weaknesses of the o ther (Steckler, et al. 1992). For example, qualitative research is able to provide t hat context and nuance that quantitative research so often lacks, as well as adding participantsÂ’ voices to numerical data. Conversely, quantitative data can improve the e xternal validity of findings since sample sizes are generally larger. Together the two fo rms of inquiry create a more comprehensive understanding of an issue than either could by itself (Creswell and Plano Clark 2007). Mixed methods is an especially appropriate approach for evaluation work, since people naturally use both words and numbers to des cribe the world around them and to solve problems. Appealing to this tendency make s for a more convincing argument, an absolute necessity in evaluation since findi ngs must first be found credible and convincing by clients in order for recommendations t o be implemented (Creswell and Plano Clark 2007; Graig 2010).
44 Although the two methods can be combined in a variety of ways, in this case the qualitative and quantitative data were collected sepa rately, but concurrently and were triangulated in the analysis phase (Creswell and Plano Clark 2007). Known as Â“concurrent triangulation designÂ”, the goal is to collect non-overlapping, complementary data on a single topic (Creswell and Plano Clark 2007) Each of the methods used to collect complementary data will be described next. Data Collection Quantitative Analysis of Existing Program Records The first method, quantitative analysis, was conducted i n PASW Statistics V.18.0 (formerly SPSS). I designed templates in PASW and en tered all of the data for of the program from the past year (approximately September 1, 2009 to August 31, 2010). Every piece of information that was included on existin g program records was entered for all 681 participants. This included identical 10 qu estion preand posttests that measured knowledge, Screening Forms where height, wei ght, BMI, and waist size were supposed to be recorded at Weeks 1 and 6, and an Evalu ation Form that measured participant satisfaction and asked participants to retro spectively assess whether they met their goals and improved their health. Change in fruit and vegetable consumption and physical activity used to be measured on the prean d posttests. Currently participants are asked to give their current fruit an d vegetable consumption and physical activity habits on the Where am I? Form in Week 1, an d then retrospectively assess changes in their diet and activity level on the Evalu ation Form in Week 6. Participants also complete food diaries, but it quickly became appar ent that the legibility and level of detail varied widely and any data produced on change in diet would be unreliable. Instead I recorded whether participants submitted their food diary each week. The food diary had to be at least 50% complete in order for th e participant to receive credit,
45 meaning that at least one food had to be recorded for at least half of the meals for that week. In order to protect participant confidentialit y, each participant was assigned an arbitrary unique ID; an excel spreadsheet matching the participantÂ’s name to their unique ID was kept separately from the SPSS database. Reproductions of these forms can be found in Appendices B-G. Participant Observation Participant observation is Â“a process of learning throug h exposure or involvement in the day-to-day or routine activities of participant s in the research settingÂ” (Schensul, et al. 1999). Among other benefits, participant observati on allows the researcher to understand how people relate to each other and build relationships that are critical to more in-depth understanding (Schensul, et al. 1999). A lthough I had been provided with the facilitatorÂ’s manual and a program description, I felt it was critical to see how the groups operated firsthand since social support was such an im portant piece of the program. CHAs are also given a fair amount of leeway in terms of how the classes are run, and so I was interested to see how much the groups diverged. For example, the physical activity portion each class session is not scripted in a ny way, and is instead left up to the discretion of the CHA. The degree of participation during observation falls a long a continuum, with complete observation at one end and complete participat ion on the other. Participant observation makes up the wide grey area in between (B ernard 2006). For most of my fieldwork, I was unable to fully participate as I was ne ither a trained program facilitator nor a seriously overweight person seeking to lose weight (Bernard 2006; Schensul, et al. 1999). However, I was able to go beyond complete obser vation and participate to some degree in class activities (such as group exercise) and in teract with participants the vast majority of the time. This included not only my time with the three case study groups, but
46 other activities that I was asked to carry out as an int ern. Specifically, I helped with the baseline and/or follow-up measurements at Weeks 1 and 6 for three other branches of the workplace wellness initiative. Each branch had two or three GIFT groups, and so I interacted with seven additional groups in this manner and was able to observe the entirety of the lesson each time I did measurements. Ad ditionally, I was invited to attend one meeting of all paid CHAs that HCHD hosts semi-regul arly in order to illicit feedback on the program. Midway through fieldwork I felt I needed to expand t he study to include observations of community groups. I added third case stud y group, this one held at a public library, but due to a scheduling conflict with th e CHA I guest taught week two and then took over as facilitator of this group for Session II (Weeks 7-12). In this case I became what Bernard (2006) calls an observing participan t, a person with an insiderÂ’s perspective who makes and records observations. I felt som e conflict of interest attempting to evaluate the program and teach it simul taneously, so in these observations I shifted my focus to the challenges of being a CHA. In all I observed over forty hours of GIFT Â“in actionÂ” among the ten groups I interacted with. I attended all six weeks of the workp lace wellness group, which chose to disband after only one session, and fifteen weeks of the community center group, which is still ongoing. The library group went for twelve w eeks (two sessions), during which I observed four classes and taught five. Semi-Structured Interviews. To date, little has been done to follow up with part icipants to investigate their maintenance (or lack thereof) of weight loss and behavi or changes achieved during the program. Nor have participants been given an opportu nity give their opinions about the program, aside from the close-ended evaluation forms. For these reason I sought to do
47 semi-structured follow up interviews with program par ticipants. According to Bernard (2006) semi-structured interviews are the best choice if y ou only have the opportunity to interview informants once; they also allow you to pro duce reliable data while maintaining a degree of flexibility to follow leads. Since there were certain topics that I specifically wanted to cover but others that wanted to approach in a more exploratory way, semistructured interviews seemed the most appropriate choice Like many researchers, I faced difficulty in recruiting p articipants and had to change strategies during data collection a number of ti mes. Most notably, I shifted from in person to telephone interviews and shortened the in terview guide early in the process, and this increased participation markedly. It is also w orth noting that the case study approach was never intended to produce a representative sample, so the slightly unorthodox sampling strategy employed here is only a minor setback. In the end, a total of 17 interviews were conducted between September and November 2010. Two were conducted in person, the remainder were over the telep hone. Interviews ranged from 10 minutes to 45 minutes in length, but the average wa s approximately 25-30 minutes. The original interview guide was reviewed by the comm ittee. A much abridged interview guide was pilot tested in two interviews, bu t after it became apparent that participants had less to say for each question that I anticipated and were willing to talk for a longer period of time than expected, I added b ack in most questions. Both the full and abridged interview guides can be found in Appendi ces H and I. In both the original and revised versions topics included goals coming in the pr ogram, prior weight loss experiences, opinions on various aspects of the program (l essons, physical activity, food diary, etc), family support, and suggestions for improv ing the program. The goal was to have participants reflect on their time in GIFT and t alk about how they have been doing since the program ended. One month was chosen to allow sufficient time to pass for
48 longer-term program effects to emerge, but not so long that most participants (who the program staff described as Â“transientÂ”) will have moved on. Originally I had intended to interview participants who had completed the program, but during observations and data entry it b ecame very clear that a significant portion of participants were not completing the program. In order to better understan d this, I sought to expand my sample to include both those who did and did not complete the program (Â“completersÂ” and Â“noncompleters"). In both cases a purposeful sampling framework was used. For participants who completed the program, I drew my sample from my informants: I invited those who I had met and inter acted with over the course of the program to participate. This included the participants o f my case study workplace wellness group, as well as the groups that met during t he lunch periods before and after. As an intern, I had to collect the paperwork from all t hree groups, and thus had a chance to interact with these two groups on a weekly basis also (although I observed the entire class for the case study group only). I also did the fina l measurements during Week 6 for all three groups, and took this opportunity to invit e program participants to be interviewed approximately one month. I asked for vo lunteers to provide me with their email address or phone number. Of the twelve potenti al participants, ten initially volunteered, but only six were actually interviewed. I had planned to use the same strategy for the communit y center group, but unlike most groups which end after six or twelve weeks, this group is poised to go on indefinitely. The goal of the interview was to follo w-up with participants, so it would have been inappropriate to interview participants while th ey were still attending weekly. Due to time constraints, I was unable wait for the group to e nd. However, one person did not continue beyond the first session. I contacted this person a month after she stopped attending and she agreed to be interviewed.
49 Those who did not complete the program came from both groups I interacted with and groups that I did not. In the case of the gr oups I interacted with, I waited four weeks past each individualÂ’s last attendance. I then calle d each person and invited him or her to be interviewed between 10 am and 5pm, Mon day through Friday. If the potential particpant answered, I explained the purpose of the study and asked them if they had the time to do the interview right then. F ailing that, I asked to schedule the interview for a later time. If no one answered, I l eft a brief voicemail will be left explaining the purpose of the study and inviting him or her to participate along with my phone number. If the person did not return the first call, I placed a second phone call, but there was no answer, I did not leave a voicemail or ma ke further attempts. Using this method, I contacted eleven potential participants and six participated. I recruited from groups I had not interacted with using the database I had compiled using the existing program records. Prior to 2 010, the program forms did not ask participants for their phone numbers, and even then many participants did not put down a phone number. My inclusion criteria were thus: 1) did not complete the program, and 2) have a phone number on record. I contacted all 38 eligible participants using the same method described above and completed 4 interviews. In total using all sampling strategies, I interviewed 7 completers and 10 noncompleters. Of the seven completers, six were from w orkplace wellness groups and one was from a community group. Of the noncompleters, f our were from workplace wellness groups and six were from community groups. It sho uld be noted that of the 10 non-completers, only five were full interviews. Incom plete interviews exist for two reasons: 1) the two pilot interviews used a much abridge d interview guide with relatively few questions, 2) three participants asked to stop the interview before all questions had been answered. The sample size for the interviews was so small that it I determined it to
50 be worthwhile to include the information I did gathe r, rather than discard the data altogether. Supplemental Sources of Information In addition to the data described above, two other so urces of data were shared with me by informants and utilized for triangulatio n purposes. One was an audio recording of a focus group conducted by HCHD as part of t heir community health assessment effort that I was given permission to use. The f ocus group took place at a church that had recently had the GIFT program; much of the conversation focused on GIFT although that was not the intent or purpose for assembling the focus group. I listened to the entire audio recording and transcribed the portions pertaining to GIFT. The second source of information was weekly goal forms ( called Â“action plansÂ”) completed by participants, as well as the longer-term g oal setting exercise done in Week 1. The forms are mostly qualitative in nature, but t he checklist of medium-term goals completed in Week 1 is more quantitative in nature. I n total I entered of goal sheets from 345 individuals. Analysis Plan Quantitative Analysis of Existing Program Records Before analysis could begin, the issue of missing data ha d to be addressed. The data set is missing a substantial amount of data for thr ee reasons: 1) not all participants enter the program at Week 1, 2) not all participants co mplete the program, and 3) CHAs vary in their record keeping. In order to compensate fo r the fact that participants enter and leave the program at different times, I used the last value carried forward (LVCF) and next value carried backward (NVCB) techniques for t he beginning and ending weight variables (McKnight, et al. 2007). Essentially, the first weight recorded for a
51 participant (regardless of whether it was measured duri ng Week 1) was that participantÂ’s beginning weight. Similarly, the last weight recorded was carried forward to be their ending weight. The effects of last value carried forw ard on significance are not predictable, so while the chance of errors are unquestion ably heightened with its use, it is impossible to predict whether Type I or II errors ar e more likely (McKnight, et al. 2007). Using LVCF and NVCB addressed the problem of missing da ta regarding weight, but missing data was a problem for nearly every variabl e. One solution is to delete all cases in which there are one or more missing variables, bu t this would have severely reduced the sample size and statistical power (McKnight, et al. 2007). Instead, I used the available case method (also known as pairwise deleti on), which uses all available cases for each test (McKnight, et al. 2007). This of course results in a different sample size for each test, which can be problematic for sophisti cated regression analyses, but is suitable for the type of intermediate analysis done he re (McKnight, et al. 2007). With this shortcoming in mind, the sample size is reported for each statistical test. While techniques such as these can help minimized the impact, missing data is still a threat to validity. The results from the quantitative analysis se ction must therefore be interpreted with caution. Originally the database included data for Sessions I an d II (Weeks 1-12), but was later scaled back to include only Session I (Weeks 1-6) si nce so few records existed for Session II (Weeks 7-12). Seventeen participants were re moved at this point because they participated in Session II but not Session I, redu cing the sample size to 664. In the first phase of data analysis, the entire data set (664 p articipants) was used to investigate beginning waist circumference, beginning BMI, demograph ics and attendance. Differences between completers and noncompleters were also investigated in order to determine whether the noncompleters were different de mographically from completers.
52 Change in knowledge (as measured by the pre and postte sts) was also assessed, as well as opinions regarding CHAs and behavior changes (u sing the Evaluation Forms). The way in which self-reported fruit and vegetable con sumption was changed twice during the 1 year period the data was pulled fr om, complicating analysis considerably. It used to be that daily fruit and veget able consumption (in cups) was measured alongside the ten knowledge questions on the preand posttests. This is no longer the case, nor are participants asked to think ab out their consumption in terms of cups. Currently, consumption is assessed on the Where Am I? Form in Week 1 and the Evaluation Form in Week 6, but in very different way s. The Where Am I? Form asks Â“On average, do you eat a total of five (5) fruits and/o r vegetables every day?Â” with Â“yesÂ” and Â“noÂ” as answer choices. This question is not repeated on the Evaluation form and instead participants are asked to retrospectively assess whe ther they have increased their fruit and vegetables intake. As described in th e methods section, data were combined from the older and newer versions of the Eval uation Form when possible. In some instances it could not combined because the questions were too dissimilar, so it is simply reported as is. Change in fruit and vegetable consumption could not be assessed because: 1) consumption is measured differently in Weeks 1 and 6, and 2) data could not be matched because Evaluation Forms are anonymous. Many of the same issues that impacted the fruit and veg etable consumption analysis were also apply to physical activity. Like fruit and vegetable consumption, the physical activity used to be measured alongside the ten kn owledge questions on the preand posttests. Currently, physical activity is assessed on th e Where Am I? Form in Week 1 and the Evaluation Form in Week 6, but in very dif ferent ways. The Where Am I? Form asks as series of three questions where participant s are asked first if they engage in physical activity, then how many days per week, and f inally how many minutes each session. This series of questions is no repeated on the Ev aluation form and instead
53 participants are asked to retrospectively assess whether they have increased their physical activity. The two versions Evaluation Form also ask participants a number of questions regarding satisfaction with the facilitator. The bigg est difference between the two versions is one calls the CHA the Â“presenterÂ” and the oth er uses the term Â“facilitatorÂ”, but for the most part the questions were identical and the responses from the two versions were combined. A few questions were added to the curren t version of the form, and are also presented. It should be noted that again, a relat ively small number of participants completed these forms (121 of 664 or less than 20%) and their opinions may not be true for all participants of GIFT. In addition, the Evalua tion Form is a bit confusing because the question stems and answer choices donÂ’t match. Partici pants are asked to rate their level of agreement with various questions, but usually in surveys this type of rating scale is used with statements rather than questions. Further, the way the form is designed, the response choices are simply the numbers 1-4 next to each question. There is key explaining the meaning of each number at the top, bu t some participants may have been confused by this layout (see Appendix F). There were a couple of instances during data entry I noticed participants who gave very negative ra tings throughout the Evaluation Form and then wrote something positive in the open-en ded section at the bottom, suggesting that they misunderstood the ratings scale. T herefore, results were interpreted with caution. The second phase of analysis focused on weight change durin g the program and its relationship to demographic factors, food diary compl etion, and attendance. Only those who had attended at least two times were included in this portion of the analysis since at least two measurements are necessary in order to i nvestigate weight change. Individuals who had attended only once were removed ( n=156), as well as individuals who were part of groups for which there was less than tw o weeks of data (n= 76) or
54 inconsistent data (n=12). In total, 244 cases were remo ved, leaving a sample size of 405. This same sample was used to investigate the relatio nship between change in waist circumference and change in weight. In this phase descriptive statistics, KruskalWallis, Mann-Whitney U, X 2 for independence tests were used. Participant Observation After each observation event, I wrote copious fieldnot es, nearly always later that day. I mostly described events, but I also included some musings about methodology and some tentative conclusions. As recommended by Schensul et al (1999) I was careful separate my emotions from the events; I worked to describe events neutrally with as much detail as possible before stating my reactions, f eelings, and opinions. Participants names were not included in my fieldnotes, nor were locations. Altogether I compiled approximately 100 pages of fieldnotes (more than 44,000 words). In analysis, I used a deductive framework described by LeCompte and S chensul (1999). Using the tracking changes function in Microsoft Word, I coded passa ges that related to either group dynamics (including instances of social support) or w ays in which the program met (or failed to meet) the needs of participants. These broad codes were further refined and sub-codes were developed. Eventually a codebook was made with a definition and inclusion and exclusion criteria for each code. A separate word document was created where all quotes for each code were compiled. Semi-structured Interviews When possible interviews were audio recorded (11 of 17 interviews). Two were not recorded because participants objected, and the firs t four telephone interviews were not recorded because I worked in an open area where usi ng speakerphone would have been inappropriate. I eventually purchased a device to enable the recording of telephone
55 interviews. When interviews were not recorded, I took e xtensive notes during and immediately after the interviews. For those that were recorded, the responses to each question (including probes) were transcribed. In both cases I also took notes during the interviews, including participantsÂ’ general disposition a nd points which elicited strong emotional reactions. During the analysis process I utilized deductive and in ductive approaches at different times. As a goal-free evaluation that lac ks hypotheses, this study could be classified as exploratory in nature. According to Bernard (2006), inductive analysis is most appropriate for exploratory research, while deduct ive approaches are best suited in the confirmatory research that tests hypotheses. However LeCompte and Schensul (1999) point out that the dualism between induction a nd deduction is something of an oversimplification because ethnographers use both inducti on and deduction throughout their analysis. After I reading through the interview s a few times to ground myself in the data, I decided to take a two phase approach: deduction followed by induction. In the first phase, I deductively coded the responses to e ach question on the interview guide based on the interview question and m y research questions. All of the responses to each question were first compiled into a wo rd document, and then each response was assigned a code. As the analysis was refined, cod es were combined and separated and a code book was created that detailed the definition and inclusion and exclusion criteria for each code. An excel spreadsheet was used to keep track of the code or codes assigned to each personÂ’s response to each que stion. In the second phase, a more inductive approach was taken to allow hi gher level themes to emerge from the text that went beyond individual interview questions. As I read through the text and became further grounded in the data, I used the co mment function in tracking changes in Microsoft Office to write memos. Through thi s iterative process, I was able to
56 clarify the themes and patterns and eventually choose ex emplar quotes to illustrate each finding. Supplemental Sources of Information The qualitative portion of the goal forms was analyze d in much the same was as the deductive phase of the interview analysis, since the goal forms also pose a series of questions to participants. The qualitative checklist sect ion was analyzed using simple frequency calculations, as was the data provided by the e mployerÂ’s satisfaction survey. The focus group was coded using the same codes that had be en developed for the fieldnote analysis. Triangulation This study employs a mixed methods approach and pulls da ta from many sources, creating a rich environment for triangulation Triangulation involves the crosschecking of quantitative and qualitative data in o rder to assess reliability and validity (Handwerker and Borgatti 1998; Schensul, et al. 1999). During the analysis phase, the data were combined in two ways. The first w as to expand upon the quantitative findings using qualitative data (Creswell and Plano Clark 2007). Prior to this study, no one had followed up with participants after the program, so interviews provided important additional information about events after the program not captured in the existing program records. More significantly, qualitati ve findings were used as an aid in interpreting the quantitative data (Bernard 1988; C oombes 2000; Salazar, et al. 2006; Steckler, et al. 1992). As Coombes (2000) puts it, "Quantitative methods can best evaluate whether there is a relationship between an intervention and a health outcome, whereas qualitative methods are best placed to assess why the relationship existsÂ” (italics original). Rather than simply speculating at th e meaning of the quantitative
57 results, the qualitative data is used as a rich source f rom which to draw explanations. This is especially important in this study, since the missi ng data weakens the validity of the quantitative findings. Since this study lacked a control group, planning for t riangulation of data was critical. The absence of a control group makes it impossibl e to definitively state that observed effects are due to the program; apparent pro gram effects could be due to a wide variety of outside factors such as environment, exp erience or socioeconomic status (McKenzie and Smeltzer 2001, Royse et al 2001). That being said, effects seen in the qualitative observations and interviews are consistent w ith the effects seen in the quantitative analysis, a stronger case can be made that these effects are indeed due to the program and not extraneous factors. Conclusion This study employs a mixed method design to explore th e effects of the GIFT program, assess its ability to meet the needs of partici pants, and determine the degree of fit between the explanatory models employed by t he program and its participants. To this end, three main methods were used: quantitative a nalysis of existing program records, participant observation and semi-structured qu alitative interviews. Analysis was carried out quantitatively using intermediate statistics, while the qualitative analysis utilized inductive and deductive approaches. Triangula tion of all three methods as well as other sources of data was carried out in order to imp rove validity.
58 Chapter 4: Results Introduction As described in the methods chapter, three methods were used to better understand the effects of GIFT and how the program is meeting (or failing to meet) the needs of participants, as well as explore issues of educat ion, empowerment and individualism in regard to weight loss. This chapter pr esents the results from the analysis of the data collected for this study. The results are org anized according to methodology and theme. Quantitative Analysis Population Reached The sample included data for 75 GIFT groups which rang ed in size from 1 person to 32 people, with an average of 8.8 total participa nts and a median of 6.5 total participants. However, there was evidence there were m ore groups than were entered into the database. For instance, there were several occasi ons in which an attendance sheet with names was the only available data and so was not entered. Table 1 below shows the demographic characteristics of part icipants of GIFT, i.e. the population reached. Data on these three demograph ic characteristics exists for only 68.1 73.3% of the total sample (664 participants). That being said, the data available suggests that the overwhelming majority of participan ts were female (87.3%) and most participants were ethnic/racial minorities (75.1%). Reg arding age, participation falls
59 along a bell curve, with the majority of participants in their forties or fifties. The typical participant was a middle-aged African-American or Hispan ic woman. Table 1 Demographic Characteristics of GIFT Participants Characteristics Frequency (%) Gender Female 425 (87.3) Male 62 (12.7) Total 487 (100.0) Ethnicity African-American/Black 205 (43.3) Hispanic/Latino 118 (24.9) Caucasian/White 127 (26.8) Asian/Pacific Islander 5 (1.1) Native American 2 (0.4) Other 16 (3.4) Total 473 (100) Age 18-30 40 (8.8) 31-40 65 (14.4) 41-50 108 (23.9) 51-60 121 (26.8) 61-70 81 (17.9) 71 and older 37 (8.2) Total 452 (100) A little over half of participants (n=362, 54.5%) rep orted where they heard about GIFT. Most heard about it through word of mouth (n=1 08, 29.8%), agency outreach (n=42, 11.6%), printed media (n=35, 9.7%), community partners (n=49, 13.5%) or Â“otherÂ” (n=105, 29.0%). Most who chose Â“otherÂ” were part of wo rkplace wellness groups and indicated that they learned of GIFT through a co-work er or their employer. Beginning BMI and Waist Circumference Although beginning BMI is reported on the screening f orm, BMI was also calculated using reported height and beginning weight. The following chart shows both
60 versions of BMI broken down into the BMI categories used by the World Health Organization (World Health Organization 2011). Rega rdless of the method used to obtain BMI, the data shows that of participants with B MI data, approximately 28% are overweight (a BMI of 25.0-29.9), and approximately 58% are obese (a BMI over 30.0). A Wilcoxon Signed-Ranks test determined that reported an d calculated BMI are significantly different (p=0.001, z=3.445, n=406). Th is suggests that reported BMIs are not as accurate as they could be. 50 100 150 200 250 Less than 18.5 18.5-24.925.0-29.930.0-34.935.0-39.940.0 and upMiss ing Reported Calculated Figure 1 Beginning Body Mass Index (BMI) Next, it was investigated whether the difference betwe en reported and calculated BMI led to participants being improperly classified accor ding to the BMI categories used in the program. A crosstabulation chart showed that re ported BMI categorization put 18 participants (of 397) incorrectly into either a highe r or lower category. A chi-square for independence could not be calculated because the data did not meet the criteria for expected frequencies, even when categories were collapsed Still, the data shows that
61 for a very small number of cases the reported BMI was in accurate enough to incorrectly classify participants. Regarding waist circumference, only about 60% of partici pants had a beginning waist circumference recorded. Of the 395 who did, 76.5% did not meet current waist circumference guidelines of <35Â” for women and <40Â” for men when they entered the program (Centers for Disease Control and Prevention 20 11a). Overall, a strong majority of participants did not meet guidelines for BMI or wa ist circumference when they entered the program. Attendance Attendance was tracked using weekly sign in sheets. Figure 2 shows overall attendance for each week of the program. Attendance stea dily falls as the program progresses. The amount of missing data increases in Weeks 4-6 indicating that record keeping declines in the second half of the program. 50 100 150 200 250 300 350 400 450 Week 1Week 2Week 3Week 4Week 5Week 6 Attended Did not attend Missing Figure 2 Attendance by Week
62 Figure 3 shows the breakdown of the number of classes par ticipants attended. Of the 556 participants with attendance data, approximate ly a quarter (28.3%) attended only one class, and 12.2% attended all six weeks of the program. This representation is not entirely fair, however, because not all participan ts enter at Week 1 and therefore do not have the opportunity to attend all six classes of Se ssion I. 20 40 60 80 100 120 140 160 180 1 class2 classes3 classes4 classes5 classes6 classe sMissing Figure 3 Number of Classes Attended Figure 4 shows the distribution of entry points into th e program. Of those with attendance data (n=558), 68.1% of participants began t he program at Week 1. The goal is to avoid referring participants into a GIFT group a fter Week 2, but 17.2% entered the program during Weeks 3-6.
63 50 100 150 200 250 300 350 400 Week 1Week 2Week 3Week 4Week 5Week 6Missing Figure 4 Entry into GIFT In order to account for the fact that participants ent er the program at all different times, a percentage score was created. Figure 5 shows the percentage of classes participants attended of the classes they had the opport unity to attend. The percentage scores are broken into quartiles. Of the 566 participan ts with data, 42.9% of participants attended 75-100% of classes, but another 40.8% attended less than half of the classes they could have.
64 50 100 150 200 250 300 Attended 25.0% or lower Attended 25.150.0% Attended 50.175.0% Attended 75.1100.0% Missing Figure 5 Percentage of Classes Attended In fact many participants did not complete the program For the purpose of analysis, participants were divided into three groups: Â“complete rsÂ” who attended through Week 6, Â“non-completersÂ”, who stopped attending before or at W eek 4, and Â“undeterminedÂ” participants who attended Week 5 but not Week 6. It is unclear if these Â“undeterminedÂ” participants intended to quit the program or simply m issed a week. Completers accounted for 28.3% of all participants (n=188), 41.6% were non-completers (n=276), 12.5% were undetermined (n=83) and 17.6% were missing this data (n=117). Several tests were run to determine if completers diff ered from non-completers by demographics (gender, ethnicity and age) and beginn ing weight. X 2 tests for independence were used to test whether age and ethnici ty were related to completion status. Gender had no bearing on completion status (p=0 .474, n= 415), nor did ethnicity (p=0.073, n=384). A Kruskal-Wallis test showed that we ight does not vary significantly according to completion status (p=0.712, n=466), nor do es BMI (p=0.462, n=395).
65 Age however, was related to completion status. A Krus kal-Wallis test showed that there was a difference in age among the three com pletion status groups (p=0.017, n=403). Mann-Whitney U tests were then run to uncover where the differences occurred, and it was found that non-completers were significantly younger than those whose dropout status is unclear (p=0.006, n=184). The mean a ge of non-completers was 48.3 years, versus 55.0 for undetermined participants. The d ifferences between the other groups were not significant. Finally, the relationship between the week participant s enter the program and completion status was investigated. Figure 6 shows the di stribution of completers, noncompleters and undetermined participants according to th e week they entered the program. The data in this form did not meet the req uirements for a X 2 test for independence, so the data were re-organized to compar e those who entered in the first half of the program (Weeks 1-3) with those who enter ed in the second half (Weeks 4-6). Those who entered in Weeks 1-3 were less likely to fin ish the program than those who entered later (p=0.000, n=539). Similarly, those wh o started in Weeks 1 and 2 were less likely to complete the program than those who started in Weeks 3-6 (p=0.000, n=539), and those who started in Week 1 were less likely to comp lete the program than those who started in Weeks 2-6 (p=0.021, n=539). Corroborati ng this finding is Figure 7 below, which shows the last week attended by non-completers. Appr oximately 87% of noncompleters stopped attending the program in the first half (Weeks 1-3).
66 50 100 150 200 250 Week 1Week 2Week 3Week 4Week 5Week 6 Completers Non-completers Undetermined Figure 6 Entry Point of Participants by Completion Status 10 20 30 40 50 60 70 Week 1Week 2Week 3Week 4Week 5Week 6 Figure 7 Last week Attended by Non-Completers
67 Change in Weight As discussed in the methods section, weight change was analyz ed using a smaller data set of 405 participants. Those who attended only once, had only one week of data available, or had inconsistent data were removed. Figu re 8 shows the change in weight among participants. Most participants (69.9%) experien ced either no change or a small change in weight (5 lbs in either direction). A litt le over 40% of participants lost less than 5 lbs while almost 20% gained less than less than 5 lbs. 20 40 60 80 100 120 140 160 180 Lost < 10.01 lbs Lost 5.0110.00 lbs Lost 0.015.00 lbs No changeGained 0.01-5.00 lbs Gained 5.01-10.00 lbs Gained > 10.01 lbs Missing Figure 8 Change in Weight However, looking at pounds gained or lost oversimplifi es matters because it fails to take into account that people enter and leave the program at different times and thus have different amounts of time in which to lose (or gain) w eight. For instance a person who attends three classes has a smaller of window of time in which to lose weight than a person who attends all six. This was dealt with in two ways. One was to divide weight change by number of weeks attended for each participan t to produce a new measure of
68 Â“weight change per doseÂ” (i.e. each class is a Â“doseÂ” of th e program). Another was to simplify weight change into three groups: gained, mai ntained or lost weight. These three categories are collectively referred to hereafter as Â“ weight change statusÂ”. Of the 341 participants with weight change data, 64.2% (n=219) lost weight, 10.0% maintained their weight (n=34), and 25.8% gained weight (n=88). Those who gained, maintained and lost weight were separated out in order to do a paired com parison (a Wilcoxon Signed Ranks Test) to determine if weight changed significantly. Th ose who lost weight lost a significant amount of weight (p=0.000, n=219), and th ose who gained weight gained a significant amount of weight (p=0.000, n=88). Tests were run to determine the relationship between weight change and demographic characteristics (gender, ethnicity and age) First, a Mann-Whitney U test was used to determine if weight change per dose differe d by gender. It was not significantly different (p=0.431, n=306). A X 2 test for independence was also calculated to test for a relationship between gender and weight change status and was also not significant (p=.534, n=306). Both tests suggest that one gender did not have greater or lesser success than the other. Next a Kruskal-Wallis test was used to determine if we ight change by dose differed among ethnicities. In order to meet the requ irements of the tests ethnicity was simplified into four groups: African-American/Black, Hispa nic/Latino, Caucasian/White and Other. There was not a significant difference amon g ethnicities (p=0.088, n=298). A X 2 test for independence was also used to test for a relati onship between ethnicity and weight change status and was also not significant (p=0.17 4, n=298). Taken together, the tests suggest that no ethnic group did significantly better or worse than the others. A Kruskal-Wallis test was also used to determine if weig ht change by dose differed among age categories (the same categories used a bove in Table 1). There were no significant differences among age categories (p=0.13 4, n=301). A X 2 test for
69 independence was also used to test for a relationship bet ween age categories and weight change status. In order to meet the requiremen ts for this test, age categories had to be collapsed into 18-40, 41-60, and 61+. The result s were not significant (p=0.262, n=301). The tests suggest that no age group did signif icantly better or worse than the others. Next, the relationship between weight change and atte ndance was explored. First a Kruskal-Wallis test was used to determine if wei ght change by dose differed among participants who attended 2, 3, 4, 5 and 6 classe s. The test was not significant (p=0.088, n=341), indicating that attending a certain number of weeks didnÂ’t lead to improved outcomes. However, at the suggestion of prog ram staff, I divided the participants in two groups by attendance: those who comp leted up to half the program (2-3 classes) and those who completed more than half of t he program (4-6 classes). A Mann-Whitney U test was conducted to compare weight chan ge by dose between participants who attended 2-3 classes and 4-6 classes. The r esults were significant (p=0.009, n=341). Those who attended 4-6 classes lost an average of 0.46 lbs per class, slightly more than those who attended only one or two classes (0.31 lbs per class on average). A X 2 test for independence was also used to test for a rela tionship between attendance and weight change status. The results were si gnificant (p=0.000, n=341), and indicated that those who completed 4-6 classes were more likely to lose weight than those who attended 2-3 classes. The cross tabulation showed that half (49.1%) of participants who attended 2-3 classes lost weight, but a lmost three-quarters (72.0%) of those who attended 4-6 classes lost weight. Finally, the relationship between weight change and f ood diary completion was also explored. In order to account for the varying att endance of participants, a percentage score was made for food diary completion by d ividing the number of food
70 diaries each participant completed by the number of fo od diaries he or she had the opportunity to do. In some cases the percentage exceeds 1 00% because some participants missed a class but turned in two food diarie s the following week. The box plot in Figure 9 shows food diary completion broken dow n by weight change status. It indicates that participants who were dedicated enough to do their food diary even when they missed a class all lost weight. At the same time, it also shows that most participants who gained weight did their food diary at least some of the time. It was in fact the people who experienced no change in weight that comple ted the fewest food diaries. Figure 9. Food Diary Completion by Weight Change Status
71 Figure 10 is a slightly different way of looking at the same information. Percentage food diary completion was broken into terti les, meaning that the 405 participants were ranked by their percentage food dia ry completion and then divided into three (roughly) equally sized groups. In this case, the bottom tertile consisted of participants who completed their food diary 20% of th e time or less, the middle tertile completed theirs between 20-66.66% of the time, and the upper tertile did their food diaries more than 66.66% of the time. The next chart shows the tertiles broken down by weight change status. Due to missing data regarding wei ght change status, the tertiles were no longer equally sized. Percentages are presented here in lieu of raw numbers to level the playing field. 102030405060708090100 Bottom tertile Middle tertile Upper tertile %Lost Weight % Maintained % Gained Weight Figure 10 Food Diary Completion Tertiles and Weight Change S tatus
72 Figure 10 shows an upward trend for food diary comple tion and weight loss Â– a greater percentage of participants in the upper terti le (who did their food diaries the most often) lost weight than those in the middle tertile, and a greater percentage of the middle tertile lost weight than those in the bottom tertile. It should be noted however, that almost 20% of participants in the upper tertile gained weig ht. A X 2 test for independence was calculated to see if the relationship between food diar y tertile and weight loss status was significant, and it was (p=0.000, n=340). Thus food di aries appear to help participants lose weight, but do not work for everyone. Change in Waist Circumference The same smaller sample of 405 was also used to calculate change in waist circumference. Figure 11 shows the change in waist circumfer ence among participants. Almost three-quarters of the sample (73.6%) either did not attend Week 6 or did not have a waist circumference measure recorded at Week 6, ma king it impossible to calculate change in waist circumference. For the 107 indiv iduals who did have both a beginning and ending measurement, 61.7% decreased thei r waist size and 29.0% decreased it by two or more inches. Another 22.4% main tained their waist circumference. Less than 10% increased their waist size whil e participating in the program.
73 50 100 150 200 250 300 350 Lost> 2"Lost 1.01.9" Lost 0.10.9" No changeGained 0.1-0.9" Gained 1.0-1.9" Gained > 2.0" Missing Figure 11 Change in Waist Circumference Of the 103 participants who had a beginning and endin g waist circumference measurement, 11 (10.6%) reached the waist circumference g uidelines during the program (<35Â” for women and <40Â” for men) (Centers for Disease Control and Prevention 2011a). Most participants (n=64, 62.1%) d id not meet the requirements by the end of the program; a little over a quarter of participants already met the guidelines when they entered the program (n=28, 27.2%). A X 2 test for independence was calculated to test if the change in frequency of meetin g the guidelines from pre to post was significant, and it was (p=0.000, n=103). However, it should be noted that this accounts for only 15% of the total sample and so may no t be true for all participants of GIFT. Only people who finished the program and atten ded Week 6 are included in these calculations, and completers may be different from not completers in important (but unknown) ways.
74 Finally the relationship between weight change and w aist circumference change was explored. The two variables significantly correlated (r=0.289, p=0.003, n=107), however the low correlation coefficient suggests that w eight change and waist circumference change are not strongly related. That is to say, weight loss does not necessarily go hand in hand with a decrease in waist circu mference and neither does the reverse. Additionally, a X 2 test for independence was calculated to test the relationship between weight loss status (gained, maint ained or lost weight) and waist circumference status (gained, maintained or lost inches). The result was significant (p=0.29, n=107) and the cross tabulation suggests that t hose who lose weight also tend to lose inches, but some people lost weight and gained inches. The results may be a bit unclear due to lack of consistent measurement of waist circum ference. When I assisted with measurement at Week 6, some participants who appea red to gain inches despite losing weight reported having been previously measured higher than their navel. Change in Knowledge Figure 12 shows the number correct, incorrect and missing for each question on the knowledge pretest. It uses abbreviated question st ems, but the full questionnaire can be found in Appendix B. Of the 664 participants, o nly 202 had pretests and the other 462 were missing. Correctness varied considerably across que stions, but in general participants entered the program with a fairly high level of knowledge. For seven of the ten questions, more than 70% of participants answered them correctly. Less than 50% of participants got the remaining three questions correct. One of those questions, question 9, was problematic. The question asks participants, Â“Pe ople with diabetes should keep their fasting blood sugar within which range?Â”, but th e lesson covers risk for and prevention of diabetes, not how to control the disease once acquired. A chart of Â“Guidelines for blood sugar or glucoseÂ” from the America n Diabetic Association is
75 provided in the lesson, but it is not clear if these are guidelines for diagnosis or management. Further, the answer choices provided do no t match the fasting blood glucose ranges in the chart. On three occasions during ob servations, I witnessed confusion and debate over this particular question, but not for any of the other questions on the pretest. Even CHAs were sometimes unsure of the answer, since no answer key is provided in the facilitatorÂ’s guide. For these reason s, this question was not included in the analysis of overall performance on the pretest. 100200300400500600700 "BMI" stands for: Healthy range of BMI Serving size of meat How many F/V daily? Which colors of F/V? Benefit of PA? Benefit of water? Risk factor for diabetes Fasting blood sugar Action to lower blood sugar Correct Incorrect Missing Figure 12. Knowledge Pretest Results The nine remaining questions were added together to create a sum score for pretest knowledge. A score of 9 indicates that participants got all nine questions correct, while a score of 0 indicates they did not answer any questions co rrect. Figure 13 shows the distribution of scores for the 202 participants who comp leted the pretest. Almost two-
76 thirds of participants achieved a score of 7 or higher, m eaning they answered at least 7 of 9 questions correctly. 10 20 30 40 50 60 123456789 Figure 13. Distribution of Knowledge Sum Scores for Pretest Only 35 participants completed the posttest, about 5 % of the entire sample. This is in part due to the fact that less than half of part icipants complete the program. Only 219 participants definitively attended Week 6 (when th e posttest is given), and data is missing for another 143 participants. Even if 219 is se t as the expected number of posttests (a generous approach), only about 16% are a ccounted for. Results gathered from so few participants is not necessarily representative of all participants of GIFT, so results from the posttests and comparisons with the pret ests must be interpreted with extreme caution. Generally, a 50% or greater response is needed to extrapolate from a sample to the entire population (Madrigal 1998). Su m scores were also calculated for
77 the posttest and are shown in Figure 14. Scores on the posttest were also high: 33 of 35 (or 94.3%) achieved a score of 7 or better. 5 10 15 20 25 30 35 40 123456789 Figure 14. Distribution of Knowledge Sum Scores for Posttest Only 22 participants completed the pretest and posttes t, making it difficult to ascertain whether knowledge improved for all participa nts of GIFT because such a small sample is not necessarily representative. Nevertheless, a W ilcoxon Singed-Ranks test was computed in order to test whether participants impr oved their knowledge sum score between the pretest and posttest. The result was signif icant (p=0.002, n=22), indicating that overall knowledge did improve. However, this t est did not reveal which questions participants demonstrated improved knowledge on. Nor did it reveal whether participants were consistent in their knowledge between the preand posttest (i.e. participants who answered a question correctly on the pretest should theo retically also get it correct on the posttest). Figure 15 has the item analysis for all ten questions for the 22 participants
78 who completed both the pretest and posttest. It is f ollowed by Table 2 that serves as a key for the graph. Again, the data suggests that part icipants enter the program with a high degree of knowledge. 510152025 "BMI" stands for: Healthy range of BMI Serving size of meat How many F/V daily? Which colors of F/V? Benefit of PA? Benefit of water? Risk factor for diabetes Fasting blood sugar Action to lower blood sugar Correct-Correct Incorrect-Correct Correct-Incorrect Incorrect-Incorrect Figure 15. Item Analysis for Knowledge Questionnaire Table 2. Key for Knowledge Item Analysis (Figure 14) Color Pretest Posttest Meaning Blue Correct Correct Entered the program with knowledge Green Incorrect Correct Knowledge increased Orange Correct Incorrect Either 1) Â“lucky guessÂ” on pretest but knowledge did not actually increase, or 2) the question is flawed Red Incorrect Incorrect Knowledge did not increase
79 Using the information in Figure 15 above, FisherÂ’s Exa ct Tests were used to test for change in knowledge for each individual question. Tabl e 3 has the results of each of the tests. Table 3. FisherÂ’s Exact Tests by Question Abbreviated question stem Significant P value Sample size (n) 1 Â“BMIÂ” stands for: No 0.091 22 2 Healthy range for BMI? No 1.000 22 3 Serving size of meat? No 0.135 22 4 How many F/V daily? No 1.000 22 5 Which colors F/V? No 1.000 22 6 Benefit of PA? No 1.000 22 7 Benefit of drinking water? No 0.091 22 8 Risk factor for diabetes? No 0.182 22 9 Fasting blood sugar? No 0.165 22 10 Action to prevent diabetes? No 1.000 22 None of the tests were significant, meaning that the gains in knowledge seen above in Figure 15 could be due to chance. The results a re probably not significant because scores were so high on the pretest there was littl e room to grow and gain knowledge. Table 4 below demonstrates this well: it sho ws the percentage of correct answers for each question on the preand posttest for the 22 participants who completed both. The pattern of a high percentage of co rrect answers on the pretest and even higher percentage for the posttest indicates that the instructional complexity was too low (Virginia Tech 2009). In other words, the lesso ns were too easy. Ideally, there should be about 15% correct answers on the pretest and 85 % on the posttest (Virginia Tech 2009). A drop in the percentage of correct responses from pretest to posttest like
80 the one seen in question 9 suggests that the question i s defective (Virginia Tech 2009). This corroborates with the problems with this question di scussed earlier. Table 4 Percentage of Correct Answers on Preand Posttests Question % Correct PREtest % Correct POSTtest 1 Â“BMIÂ” stands for: 90.0 95.4 2 Healthy range for BMI? 54.5 81.8 3 Serving size of meat? 81.8 81.8 4 How many F/V daily? 54.5 86.4 5 Which colors F/V? 86.4 100.0 6 Benefit of PA? 100.0 100.0 7 Benefit of drinking water? 90.9 95.4 8 Risk factor for diabetes? 81.8 95.4 9 Fasting blood sugar? 40.9 31.8 10 Action to prevent diabetes? 95.4 100.0 Fruit and Vegetable Consumption The way in which self-reported fruit and vegetable con sumption is measured was changed twice during the 1 year period the data was pu lled from, complicating analysis considerably. It used to be that daily fruit and veget able consumption (in cups) was measured alongside the ten knowledge questions on the preand posttests. Currently, consumption is assessed on the Where Am I? Form in Week 1 and the Evaluation Form in Week 6, but in very different ways. Further, the a nswer choices in the Evaluation Form changed as well, going from a yes/no dichotomy to a lik ert-scale (Â“strongly agreeÂ” to Â“strongly disagreeÂ”). Many of the question stems remaine d the same, but not all. As described in the methods section, data were combined from the older and newer versions of the Evaluation Form when possible. In some i nstances it could not combined
81 because the questions were not similar enough, so it is simply reported as is. Change in fruit and vegetable consumption could not be assessed beca use: 1) consumption is measured differently in Weeks 1 and 6, and 2) data coul d not be matched because Evaluation Forms are anonymous. Starting with the older question on daily consumption from the preand posttest, 89 participants answered on the pretest, but only 2 on the posttest. Due to the negligible data for the posttest, only the pretest data is shown in Figure 16. Although guidelines for fruit and vegetable consumption have recently changed and are now tailored for age, sex and activity level, previous recommendations called five or more servings of fruits and vegetables daily (Centers for Disease Control and Prevention 2008; Centers for Disease Control and Prevention 2011d). It appears tha t at least 58% of the people who answered this question were not meeting this guideline when they started the program. The additional 39% who reported eating more than 3 cups (but presumably less than 7) may or may not have reached recommended consumption. How many fruits and vegetables do you eat daily? 5 10 15 20 25 30 35 40 45 50 I don't eat fruits and vegetables More than 1 cupMore than 3 cupsMore than 7 cups Figure 16. Beginning Fruit and Vegetable Consumption as Measured by the Pretest
82 Turning to the current assessment methods for fruit and vegetable consumption, the Where Am I? Form during Week 1 asks Â“On average, do you eat a total of five (5) fruits and vegetables each day?Â” Â“YesÂ” and Â“noÂ” are the only response choices. Of the 201 participants who filled out this form, most (155 or 77.1%) reported they did not eat 5 servings a day. Of the remainder, 38 (18.9%) reported they did indeed eat 5 five servings of produce a day, and 8 (3.9%) chose not to answ er this question. Finally, the Evaluation Form in Week 6 asks, Â“Have y ou increased your fruit and vegetable consumption?Â” The answer choices provided are Â“ yesÂ” and Â“noÂ”. Of the 187 who filled out this form, the majority (113 or 60.4% ) reported that they did increase their consumption. Only 4.2% (8 participants) said that they did not, and 35.3% (66 participants) chose not to respond. Physical Activity Many of the same issues that impacted the fruit and vege table consumption analysis were also apply to physical activity. Like fruit and vegetable consumption, the physical activity used to be measured alongside the ten kn owledge questions on the preand posttests. Currently, physical activity is assessed on the Where Am I? Form in Week 1 and the Evaluation Form in Week 6, but in very di fferent ways. The Where Am I? Form asks as series of three questions where participants are asked first if they engage in physical activity, then how many days per week, and fi nally how many minutes each session. This series of questions is not repeated on the Ev aluation form and instead participants are asked to retrospectively assess whether th ey have increased their physical activity. Beginning with the older question on weekly physical activity from the preand posttest, 88 participants answered on the pretest, but o nly 2 on the posttest. Due to the negligible data for the posttest, only the pretest da ta is shown in Figure 17. The
83 responses to this question are difficult to interpret b ecause the answer choices do not account for all possibilities. For example, person who go es for a 30 minute walk 3 times a week may have a difficult time choosing an answer. That being said, a little over half of the participants who answered this question probably di d not meet CDCÂ’s recommendations for physical activity for adults when they started the program (150 minutes of moderate exercise or 75 minutes of vigorous activity per week) (Centers for Disease Control and Prevention 2010). This question do esnÂ’t discern between vigorous and moderate physical activity, so it is difficult to te ll if the participants who were active 20 to 30 minutes 4 times per week were meeting the guideline when they entered the program. How much time are you engaged in physical activity over a week? 5 10 15 20 25 30 35 40 45 50 I don't exercise10 to 20 min 1x a wk20 to 30 min 4x a wkMore than 30 min a day Figure 17. Beginning Physical Activity Level as Measured by Pretest Turning to the current assessment methods, Figure 21 show s the results from the series of question on the Where Am I? Form. These results reflect only the 201 participants who filled out this form; missing responses r efer only to those who filled out
84 the form but skipped this particular question. More than half of participants (59.7%) who filled out this form reported being physically active at the start of the program. Many in the missing category were placed there because the partici pant circled both yes and no. The binary nature of this question doesnÂ’t allow peop le to express that they exercise sporadically. Do you exercise? 20 40 60 80 100 120 140 YesNoMissing Figure 18 Physical Activity Participation as Measured by the Whe re Am I? Form Those who reported exercising were asked to answer two additional questions regarding the number of days per week they were physi cally active, and how long they exercised each time. Figure 19 shows the results for the 120 participants who were active at the start of the program using the response ch oices provided to participants. Due to the ambiguity of the answer choices, it is impossi ble to calculate the numbers of minutes of physical activity participants were engaging in when they entered GIFT. For example, more than 30 minutes could mean anything be tween 31 minutes and several hours of physical activity. However, estimating from th is chart, it does appear that many
85 of the participants who completed this form are probab ly not meeting the CDCÂ’s recommendations for physical activity. 102030405060 1-2 days3-5 days6-7 days <30 min 30 min >30 Figure 19. Beginning Physical Activity Level as Measured by the Whe re Am I? Form It is difficult to make generalizations about how much physical activity participants engage in when they start the program d ue to both the limitations of the questions used to assess physical activity, and the relativ ely small amount of data. The database contains information about beginning physical a ctivity for less than half of all participants (289 of 664 participants). As discussed pre viously, a response rate of 50% or greater is generally needed to make inferences abo ut the entire group. Bearing this in mind, the data suggests that most participants are proba bly not meeting CDC recommendations for physical activity and some are not phy sically active at all when they begin the program. Since the questions on the Where Am I? Form are not i ncluded at Week 6, the only indication of change in physical activity level dur ing the program comes from the
86 Evaluation Form. Like fruit and vegetable consumption participants are asked to retrospectively assess whether they have increased their p hysical activity level using the question Â“Have you increased your physical activity/exer cise?Â” Â“YesÂ” and Â“noÂ” are the only response choices. Almost half (101 or 46.1%) of 18 6 participants who filled out the evaluation form reported that they increased their ph ysical activity, while 10.2% (19 participants) did not and 35.3% (66 participants) chose not to answer this question. However, it should be noted that only about one-thir d of people who participated in the program filled out this form, so these results may not b e representative of everyone who participated in GIFT. Program Satisfaction The Evaluation Form contains several questions to assess pa rticipantsÂ’ satisfaction with their Community Health Advisor (CHA ), the teacher/facilitator of the program. As previously discussed, the evaluation form chan ged during the 1 year period selected for analysis, but most questions regarding progr am satisfaction remained the same. Figure 20 shows the results of these five questions f or the 121 participants who completed either the older or current version of the E valuation Form. Participants were overwhelming satisfied with the performance of their CHAs, with more than 85% agreeing or agreeing strongly all for questions.
87 Did the Facilitator... 20406080100120140 Answer your questions? Make the sessions fun? Knows the materials well? Show concern for you? Strongly disagree Disagree Agree Strongly Agree Missing Figure 20. Satisfaction with CHAs as Measured by the Evaluation Forms Although many of the questions on the older and newer versions of the Evaluation Form were nearly identical, the older for m contained some additional questions that are no longer used. Namely, the older version of the Evaluation Form asked participants to rate each of the GIFT lessons from Week 2-6. Figure 21 shows the responses of the 71 participants who completed this exerci se. This chart accounts for only about 10% of total participants in the sample, so these results are not necessarily true for the entire population of people who have p articipated in GIFT. Nevertheless, the results do suggest that participants were satisfied wit h the lessons.
88 1020304050607080 BMI Portion Control Fruits and Veg PA and Water Diabetes Prevention Strongly disagree Disagree Agree Strongly Agree Missing Figure 21. Ratings of GIFT Lessons The current version of the Evaluation Form asks three additional questions to solicit feedback from participants about the program. Th e results are presented in Figure 22. Of the 51 participants who filled out this version of the Evaluation form, a strong majority held favorable views about the way the info rmation was presented, the length of the class sessions, and their opportunities for participat ion.
89 102030405060 Was the information presented in an understandable way? Was there enough time allowed for each session? Did the presentations allow you to participate? Strongly disagree Disagree Agree Strongly Agree Missing Figure 22. Feedback on Program Elements Other Outcomes Although goal setting is an important activity in W eek 1, progress towards goals is not tracked during the program. Instead, the eval uation form asked participants to assess whether or not they met the goals they set for the mselves. Of the 187 participants who completed the Evaluation Form, 38.5% (n=74) reported meeting their goals. Another 38.5% (n=72) did not answer this quest ion, probably because the answer choices do not account for all possibilities. For example, a person who met some of their goals but not all of them, or made progress towards th eir large goal but did not achieve it would have difficulty answering a simple Â“yesÂ” or Â“noÂ”
90 Finally, two questions assess whether GIFT has helped p articipants achieve better health in a general sense. Of the 121 participa nts, the 91.7% (n=111) reported feeling healthier and 94.2% (n=114) felt the inform ation presented in GIFT useful in leading a healthier life. Participant Observation Out of the 40 hours of participant observation and a ccompanying fieldnotes, it became clear that CHAs are operating out of an individu alistic, public health paradigm. They tended to dismiss the idea that policies or finance s could hold people back from being healthy. Â“You just have to seek it outÂ”, one CH A said as she explained why she felt that everyone already had access to affordable food. F or the most part, participants agreed with this perspective. They felt that their di et and physical activity level were under control, and a lack of progress represented a perso nal failing. There were some pockets of resistance, such as the woman who repeatedly t old the class, Â“I donÂ’t know why IÂ’m fatÂ”. She felt she didnÂ’t eat much and was alw ays on the go, so she was already following the Â“eat less, move moreÂ” prescription. Anot her woman who struggled to lose even a little weight exasperatedly told the CHA one day, Â“ItÂ’s our age, tell the truth.Â” She felt that as you got older it got harder to lose wei ght. These were exceptions, though to the generally individualistic discussions. The greatest source of contention was around ideal or Â“ healthyÂ” weight. The program uses BMI categorizations, which most seemed CHAs a gree with, or at least didnÂ’t oppose. One, however, told her group that hea lth and weight werenÂ’t directly related: you could be thin and not be healthy, and co uld be healthy without being thin. Participants tended to enter the program with an ide al weight in mind. They were sometimes surprised, or even shocked, by what was considere d a healthy weight for their height, but were not convinced that this really applied to them. Many participants
91 talked about an ideal weight well above the Â“health y weightÂ” threshold on the BMI chart. One group even had a discussion about how they would lo ok Â“sickÂ” or Â“weirdÂ” if they lost too much weight. Similarly, in another group several Hispanic women felt the waist circumference guidelines were unrealistic. According to one woman in the group, in her experience no one over the age of 10 has a waist under 35Â” (the recommendation). She felt that this universal guideline for all women did nÂ’t take into account bodies of all shapes and sizes and ethnicities. Regardless of the explanatory model employed, CHAs, p articularly the paid ones, were very dedicated. They checked up on participa nts who didnÂ’t come, making multiple phone calls if necessary, and made themselves ava ilable outside of class if participants needed advice or support. The CHAs were et hnically diverse and often matched the background of participants, which allowed fo r better discussions of variations or substitutes of specific ethnic foods or dish es. For instance, one group had frequent discussions of ways to prepare soul food dishes in healthier ways. However despite their enthusiasm, commitment and abili ty to relate to participants, some CHAs struggled to facilitate conversati on among participants. Facilitation is a very different skill set from teachin g or instructing, and without any training in facilitation, many would default to talk ing about themselves. While revealing personal struggles and solutions humanizes CHAs and can se rve as an initial starting point for the group conversation, some CHAs repeated th e same anecdotes and personal strategies week after week. Further, some strug gled to deal with strong personalities and talkative participants who liked to d ominate the conversation. There are multiple paths to a healthier lifestyle, and par ticipants would probably benefit more from hearing more about all of the other participant sÂ’ experiences and sharing their own. Regarding knowledge and the lessons, it became very cle ar during the observations that the vast majority of participants ent er the program with a good working
92 knowledge of nutrition and the mechanics of weight lo ss. They already knew to cut back on soda, sweets and fried foods and to eat more fruits and vegetables. Most were experienced dieters, and knew all too well that losin g weight requires eating less and exercising more. In fact, four different participants m ade the point that they knew what to do, they just had trouble actually doing it. Moreover, many participants actively sought health information outside of class. They talked about things they had learned from health-oriented shows like The Dr. Oz Show and The Doctors as well as segments on television news programs. In each of the three case study groups, there was at least one person who was so knowledgeable that he or she could hav e taken over as CHA given a momentÂ’s notice. Since the knowledge level of these par ticular participants and CHAs was essentially equal, there were occasionally tense momen ts when CHAs felt they were being usurped. Â“Would you like to teach the class?Â” one CHA asked pointedly after a participant interjected additional information one too many times. It is from this wealth of prior knowledge that partici pants are able to give each other informational support. Participants seemed to re ally enjoy sharing their tips and tricks, everything from specific foods to try, like a low-fat salad dressing that Â“actually tastes good!Â” to concrete suggestions for how to deal wi th challenges, like the siren call of the candy dish on a co-workers desk. Emotional support was frequently given by both participants and CHAs. Successes and progress (no matter ho w small) was met with praise, while encouragement was given to those who faced setbacks and disappointment. In many groups I worked with, partici pants were remarkably open about their weight, indicating a supportive, trusting atmosp here. However, not all groups achieved this supportive atmosphere. There was one group with whom I did not personally interact, but during the statistical analysis I noted that they mailed their food diaries in individual envelopes so that no one else coul d see what they had eaten or what they weighed. Groups that dwindled down to only 1 or 2 participants also lost out
93 on this on the support aspect of program. Â“We need to get more people in hereÂ”, one participant told me when she was the sole attendee one week. The major difference between workplace wellness groups and community groups relates to the social support aspect of the program. The preexisting relationships of a workplace wellness group are both a help and a hindran ce. Since they are more comfortable with each other, participants of workplace gr oups are able not only to cheer each other on, but also to give appraisal support (thro ugh teasing) when someone is not in line with the groupÂ’s professed goals. At the same t ime, the hierarchical nature of workplaces can interfere with the social support, since pa rticipants are not on an even playing field. The employer was advised not to allow m anagers or supervisors to be CHAs in order to avoid tying job performance to weigh t loss. This advice was heeded, and the feedback from their internal survey indicated that the CHAs with lower positions really enjoyed the opportunity to be a leader. In c ontrast, in the community groups teasing was virtually nonexistent. Instead participants s tuck to positive emotional support, and never progressed to the point where they were able to use teasing to provide appraisal support. GIFT does an excellent job of meeting participants need s in certain areas. Social support is one example; the group gives participants a su pport system for a challenging transition to a healthier lifestyle. Leadership at Hil lsborough County Health Department also doing a good job of recruiting CHAs that understa nd and respect participantsÂ’ varied cultural/ethnic backgrounds. The program also provides an opportunity for physical activity, which reinforces the point that good health i nvolves both good nutrition and physical activity. In other ways, however, the program does not always me et participantsÂ’ needs. Although CHAs themselves are culturally competent, the p rogram materials in Week 1 could be improved. The materials give sample menus for four different calorie levels for
94 the mainstream American diet, but only two levels for Â“AsianÂ” and Â“SpanishÂ” foods. Soul food, which was discussed extensively among the African-Ame rican participants, is not included at all. Additionally, challenges regarding the cost and availability of produce and places to be physically active are not explicitly add ressed by the program but were brought up by participants during class. Similarly, part icipants would occasionally talk about emotional eating as a challenge, but this is not included in the program. Probably the biggest issues participants faced related to family, friends and social situations. Again and again participants talked about the difficul ties attending social functions involving food and the challenges of living with other s who were not willing or ready to change their eating habits. There is one lesson on strat egies for social functions but it is not offered until Week 20 of the program, although so me CHAs teach it in November or December as preparation for the holidays. Additionally, the program, in many respects, fails to engage participants. Many CHAs went above and beyond their required duties and added additional components to the program to make the experience better for partici pants. Several CHAs of the workplace wellness groups did internet research to supplem ent the materials in the lessons, which were Â“too skimpyÂ”, as one CHA explained to me when we were chatting one day. She went on to explain that the materials were Â“a good jumping off pointÂ”, but there was better and more interesting information on the internet than what was included in the lessons. Another CHA asked every participant to bring in an unusual vegetable for everyone to try, but ultimately decided she didnÂ’t wa nt to continue as CHA for Session II because she felt her classes were boring. She envisioned h erself coming up with all kinds of fun activities for the group, but ended up j ust doing a lot of talking. A third CHA showed a video, did a cooking demo and suggested a conte st. Â“We can talk all day, but you need to see things, taste them, smell themÂ”, she ex plained when she announced the cooking demo. One CHA openly asked participants why the y werenÂ’t participating more
95 fully, and wondered aloud if she needed to get tough er on them. I watched groups dwindle in size before my very eyes, and eventually se ttle on a small core group that attends regularly. Interestingly, both grocery store tours (in Week 11) had unusually high attendance. That is not to say that participants did not benefit from being in the program. Often in Week 6 participants would be in a reflective mood as we took their measurements and compared them to Week 1 and shared with use the ways in which they have improved their health. Participants describe d cutting back on soda, drinking more water, switching to whole grain pasta and bread, eating more regularly, walking more, becoming more aware of portion sizes, planning m eals, eating more vegetables, and cutting back on condiments, among other improvemen ts. One woman talked about having to learn to Â“not be so cheapÂ” at the grocery sto re because produce cost more than the packaged food she used to buy. Semi-Structured Interviews Background and General Thoughts The sample consisted of seven participants who completed the program and ten who did not. Of the completers, six came from workplace wellness groups and one came from a group held at a community center. Six completer s were female and one was male. Of the non-completers, four came from workplace wellness groups and six came from community groups. Nine were female and one was m ale. By my estimation, all participants were between 30 and 70 years of age. Tw o of the participants (both completers) were also volunteer CHAs. Unlike paid CHAs who are seen as a clear authority, volunteer CHAs are the first among equals a nd participate in all aspects of the program (including weighing in, completing the food d iary, setting weekly goals, etc) as well as act as instructor and facilitator.
96 As a general opening question, participants were asked t o generally describe their thoughts about the program. A strong majority (16 of 17) held a positive opinion of GIFT. Among both completers and non-completers, the socia l aspect of the program was the most commonly praised element (3 completers and 4 non-completers), followed by the information (2 completers and 1 non-completer) As the completer from the community group explained, the program Â“gave me mor e information, of course some I already knew, but to hear it, to share it with other people who are trying to battle the same thing I am, which is, you know, weight and losing weight and getting healthier and eating healthier. It was great to be in that environ ment and see other people, people actually of different ages.Â” However, four participan ts felt the program was good but then went on to describe flaws or limitations. There was no real consensus: one wanted the program to have more structure, one already knew all of the information presented, another wanted to make it clear that the program simp ly reinforced her preexisting good habits, and the fourth was too exhausted from work to attend. No one, even among the non-completers, expressed an outright negative opinio n. The closest was a noncompleter who felt the program was only Â“okayÂ” because of its short length, but went on to praise her CHA. Reasons for participating in GIFT were varied. Those wh o were in workplace wellness groups tended to talk about purposefully seekin g a group setting in order to increase their motivation Â“get back on trackÂ” or become more accountable. As one participant explained, Â“I need something right now ju st to get myself motivated again. I have been on the Weight Watchers and IÂ’ve been on, y ou know, other routines for a while, for many years, and IÂ’ve just sort of gotten o ff it all. I would like to, you know, get myself back on track. And the fact that you go and you Â’re talking about it with other people, keep you accountable in the sense that you have to weigh in and you know, you weigh yourself, and youÂ’re conscious of that and have a goal for each week. That helps
97 me.Â” Those from community groups (both completers and n on-completers) tended to enter the program because their doctor referred them. Most participants, regardless of their completion status or group location, joined in or der to improve their health or lose weight, but three participants talked about wanting t o help others as well, either through modeling their own good habits and encouraging others or by sharing what they learned with friends and family. As one person explained, Â“[I joined] in order to really help because there are other people that I know that have questions about this but didnÂ’t have this at their availability.Â” Once participants decided to participate, they set goals f or themselves during the first week of the program. Unsurprisingly, the most com mon goal was to lose weight (10 of the 13 participants who answered this question). Those from community groups were very upfront about their desire to lose weight. There was an almost perfect overlap between people who were referred by their doctor an d their main goal being weight loss. Three of the nine (all workplace wellness participants) only listed weight loss as a goal after probing. Those three, along with the other wor kplace wellness participants, tended to view the program as a Â“jump startÂ” or a way to ge t Â“back on trackÂ” with a healthier lifestyle. Two (a non-completer and a completer) wan ted to not only lose weight, but maintain it. Explained one participant, Â“Losing weigh t was my primary goal and to do it in a way where I can maintain the loss because in the past IÂ’ve done programs where you know you lose it fast but then it comes right back.Â” H ealthier eating was also a popular goal (5 participants), specifically eating more fruits a nd vegetables. Only two participants, both completers, sought to increase their health knowledge. All of the participants had at least some previous expe rience dieting, and many described themselves as habitual dieters. There were no real differences between completers and non-completers. Â“IÂ’m a all year round, u p and down, see-saw dieterÂ”, explained one completer, while another said, Â“Name [a diet] and IÂ’ll tell you if IÂ’ve done it
98 or not. IÂ’ve done Weight Watchers, IÂ’ve done TOPS, IÂ’ ve done Atkins, IÂ’ve done South Beach. Years ago I went to some diet dude, some doctor a nd got like B12 shots injections and got medicines. This was like back in Â’80Â…IÂ’ ve pretty much run the gamut.Â” Weight Watchers was the most common formal program par ticipants had tried (3 participants), but others described individual efforts (6 participants). No one described any success stories; their previous diets either didnÂ’t wo rk in the first place or they gained back some or all of the weight. As one non-comp leter explained, Â“I lost some weight back in Â’99. I lost 55 pounds but then I gain ed it all back and then some. I went on a Weight Watchers diet.Â” When asked to describe how participating in GIFT was d ifferent from their previous weight loss efforts, four of the five non-com pleters who answered this question felt that the group setting or social support offered b y the program set it apart. As one non-completer put it, Â“This was my first time ever goi ng to like a group session or something like that. It was basically always you know my own will power.Â” There was very little consensus among completers: one felt it wasnÂ’ t any different, another felt GIFT was inferior to Weight Watchers because it was less struct ured and more casual, and others talked about it being more interactive, and having a less restrictive dieting plan. Feedback on Program Elements Participants were also asked to voice their opinions on a variety of aspects of the program. When asked to describe the most useful thing they learned in the program, three of the seven completers interviewed responded no t with information from the lessons as I had (perhaps naively) expected, but strategie s that they had learned though interacting with the group, completing the weekly acti on plan, or filling out the food diary. As one completer explained, Â“I think the most useful t hing that I learned was that being with the group encouraged you more and gives you more self-esteem into doing what
99 you should be doing when it comes to your meals. They encouraged you, they introduced different recipes also which actually, you kno w, you donÂ’t get bored with the same stuff that youÂ’ve been doing and it helps. I thin k thatÂ’s, thatÂ’s what IÂ’ve learned from this.Â” None of the completers had anything nega tive to say about the lessons, although two could not recall the topics covered or what specifically had been most useful. One of those participants couldnÂ’t recall Â“offha ndÂ” anything from the lessons that was particularly useful, but said Â“I thought the educati onal materials were very helpful. You know, as far as taking them home and reading them I thought there was a lot of good points that I wasnÂ’t aware of or just made me consi der different aspects of what I was doing.Â” Even one of the volunteer CHAs who supple mented the lessons with additional information gleaned from the internet ha d nothing but praise for the lessons. She had this to say: Â“Even if it wasnÂ’t necessarily in the book that we we re given, once you went into the websites and things like that you were a ble to find additional information in addition to what was in the manual an d the book itself. And so you were able to kind of expand on what was in the lesson plan just based on the other tools and the resources that was liste d. So the lesson plan, I think it went, it delved deep enough into ea ch section, each subject to get a very good understanding of everything like t he BMI. And even the diabetes portion, and you know your numbers and knowi ng your numbers and things like that. So I think that the lesson plan w as well-written and I think it was very informative.Â” The responses of non-completers in many ways resembled th e completers. Four of the six who answered this question talked about wha t they learned from the lessons. Those who attended only once talked about learning Â“w hat to eatÂ”, which is to be expected since the first lesson is essentially a crash course i n nutrition. Explained one woman, Â“I guess what types of food you should eat and all that. You know, what foodÂ’s you shouldnÂ’t eat Â– thatÂ’s what it is.Â” The other two non-complete rs talked of what they learned through the food diary and from the support of the other participants.
100 Conversely, when participants were asked what the least useful thing they learned nearly everyone, completers and non-completer s alike, either couldnÂ’t think of anything or felt everything was useful. Explained one completer, Â“I canÂ’t think of anything that I felt was well Â‘Why are we bothering with that ?Â’, that type of thing.Â” Another completer echoed that sentiment, saying Â“No, I donÂ’t t hink anything was not useful. Any time youÂ’re getting information about your health i tÂ’s going to be useful, depending on how you want to use it.Â” A non-completer felt similarl y and said Â“Everything was useful. Not one thing was taught that wasnÂ’t useful because I fe lt like this: if I didnÂ’t get something out of it, somebody else probably did.Â” Two non-completers felt that they hadnÂ’t attended enough classes to make a judgment in th is regard. Only one person offered any sort of criticism of the educational compone nt. This person took issue with the BMI lesson, calling it Â“destructiveÂ”. Because his ideal weight still falls within the overweight category, he felt it makes you think you w ill never reach your goal. He went on to say that Â“when you look at that chart it takes a way your whole sense of accomplishmentÂ” and that BMI was Â“unrealistic for my body type.Â” Although participants by and large held positive views of the lessons, every single participant reported that they knew most of the information covered prior to the program. One completer put the general feeling best, Â“There was very little information that I didnÂ’t already know before. I mean there wer e a couple of things here or there that that I was like Â‘Oh, I didnÂ’t know thatÂ’, but most o f it was, um, pretty general. But I guess if you donÂ’t know that stuff itÂ’s, you know, a lot.Â” Among the completers, anything new they learn tended to come from additional elements th eir facilitator brought to the program, like internet research or exercise techniques (such as the P90X workout system). Two felt that the lesson on portions provided n ew information, like the completer who said, Â“That was really new to me, cause IÂ’ ve always practiced eating small quantities and throughout the day, but not rea lly into a program where it taught you
101 exact portion size. And I think that was very beneficial .Â” One person felt that the benefit of the lessons wasnÂ’t from the Â“newnessÂ” of the informat ion, but the perspective from which it was taught. She explained, Â“And it made you look at it from a health standpoint more so than just about losing weight. So even if you donÂ’t lose the weight, if you make healthier choices, youÂ’re still becoming more healthy y ou knowÂ… I really hadnÂ’t looked at it from the standpoint of incorporate this because itÂ’s better for your health. Although I know fruits and vegetables are good for your health, but I guess I always thought if you reduce your calories, you know, that was good enough.Â” The non-completers also felt that little was new to them, but they also singled out the portions lesson (2 participants) and the food diary (2 participants) as new and valuabl e information. Interestingly, despite the lack of new information, few participants were disappointed with the programÂ’s offerings. When asked i f there was anything they hoped to learn but didnÂ’t, most either couldnÂ’t think of any thing (2 participants) or felt that the program met their expectations in this regard (2 parti cipants). As one woman put it, Â“Â… I only went through the six weeks, so for what it covered in the six week period was, you know, fineÂ…I really canÂ’t think of anything that could have been included that wasnÂ’t.Â” The other completers varied in what they were hoping to learn: one wanted more about food combinations that would promote weight loss, anot her wanted more on supplements and micronutrients and the third wanted a Â“mythbustersÂ” week that covered fad diets and why they donÂ’t work in the long-term. He explained, Â“itÂ’s really hard to eat from the food pyramid when you see people eating baco n and hamburgers and losing weight.Â” The non-completers had more topics they wished to learn about, but two felt that it was not fair for them to speculate because they had not completed the program and seen all of the lessons. Of the others who answered this question, one felt Â“they told me everything I needed to knowÂ”, but two wanted to learn exercise techniques and one
102 wanted information on what to eat to help control he r diabetes in addition to learning cooking skills. When it came to the social support portion of the progr am, the majority of interview participants (12 of 15 who answered this qu estion) enjoyed and benefitted from it. Most talked about being able to share their probl ems or the benefits of hearing othersÂ’ stories and challenges. As one non-completer put it Â“Wel l just a little bit more encouragement helps me, you know helps me out, helps m e get along a little better. When I see other people having kind of the same kind of issues that I have, you know, and how theyÂ’re able to you know take over and do w hat needs to be done for them, that kind of thing.Â” Three talked of encouraging each other and celebrating each others successes. Explained, one facilitator, Â“And I guess the other thing as a facilitator, it gave us a kind of opportunity to build a bond and encourag e behaviors and try to keep them on track.Â” Two (both completers) had less than positive feelings about the sharing. One Â“didnÂ’t feel comfortable with itÂ” and didnÂ’t find th e sharing to be very meaningful for her and the other felt ambivalent, explaining, Â“That di dnÂ’t really, you know, concern me one way or the other.Â” The third was a non-completer who couldnÂ’t comment because there wasnÂ’t any sharing in the one class she attended. Unsurprisingly, all eight who participated in workplace wellness GIFT groups (both completers and non-completers) and answered this question knew at least some of the people in their group prior to the program. Five said that they were comfortable talking about their weight and their weight loss with co-workers. Explained one, Â“IÂ’m kind of an open person and I find that you get more when youÂ’re able to give and share, so thatÂ’s why I found it beneficial to open up to people Because youÂ’re kind of a generator flow for other people and IÂ’ve found out different things from other folks too.Â” One did not feel comfortable with it, and preferred a program li ke Weight Watchers that does not include people she interacts with on a daily basis. Those from community groups
103 generally did not know anyone in their group, altho ugh one person came to the class at the urging of a friend. Of completers, four no longer kept in touch with the people in their group (or at least stopped talking about weight loss or health with those people), with one citing lack of time and the other three simply moving on from GI FT. However, three completers kept in contact informally with at least some of the others in their group. One participant said they Â“just check in with each other, like a little accou ntability thing.Â” Another explained, Â“Well I can say that we donÂ’t as much as we probably shou ld but I do know that we still kind of you know still say every now and then Â‘Are yo u drinking any water?Â’, Â‘Are you eating your food?Â’. We still ask those questions [laug hs]. You know, and we still try to encourage each other but we donÂ’t really Â– as a matter of fact I think the last thing we did was share recipes and that was since the class ended, we sha red some recipes with each other.Â” Among the non-completers, two from workp lace wellness groups still kept in contact with people in their group, but the ones from community groups did not. The final portion of the program consists of some sort of physical activity. For the most part the completers spoke positively of the physical activity portion of the class, but some drawbacks were mentioned including the small space in which the classes were held, an exercise that hurt a participantÂ’s back, and d isappointment that there wasnÂ’t organized physical activity outside of class (such as a walkin g group). These two volunteer CHAs described their efforts to come up with each weekÂ’s physical activity portion. One mined workout DVDs for exercises, while ano ther expressed concerns over finding activities that would suit everyone (a struggle that I shared when acting as a CHA during my internship). As she put it, Â“I donÂ’t think i t was a deficiency on GIFTÂ’s part or anything like that, but I was concerned I was doing thi ngs that everybody was interested in. But everyone seemed to appreciate the things that were brought forward.Â” Several of
104 the non-completers were unable to comment because they did not do any physical activity the day they attended, but the two that did had positive things to say. Everyone at least attempted to fill out the food dia ry, although some were more consistent than others. Two described themselves as Â“not go od at itÂ”. As one completer put it Â“IÂ’ll start the day off good, and then as you go along you get busy and you know you get involved and IÂ’m just not as conscientious abou t it as I would like to be.Â” All five of the non-completers who answered this question talked about doing it for a short while and then stopping. There was this idea that the food d iary was helpful, but not something that needed to be filled out for weeks on end. As on e non-completer put it Â“Â‘Cause I wrote it down a coupleÂ’a times and I just started doi ng it. I just started Â– right now IÂ’m still eating right. I might cheat once in a while but itÂ’s n ot like every day IÂ’m eating fried chicken. You know I might eat fried chicken once a month. Â” Regardless of whether they completed the food diary once or all six weeks, all of the participants drew benefits from the food diary. The most common benefit was becoming m ore conscious of eating (7 participants) and another two participants talked of u sing the diary to uncover where their diet was going wrong. As one non-completer put it, Â“Â’Cause you got a chance to actually see what youÂ’re eating wrong. Â‘Cause a lot of times you eat, youÂ’re just eating and you donÂ’t even think about it at all. And so you write out a food diary, you kinda you know see what went in and how it should be, that kin d of thing.Â” Others talked of the food diary helping them to snack less, be more cognizan t of portion sizes, and serving as a tool to keep on track. All participants were asked if they were able to atte nd all sessions, as a nonjudgmental way to address why participants did not compl ete the program. All six of the completers attended at least five of the six classes in Sessi on I, but one person talked about having to Â“make an effortÂ” to attend some week s because of work demands. The non-completers talked of a wide variety of reasons for not finishing the program. Three
105 of the four non-completers from workplace wellness group s talked about work demands impeding on their ability to attend, despite the fac t that the groups are generally held during lunch hour or before work. The other workplace wellness non-completer stopped attending because the class took place on Â“her timeÂ” rathe r than the companyÂ’s time and she had other personal matters to attend to. Among th e community group noncompleters, there was no consensus at all: two experienced health problems that reduced their mobility, one was too tired after work, one lacked money for bus fare to get to class and a third felt the time and location was too inconvenient to continue attending. Another went out of town and assumed the class was over w hen his CHA didnÂ’t call to remind him about the next class. The final non-complete r attended one GIFT class, became inspired by what she experience and finally took her employer up on the offer of a free gym membership. She didnÂ’t feel it was necessary to continue GIFT. Changes Made due to Participation Completers and non-completers alike reported making changes because of the program. All seven completers made at least one change, as did seven of the ten noncompleters who answered this question. The most common cha nge was increased physical activity (5 completers and 3 non-completers), fol lowed by eating more fruits and vegetables (2 completers and 3 non-completers) and drin king more water (2 completers and 3 non-completers). Â“IÂ’ve been a lot more committ ed to physical exerciseÂ” one completer said as she explained her 5-day a week workout regimen. Another said, Â“I do try to make sure that I get a little more water in. T hat was one of my major problems. IÂ’m trying to continue the program. You know IÂ’m not as f aithful with my fruits and vegetablesÂ… That was the other thing Â– the darker vegetables, you know, the more vivid like the orange and the green. I never really thoug ht about that. And that was one thing that I became more aware of from the program.Â” Three other participants (2 completers
106 and 1 non-completer) discussed being more conscious of the ir eating habits and their health. As one woman put it, Â“I find that I try to think more before I grab some of those snacksÂ…ThereÂ’s a little hesitancy there that helps in mak ing some choices. I have the opportunity to make some better choices.Â” Seven particip ants (3 completers and 4 noncompleters) reported that they had maintained all of these changes, but several admitted to backsliding. One woman described her efforts to giv e up Diet Coke in favor of water: Â“IÂ’ve been sneaking back up a little bit on it here l ately, IÂ’ve got to get that back down. ItÂ’s truly an addiction.Â” Said another about her attempt to eat more fruits and vegetables, Â“IÂ’m sticking with it but not as thoroughly as I was w hen I was on the program, you know what I mean? IÂ’m still doing the things the program taught me as far as like I said the vegetables and things.Â” Participants described a number of challenges that make it difficult to stick to these changes. Busy schedules were something that completers and non-completers a like faced. Said one completer, Â“The food part is har d for me because I feel like IÂ’m always in a hurry and I want to be able to just grab and go, and the stuff thatÂ’s grab and go is not good for you. I mean you can only grab so ma ny apples, or grab so many bananas, you know?Â” Another talked about finding tim e to exercise, saying Â“When you go home you have children, you have things to do at h ome, you have to cook. You know, thereÂ’s never time. So youÂ’re up from five in the morning trying to get breakfast and everything and lunches packed and then till ten at night. ItÂ’s just hardÂ… I go to the gym everyday on my lunch hour and then thatÂ’s it. So I have a pretty tough, a tight schedule.Â” A non-completer found it difficult to find t ime to grocery shop, saying Â“With my schedule, sometimes itÂ’s harder for me to go out and shop and find enough to have in my home so I can plan which is one of the biggest things really. Planning i s one of the most helpful things you can to, to be able to plan ah ead and have the stuff available
107 before you need it. So thatÂ’s one of my things, and sometimes the cost factor becomes an issue, but I try to work with it.Â” Three participants (2 completers and 1 non-completer) talked of challenges arising from social situations and family members. One w oman talked of the resistance she faced at home: Â“Â… I live in a household where there are two others who you know, they were kinda used to eating what they want to eat And I try to Â– IÂ’ve done things like incorporated wheat bread. You know theyÂ’ll still fight me from time to time and if we run out theyÂ’ll go buy white. You know [I] try not to d rink sodas, theyÂ’ll go buy sodas. IÂ’ve instituted wheat pasta, sometimes theyÂ’ll go along wit h it, theyÂ’ll go buy the regularÂ… But you know you have to battle that so that makes it ha rd sometimes.Â” One said, Â“I mean I like good food, as far as like fresh vegetables and th ings like that go. But man they take so long to fix. My family was hungry yesterday, they w ant it like yesterday, not, you know, 20 minutes from now.Â” One participant from a workplace wellness group brought up an interesting and unique set of challenges. He felt that it has Â“hard if the people in your group arenÂ’t as committed.Â” Once the program had ended, he found it d iscouraging to see others backslide. Â“Some people went back to their old habits, which makes it hard for you to stick with new ones, especially when you see them every day.Â” Others talked about lacking motivation, traveling frequently, and keepin g healthy foods on hand in order to avoid temptation both at home and at work. When participants were asked to describe what made it easier for them to stick with the changes they were trying to make. The most co mmon facilitator was inner motivation and determination (2 completers and 3 non -completers). Explained one completer, Â“My own ambition, my own inner self is what drives me to do it. You know you need to do this, you need to stay fit, you need to ge t the stomach down, you just need to go. And thatÂ’s it. ItÂ’s just me driving me to do wha t I want to do.Â” A non-completer
108 expressed a similar sentiment: Â“Just me doing it and bei ng motivated to do. Had I not been motivated I probably wouldnÂ’t have did it. Not yet, kept putting it off and making excuses.Â” Three of the completers felt that the group setting helped them, liked the man who said that the class Â“sparked motivationÂ” or the woma n who felt that the co-workers from her group who she still kept in touch with helped her. She explained, Â“You try to keep each other on track. Â‘Did you do your walking to day?Â’, Â‘Did you try this?Â’, that type of thing and ideas with recipes and so on.Â” In contrast, non-completers tended to talk about more concrete aids, like being able to cook or fr eezing meals ahead of time. Most of the participants, completers and non-completers a like, described the changes they made in their lives having a positive imp act on others. Of the eight participants who felt that their personal changes impa cted others, seven said it was through purchasing healthier food and cooking differen tly. As one participant explained. Â“So yeah it has affected them but in a good way too because I have been trying to cook a little bit healthier for them and theyÂ’ve liked so me of the things that weÂ’ve tried and so, itÂ’s affected them too.Â” The other person felt that j ust setting a good example had influenced friends positively. She explained, Â“Â… friends have seen what IÂ’ve been eating and go Â“hmmm, maybe IÂ’ll try thatÂ”. So that has bee n an influence for a couple of people.Â” In addition to all of the lifestyle changes participan ts made, most also lost weight. Weight loss among the completers was modest, with fou r of the seven participants losing six or less pounds over the course of the six week program. One lost 10 pounds, one didnÂ’t lose any (but did lose 6 inches in her waist ), and the final completer wasnÂ’t interested in losing weight. Only one didnÂ’t maintai n this weight loss, but attributed this to a medication whose side effects include weight gain. I nterestingly, all of the eight noncompleters who answered this question, seven also reported losing weight and the eighth wasnÂ’t sure one way or the other. Again, most l ost six pounds or less, but two
109 reported losing between 15-20 lbs. All eight maintain ed their weight loss. That being said, it is more difficult to know whether the weight loss of the non-completers is attributable to GIFT, since many things have happene d in the participantÂ’s lives since their short participation in the program. For exampl e, one felt that part of her six pound weight loss was due to her recent sickness, and another t hat estimated her weight loss at 15-20 lbs due to joining a gym after participating in one class of GIFT. When asked if they had met their goals, both complete rs and non-completers were ambivalent. Four of the seven completers were sat isfied with their accomplishments during the program, but the rest felt th at they had met some goals but not others. As one woman explained, Â“I donÂ’t think I Â’ve met my goals for myself totally but for what I set out for the program, yes. So like a s I set my goals during each week, I met my goals. Now, as far as where I want to be, I ha venÂ’t gotten there yet. So you know, thatÂ’s still ahead of me. I havenÂ’t totally rea ched my total goals.Â” The noncompleters who answered this question were similarly ambi valent. One man said he had Â“kind of sort ofÂ” met his goals, but he felt he n eeded to be better about exercising and wanted to lose more weight. Another felt that we ight loss would never be truly accomplished and would always be an ongoing effort. She described her feelings like this: Â“Â‘cause thatÂ’s always going to be a constant struggl e. Just depends on whatÂ’s going on in your life that you know, can trigger you do go back to your bad habits or something like that.Â” Friends and Family GIFT reached beyond the participants, as many shared e ither the knowledge or the materials themselves with friends and family. Three of the six shared the actual lessons with family members and another told her friend s about the class and tried to Â“be an exampleÂ” However, two participants hinted that their family members were less
110 than receptive. One reiterated her struggle to change the foods kept in the home, and another admitted that she didnÂ’t share the materials w ith anyone. She went on to say, Â“I try to encourage my husband, but it doesnÂ’t work, so I just work with myself [laughs].Â” Three of the five non-completers who answered this que stion also shared the materials with friends or coworkers. Another didnÂ’t share the a ctual materials, but did talk with his friends and family members about eating more vegetabl es. He explained, Â“Like I said most of my family and friends, you know, theyÂ’re all about meat, no one wants to eat vegetables. And if they do itÂ’s like Â– Â‘cause you know even when a lot of us were growing up in my family, you eat a small amount of vegetable s and a big portion of meat. Nobody ever told me that vegetables should be a little bit m ore, you know that kind of thing.Â” When asked if family and friends were supportive, most participants (five of six completers and five of six non-completers) felt that the y were. Among completers and non-completers, the support tended to take the form of verbal encouragement rather than tangible support like exercising together. One com pleter put it like this, Â“You know, just verbally. You know, Â‘Yeah, you can do itÂ’, Â‘That Â’s goodÂ’, you know that type of thing.Â” Another explained that her family was very supportive saying, Â“At home, weÂ’re all conscious of trying to eat healthy, and just by bringin g home some of the literature and some of the ideas. Everyone was sort of interested in it And that really helps. Again if you have, you know, people with common goals around y ou that is helpful to me.Â” This encouragement from family and friends also sometimes in cluded more pointed reminders when participants appeared to be veering of f track. One non-completer put it like this, Â“Yes, they kept tabs on me. Yeah, you know (unintelligible) Â‘I thought you was supposed to be doing this.Â’ or you know.Â”
111 S uggestions for Improving GIFT Finally, participants were asked what they would do differently if they were to teach the class. The most common change was about the time and/or location of the class (one completer and three non-completers). The compl eter would have rather held the class before work rather than over lunch, and the non-completers wished the class had been at a more convenient time or location. Other suggestions from the completers included: more space in to write in the food journal, more concrete suggestions for the physical activity portion each week, and scheduled physical activity outside of class. One completer would have liked a more knowledgeable facil itator. She explained, Â“The people who were moderating the groups I know put a l ot of time into it. But again, theyÂ’re not professionals in that field, so again it wasÂ…maybe it would have been better if there was a person that was a real team leader as far as in t hat fieldÂ… someone with more indepth knowledge and I guess is more aware of health an d diet issues.Â” Suggestions from non-completers included: having an accountability buddy within the class, making the class longer than six weeks, and a week devoted to Â“ healthy swapsÂ”. The participant explained healthy swaps further, saying, Â“I think I w ould actually like to have, on occasion, maybe once or twice, to have something on hand that would show easy and/or simple some of the transitions can be done. How you can t ake something that people are doing now, and say Â“You can do thisÂ”. You can make this and this will Â– you know, eat this, not that kind of thing. Whereas you can take something somebody has high in calories and do a conversion and show them how the same thing can be done, taste as well but cut the caloriesÂ” (emphasis hers).
112 Supplementary Sources of Information Goal Forms and Weekly Action Plans During Week 1 of GIFT, participants complete a workshe et about their mediumterm goals, usually for the duration of the program, but participants can determine the end-date. They are also instructed to come up with a p ositive reward and a Â“negative rewardÂ” (i.e. a punishment). Of the 345 participants w ho completed these Week 1 goal sheets (about half of the sample for the statistical ana lysis), the most common positive rewards were clothes (82 participants), an experience such as a vacation or night out (31), a material purchase other than clothes (26) and p ampering such as a haircut or pedicure (12). However, 27 participants misunderstood an d put either a method of achieving their goals or the date they would achieve them by. Only 2 participants put an intrinsic reward, such as feeling good about themselves. I nterestingly, responses tended to be grouped together, suggesting that participants w ere influenced by the suggestions given and examples used by their CHAs. As for the neg ative rewards, only 50 participants followed the directions and put an unplea sant task or said they would deprive themselves of something. Instead, participants te nded to say that if they did not meet their goals they would continue the program (25 participants), Â“continueÂ” or Â“try againÂ” without specifying whether it would be through the program or individual efforts (55), try harder or work harder (22), and feel bad (9). An additional 16 participants said they would exercise more, indicating that they view ex ercise as an unpleasant task or a punishment. The goals listed on the goal sheet have changed over t ime. Eight of the goals have remained consistent, but two different goals have been added to the current version (maintaining a weekly food tracker and weigh ing in weekly). Participants tend to check off several of the goals available on the checklist When participants had eight goals to choose from, they picked 4.95 on average, and when there were 10 available
113 they chose an average of 6.43 goals, suggesting a posit ive correlation between the number of goals suggested and the number chosen. Using a percentage score to account for the varying number of goals, the average participant chose to adopt 61.8% of available goals. Figure 23 below shows the number o f participant who selected each goal. With the exception of decreasing sugary drinks a nd Â“otherÂ”, each goal was selected by approximately two-thirds of participants. Th e Â“otherÂ” category had a mixed bag of responses that included reducing or avoiding specif ic foods (5 participants), diabetes management (4 participants), and smoking cessati on (3 participants) as well as many other unique goals. 50100150200250300350 Increase fruits Increase vegetables Increase number of steps Exercise 3x a week Increase water consumed Decrease sugary drinks Lose __ pounds Other Maintain weekly tracker Weigh in weekly Not a goal Goal Missing Figure 23 Goals Chosen by Participants
114 Almost two-thirds of participants (65.8%) set weight lo ss as a goal, but they varied in the amount of weight they wished to lose. More than one-third (81 or 35.7%) wanted to lose 1-2 lbs, but since the goal form specifica lly recommends 1-2 pounds per week, it is likely that these individuals intended to lose 1-2 lbs per week rather than 1-2 lbs over the course of six weeks. An additional 101 part icipants (44.5%) followed that recommendation and set their goal from 3 to 12 pounds. Of the remaining participants, 35 (15.4%) wanted to lose between 13 and 30lbs and 1 0 (4.4%) between 31 and 100 lbs. The goal form is intended to be for the six weeks of the lesson but is structured in such a way that participants are able choose any timefram e, making it difficult to tease out whether participants had unrealistic expectations for the class or were making longterm goals. In addition to the 345 goal sheets from Week 1, an a dditional 654 weekly action plans created by 358 participants were analyzed. The mo t common goals were to increase physical activity (203 goal sheets, 31.0%), eat di fferently (177, 27.0%), lose weight (usually 1-2 lbs) (118, 18.0%), and drink more water (79, 12.1%). Those who wanted to eat differently had different strategies: eating more fruits and or/vegetables (50 goal sheets), those who had vague goals of wanting to Â“eat healthyÂ”, Â“eat rightÂ” or Â“watch what I eatÂ” (45), cutting out or reducing specif ic foods like sweets, snacks or fast food (30), controlling portion sizes (21), and eating at a different time of day (including avoiding late night snacking) (10). Even though the g oals often differed from week to week and certainly from participant to participant, th e reasons behind them were very similar. Participants tended to write that they were doing this either for their health, in order to lose weight, or that they Â“needed toÂ” in or der to meet a recommendation or guideline they currently did not. Rarely did particip ants write of looking or feeling better as a rationale. Impediments were also much the same acr oss goals. Whether it was drinking more water or cutting back on ice cream, par ticipants tended to write about a
115 lack of time (usually because of work and family commitmen ts) and Â“lazinessÂ” or a lack of will power/determination as impediments. In fact som e participants were so concerned about their lack of will power that a few set weekly goals relating to gaining Â“controlÂ” or Â“trying harderÂ”. Many of the solutions to impediments of all kinds were mental rather than concrete actions. Participants wrote of working harder, trying harder and being more disciplined to overcome their obstacles. This attitude wa s best exemplified by the participant who wrote, Â“I think that when one wants som ething there are no obstacles.Â” Despite all of the commonalities there were some diffe rences in impediments across the different goals. For example, weather was see n as an obstacle to both losing weight and being more physically active. For the goals related to eating, participants wrote about temptations and cravings as impediments, as well as parties and social events. Eating more fruits and vegetables required mor e planning, and cutting out foods like sweets and snacks was made difficult by their easy a ccess and family members who still wanted to keep them in the house. Again, a lack o f will power or determination was a strong theme throughout the goals regarding diet. Another clear theme was the vagueness of the goals. Fi fty-six of the goal sheets had multiple goals, and others were completely opaqu e, like the participants who wrote Â“stay on trackÂ”, Â“do the programÂ” and Â“make lifestyle changesÂ” as their action plan goal. A large number relating to both physical activity and diet were not very specific. Many participants wrote simply Â“exercise moreÂ” or Â“eat more f ruitÂ” without defining what Â“moreÂ” meant. Similarly, the plans to overcome impediments we re sometimes vague, and there were instance where participants put question marks or ad mitted they did not know what to do about a particular obstacle.
116 Community Health Focus Group In addition to the goal forms and weekly action plan s, there was another supplemental source of information: a focus group under taken as part of a community health assessment. The church congregation that partici pated in this focus group had recently participated in GIFT, and while GIFT was not the intended topic of the focus group, a great deal of time was spent discussing the pro gram. The participants apparently did not realize that the Hillsborough Cou nty Health Department was behind both the focus group and GIFT, making the discussion mu ch more candid than it might have been otherwise. One person in particular was very articulate about the problems of educational programs like GIFT. Â“I think more community outreach and more education. But, but not just education as we know it because I think the reason why it hasnÂ’t been successful in the past is that those who are sharing that information are talking at people. They need to speak to them where they are. T o just tell an African-American in an urban community Â‘You canÂ’t ea t ribs anymoreÂ’, thatÂ’s really not going to work very wellÂ… But if you tell them, Â“You may not be able to eat ribs because they too fatty, but t here are other cuts of pork you can still eat if you cook them this way.Â” Another person felt that education was beneficial, but it really came down to personal motivation to make changes. Â“I know that education is extremely important and I do think itÂ’s key and what IÂ’m about to say is something that no one from th e outside can provide, and thatÂ’s motivationÂ… Because I think until you have some major thing, you almost think that itÂ’s not going to happen to you. You know what I mean? I havenÂ’t been diagnosed with anyt hing, but I know that IÂ’m too heavy and perhaps itÂ’s just a matter of time. And I know how to lose weight even, and I know how to basically, basically now, IÂ’m not a nurse like she is, but I know basically what constitutes a healthy meal. So I do think that education is key, but even knowing tha t, itÂ’s like smoking or drinking or any other excess thing. People know that. People know enough to know where they are is a bad place. But how to they becomeÂ…I donÂ’t think another person can provide that fo r you. ItÂ’s hard for me to stay focused.Â” Suggestions for improving motivation included instruct ors or teachers who are passionate and knowledgeable, and accountability partne rs. One person felt that lack of
117 motivation was preventing people from taking advanta ge of free resources like the GIFT program. At their church, GIFT ended with less than hal f of the people they started with, which this person attributed to individuals losing motiv ation. One of the non-completers spoke up about why she didnÂ’ t complete the program, saying Â“And the reason why I dropped out is because, #1 and this is not any reflection on you because I know itÂ’s not your program, but I did nÂ’t find it exciting. I didnÂ’t find it Â– although they were saying all the right stuff, you kno w, all the right stuff, there was not anything there that made me want to keep coming back Two other participants objected to this sentiment, saying they had Â“wonderful timeÂ”. Two different participants suggested more interactive p resentations. One example was a presentation that visually shows the harmf ul effects of sugar on your body rather than just talking about avoiding sugar. Th e woman who discussed why she didnÂ’t complete the program gave a very impassioned spe ech about how a more interactive format would have kept her coming. In her words: Â“You know, we cook in a rut, we live in a rut. We do the same things over and over again. ThereÂ’s nothing exciting about the sam e thing. If you want to try something new, if you want to get people to try something new, you have to present them new and different [Â“go od ideaÂ”]. Cooking, you know, cooking classes. You know, things like this. D onÂ’t just say hereÂ’s a recipe. Say come and taste what this tastes lik e. Say Â“you think you need a pound of bacon, but you donÂ’tÂ” and let t hem taste it before you tell them thereÂ’s no meat in it or let them taste it and say Â“ dang, this is goodÂ” and then say, thereÂ’s no pork in those greens. You know what IÂ’m saying? IÂ’m talking about interactive stuff. Give the m something concrete. DonÂ’t give me a piece of paper and say, Â“Here, try th isÂ” or Â“Here, try this dietÂ” or Â“try this recipeÂ”. You know something Â– creat e an era [sic] of excitement and about it. I mean an ongoing, not just the first day, but every time they come to that place, you got this going on. On Tuesdays they got a juice bar and on Wednesday they got cooking classes, vegetarian Â– you know that kind of stuff. [murmurs o f approval] ThatÂ’s the kind of stuff that make you get out your house and go [stronger approval]. Especially if what weÂ’re creating tastes good.Â” There was also some further discussion about the taste and appeal of food being as important as its nutritional content. As one person put it:
118 Â“WeÂ’re very taste oriented people because we season our food well, and you know, we want food that tastes good If it doesnÂ’t taste good then you not going to eat it. You may eat it once, but you no t going to keep eatin it. So we need to address healthy eating where we are. D onÂ’t just say you canÂ’t eat that anymore because you canÂ’t take stuff away from people without replacing it, and for African-American people and Third World people, you canÂ’t just replace it, but you got to rep lace it with something that tastes good or we not going to eat it. Conclusion This chapter presented the results of the statistical a nalysis of program records from 664 participants, observation of nine GIFT groups, and interviews with seventeen participants, with goal forms and a focus group as supp lements. The results were discussed by methodology and topic, but the next chapter will synthesize findings and delve into broader themes. Recommendations for the imp roving GIFT and conclusions regarding weight loss and its ideological underpinnings will also be discussed in the next chapter.
119 Chapter 5: Discussion Introduction This chapter gives an overview of the major findings of this study, organized by research question. A summary of the effects of the GIFT program is given, followed by a discussion of the way in which the program meets and fail s to meet participantsÂ’ needs. Next, the explanatory model used by participants is det ailed, as well as the role of empowerment within the program. Finally, there is a discussion of the implications of this study for both anthropology and public health, as well as recommendations for GIFT and weight loss programs in general. Effects of GIFT Although this study did not have a control group, and therefore cannot be certain that the effects seen in analysis are due entirely to th e program, there was a great deal of convergence in the results from the quantitative anal ysis, observations, semistructured interviews and supplementary sources of inform ation. This suggests findings are both internally valid and probably due to GIFT. Weight Change The findings suggest that a fair number of participants lose weight (64.2%), and weight loss tends to be modest (less than 5 lbs). Althoug h participants were sometimes disappointed with their progress during Session I of GIF T, this modest weight loss shows that participants are not crash dieting and are instead making the kind of small, incremental progress associated with long-term weight m aintenance (Centers for
120 Disease Control and Prevention 2011e). Interviews sugge sted that most participants were able to sustain this weight loss, but only one was able to lose any additional weight. It should be noted that this type of question is susceptible to socially desirable answers, but with no alternate source of information th ese self-reports must be taken at its face value. The quantitative portion of analysis regarding weight change showed that weight change did not differ significantly by gender, age, or ethnicity, suggesting that the program does not have greater success with one sub-popul ation over others. Weight change was related to attendance, however. Participant s who attended 4-6 classes were significantly more likely to lose weight (p=0.000 n=341) and lost more weight per class attended (p=0.009, n=341) than those who attended only 1-3 classes. The greater success of participants with greater exposure to the progra m suggests that the current policy of not referring participants beyond Week 2 is a good one and should be implemented more consistently. Food Diaries The qualitative analysis also revealed an upward trend between food diary completion tertile and weight loss status, meaning that those who did more food diaries were more likely to lose weight. A chi-square test for independence confirmed this relationship (p=0.000, n=340). However, almost 20% o f participants in the top tertile (meaning they completed the most food diaries) gained weight. From this analysis, is appears that food diaries do help people lose weight, but do not work for everyone. It should be noted, however, that food diary completion was investigating using a simple completed/not-completed metric, with Â“completionÂ” defi ned as having at least 50% of the form filled out. During data entry and participant observation I noted a wide variety in completeness and witnessed numerous instances of participan ts filling out their food
121 diary in class just prior to turning it in. It could be that success with food diaries is tied to the level of detail recorded or the time it is filled out (immediately after eating vs. the end of the day or week). This was seen in the literature, although there was a great deal of conflicting evidence (Baker and Kirschenbaum 1993; Goris, et al. 2000; Helsel, et al. 2007; Shay, et al. 2009). The motivation behind food diary completion may also have a part to play in the relationship between food diary completion and weight loss. One of the complaints raised by the CHAs was the difficulty in getting partici pants to fill out their food diaries each week. Participants for their part, tended to view the food diary as a useful tool for self-reflection, but not necessarily something that neede d to be completed for weeks on end. This raises the question of whether participants comp leted their food diaries because they saw the value in it or whether it was simpl y to comply with the program, which presents the food diary as mandatory (although th ere are no repercussions for not doing it). Other Changes The quantitative analysis, observations and interviews indicated that participants made a number of other changes beyond weight loss. The quantitative analysis revealed that most participants are not meeting CDC recommendat ions for fruit and vegetable consumption, physical activity, water consumption, or waist circumference (Andersen, et al. 2003; Centers for Disease Control and Prevention 2008; Centers for Disease Control and Prevention 2010; Centers for Disease Control and Prevention 2011d). While the data regarding fruit and vegetable consumption, physica l activity and waist circumference was far from ideal, what exists suggests that most participants move closer achieving these guidelines through the program. F or instance, the majority reported that they had increased their fruit and vege table consumption and physical
122 activity at the end of the program on the Evaluation Form. The waist circumference data similarly suggests that a small number of participants (11 ) achieved the guideline for their gender, but more than 60% decreased their waist size. The analysis also showed that weight loss and waist circumference do not necessaril y go hand in hand (a phenomenon I also witnessed during observations), which underscores the value of using both measurements in order to avoid reliance on o ne particular measure as the indicator of increased risk for chronic diseases. Water consum ption was not measured at any point, but the weekly action sheets suggest it was a common target for improvement, and water was a frequent topic of discussion during the classes I observed. Although there is no hard data, it is likely that many participants improved their water consumption. Finally, in observations and i nterviews participants described a number of other positive changes, including cutting bac k on soda, switching to whole grain pasta and bread, eating more regularly, becomi ng more aware of portion sizes, planning meals, and cutting back on condiments, among other improvements. Ripple Effects GIFT had a positive impact not only on participants but on the families, friends and co-workers of participants. Several of the intervi ew participants shared either the materials or the information within the materials wit h family, friends and co-workers. Almost all of the interview participants said that thei r participation in GIFT had positive effects on others. Most reported keeping healthier fo ods in the house and cooking differently, which changed the way the entire family eats. Two participants talked of consciously serving as a positive role model for friends an d family.
123 Satisfaction Overall, participants had a positive attitude towards G IFT. In the interviews, completers generally described having a positive experie nce within the program and even the non-completers had very few (if any) negati ve remarks. The results from the Evaluation Form were overwhelmingly positive. It shou ld be noted the Evaluation Form is administered in Week 6, and so only reflects the per spective of participants who complete the program. Still, those who completed the f orm had very high opinions of their CHA and the program in general. Although data on the individual lessons was limited (and is no longer collected), what exists was also very positive. Taken together, the data from multiple sources suggests that participants are satisfied with their experiences in GIFT. Meeting (and Failing to Meet) ParticipantsÂ’ Needs Meeting Needs GIFT does an excellent job of meeting participants nee ds in a number of key areas. The CHAs are dedicated and passionate, and often make themselves available to participants outside of class. The weekly classes also provid e a much-needed support system. Although nearly all participants interviewed h ad a history of dieting, many had only made individual efforts and appreciated the sol idarity that the group setting provided. Further, it was clear through the interview s, observations and weekly action plans that not all participants had supportive friends, family and co-workers outside of class. Including social support as a distinctive portion of the class ensures that all participants have at least their group as a support syste m. Similarly, including physical activity as a distinct portion of the class helps time-stra pped participants Â“build inÂ” activity into their schedules without any additional effort a nd exposed participants to new types of exercises or workout systems. It also reinforces the id ea that physical activity is
124 equally as important as diet for good health. Unfort unately, the exercise portion of the classes was implemented unevenly, but its inclusion is to GIFTÂ’s credit. A final dimension was the food diary, which participants universa lly saw as a helpful tool for self-reflection. While some participants didnÂ’t feel a need to complete one for weeks on end, the participants interviewed felt the food diar y benefitted them. Failure to Meet Needs However, the program fails to meet participantsÂ’ need s in other important ways. The lessons donÂ’t give enough attention or space to diet ary habits outside of mainstream American culture, despite the fact that most participan ts are minorities. The best example of this comes from the Week 1 lesson, which includ es sample daily menus at four calorie levels for the mainstream American diet, but only two calorie levels for Â“AsianÂ” and Â“SpanishÂ” foods. Soul food, which was discussed extensively among African-American participants, is not included. The progr am also doesnÂ’t directly address many of the issues that participants see as impediments. Some problems, like those related to family members, social situations, emotional eating, and lack of time, are discussed during the social support portion of the class. Pa rticipants try very hard to brainstorm solutions for others in their group, but th e lessons themselves very rarely delve into the social or emotional aspects of weight l oss. Parties and other social events are explicitly covered in a lesson called Party Time but it is not officially taught until Week 20, although some CHAs taught it in November or D ecember in preparation for the holiday season. Very little credence is given to st ructural barriers such as the cost and availability of both produce and places to be phy sical active in either the lessons or class discussions. In addition to not addressing many of the impedimen ts participants faced, the lessons also cover a great deal of material that particip ants already knew prior to
125 entering GIFT. The quantitative analysis, observations and interviews all indicated that the instructional complexity of the lessons was too low. While participants valued education tremendously, every interview participant in dicated that very little of the information presented was new. Similar things were see n in the observations, as participants demonstrated that they sought health info rmation outside of GIFT and were quite knowledgeable about the basics of nutrition and the mechanics of weight loss. Additionally, the item analysis of the pre and postte sts revealed that knowledge does not significantly improve because participants scored so highly on the pretest there was little room for improvement. Probably the biggest way in which the program does no t meet participantsÂ’ needs is the way in which it fails to fully engage them. Man y of the CHAs, both paid and volunteer, went above and beyond expectations to add components to their classes to better engage participants. Several added additional information from the internet, as well as activities like a cooking demonstration and bri nging in food samples for all to try. One CHA directly asked participants why they were not more enthusiastic and involved. Some classes were lively and involved, but others were rather subdued, with participants simply sitting back and listening rather than actively engaging in discussions. Non-Completion It is these shortcomings in meeting participantsÂ’ needs t hat I believe contribute to the high number of non-completers. Only about one-t hird definitively complete Session I of the program by attending Week 6. The data suggests that finishing the program is unrelated to age, gender or ethnicity, which effective ly eliminates the possibility that GIFT appeals to some groups or populations better than others. However, it is clear from the quantitative analysis that participants who enter G IFT during Weeks 1-3 are less likely to complete the program (p=0.000, n=539). I originally hypothesized that people
126 who entered the program later might struggle to fit into an established group and have a higher non-completion rate, but the evidence from bot h the quantitative analysis does not support this. Instead, most participants start in W eek 1 and slowly dwindle in membership as the weeks pass. New members occasionally joi n but the group and generally stay on until the program ends. Interviews w ith ten non-completers revealed that participants decide not to continue the program fo r a number of reasons, most notably the inconvenience of the time and/or location of the class, the interference of other obligations and responsibilities and injuries/il lness. Coupled with findings on the lessons and engagement, on e explanation is that participants come to the program and find nothing new or interesting that keeps them coming. This was most directly expressed by the participan t in the community health focus group who did not realize HCHD was behind GIFT, and was therefore unusually candid about her disappointment with the programÂ’s lac k of excitement and originality. It is also worth noting that both grocery store tours I wa s a part of had unusually high attendance Â– it was something new and exciting that par ticipants did not want to miss. Attending a class like GIFT requires effort since partici pants must carve out time in their busy schedules; participants who do not complete the progr am simply may not see any reason to continue making that effort. As Davison and Pennebaker (2000: 246) point out, when it comes to support groups, members Â“vote with t heir feetÂ”. Another possible explanation is that non-completers are not ready to make lifestyle changes, and so decide to stop attending. Ho wever, I would argue that a person who is not ready to make changes would not come even on ce. While it is probably unrealistic to expect a 100% completion rate, the high number of non-completers can be seen as a missed opportunity to really engage people wh o have demonstrated an interest (by coming to at least one class of GIFT) in mak ing a shift towards a healthier lifestyle.
127 Explanatory Models For the most part, the program, CHAs and participants a ll operate out of the dominant individualistic paradigm. The major goal of the program is weight loss through increased knowledge and the adoption of healthy behav iors (namely fruit and vegetable consumption, physical activity and water consumption), in line with CDC recommendations (Centers for Disease Control and Prevent ion 2011c; Centers for Disease Control and Prevention 2011e). This is borne ou t in the lessons and in the variables chosen for measurement and reporting. Particip ants largely agree with this, although a small minority of participants sought educa tion or improved health rather than weight loss. This agreement with the programÂ’s stated g oals is most clearly seen in the weekly action plans. The most common weekly goals were regarding losing weight, eating differently, exercising more and drinking more water. Similarly, the goals described by participants in interviews were also very m uch in alignment with the programÂ’s goals. Most importantly, weight loss and better health are ach ieved through individual effort. Any failures are the personÂ’s own, and blame is not assigned to the program. For example, on the goal forms in Week 1, most participants did not set a punishment (Â“negative rewardÂ”) for themselves if they did not re ach their goals, but instead said that they would Â“continue the programÂ” or Â“try againÂ” if they failed. What is interesting about this is that participants, before they really even star ted the program, assumed that if they did not reach their goals it was because they failed the mselves, not because the program failed them. It is as if participants had no t even considered the possibility that the program might be deficient or unhelpful. Further in the interviews, the participant who came closest to having a negative attitude towards G IFT framed her disappointment in terms of a Â“bad fitÂ” between herself and GIFT. It was not that the program did not meet her needs, but rather she did not fit the program an d needed to look elsewhere. This is
128 very much in line with the public health paradigmÂ’s vi ew that diets fail because individuals are not committed to them (Saguy and Rile y 2005; Stinson 2001). Blame is also not assigned to attenuating circumstances wit hin GIFT. In group discussions, participants were given little room to make excuses or assign blame to their physical environment or financial circumstances. The prevail ing attitude was that more effort, a different strategy or more planning could solve all problems. This was also borne out in the weekly action plans, where participan ts often wrote of Â“lazinessÂ” and lack of willpower as impediments to a variety of goals. Reading the goal forms, it is as if participants see themselves as their own worst enemy. Aga in, this echoes the dominant public health modelÂ’s assertion that individuals are fu lly responsible for weight gain and must use discipline and hard work to overcome their affli ction (Honeycutt 1999; McKinley 1999; Ritenbaugh 1982; Sobal 1999; Stinson 2001). As other social scientists have pointed out, in many way s weight loss in the dominant paradigm is as much about gaining control ove r an out-of-control body as it is becoming healthier and more attractive (Gilman 2008; Stinson 2001). This was also true for the participants of GIFT. Although power and contr ol were not discussed directly, it obliquely came out in discussions when participants didnÂ’t understand how they had gotten so large or why they were not losing weight. I n their minds, they were doing everything they were supposed to, so why wasnÂ’t their b ody cooperating? Other participants struggled to gain control over their rela tionship with food, which had an incredible strong hold on some participants. One woman told the class that she had to learn to drive in the center lane on the highway so that she would be less tempted to pull over for fast food. Indeed, in the weekly action pla ns, resisting temptation was seen as an impediment to goals relating to diet/eating, and some participants were so concerned about their lack of will power that their goals for t he week were related to gaining Â“controlÂ” and Â“trying harder.Â”
129 There were some pockets of resistance to this individualist ic paradigm however, that mostly related to ideal body size. GIFT currentl y puts a lot of emphasis on BMI, calculating BMI at Weeks 1 and 6, and devoting all of Week 2 to BMI, waist circumference and body fat percentage. However, observat ions and interviews revealed that participants enter the program with an ideal wei ght in mind based on their cultural or individual preferences. Many do not feel that they ca n reach what the BMI chart defines as a healthy weight for their height, and some do not feel that BMI applies to their body type. Some invoked a biomedical model explanation wh en they asserted that their ethnic heritage made their body naturally larger than the CDC recommendations and expressed conviction that biological processes, such as aging, were partly to blame for their current size. Significantly, some participants beco me discouraged when they find that the weight required for healthy BMI is significa ntly lower than the ideal weight they had in mind. Most CHAs appeared to agree with, or at least didnÂ’t oppose, BMI categorizations. One however, told her group that wei ght and health werenÂ’t directly related and that you could be thin and not healthy o r healthy and not thin. Resistance to BMI classification has been documented in other studies, sug gesting that this is one of the more common forces of resistance (Monaghan 2007; Pa rker, et al. 1995). The individualistic paradigm was so dominant and perva sive within GIFT classes that it may help explain some of the paradoxes seen in the data. For example, participants dropped out of the program in large num bers, yet had little criticism of the program and many of the interview participants had di fficulty thinking of suggestions for improvement. Similarly, in the interviews participant s reported that they knew nearly all of the information presented, yet most did not find a nything unhelpful and few could think of topics they had wanted to learn about but werenÂ’t covered. It is as if participants are so embroiled in the individualist paradigm that they didnÂ’t (or couldnÂ’t) think outside of those parameters. Participants (completers and non-comple ters alike) seemed to only
130 expect information and Â“tips and tricksÂ” on diet, phy sical activity and weight loss from the program, and the rest was up to them through individ ual effort. Since GIFT offered exactly these things, participants were highly satisfied. In the interviews, no one even considered the possibility of a program that focused on the social, emotional and structural issues related to weight loss, even though th ese issues were recurring topics of discussion during the social support portions of the classe s. Empowerment While the program materials themselves focus almost enti rely on education, sometimes CHAs strove to empower their classes, with mixed success. During participant observation, it became clear that there is a fine line between empowerment and victim blaming, between having high expectations a nd unreasonable expectations. For example, one CHA adopted Â“make a better choiceÂ” a s her mantra, which in one way instilled in participants the idea that each day contai ned multiple opportunities to make better, healthier choices and each of them had the powe r to do so. At the same time, this attitude assumes total volitional control, and no one has full control over their lifeÂ’s circumstances. To be certain, there are macro-level for ces, such as policies on food subsidies and zoning laws, that participants did not cre ate or control. In StinsonÂ’s (2001) feminist ethnography of a commercia l weight loss group, she also explored themes of empowerment. She noted that i n group discussions about stress and eating, the conversation tended to focus on i ndividual coping strategies (such as not keeping sweets in the house) rather than critiqu ing gender roles or gender-based discrimination that are the source of stress for many wo men. However she points out that some coping strategies can be empowering, such as pri oritizing, delegating, and redefining boundaries with others. While coping strate gies do little instigate change at the institutional or societal level, they do produce wh at Stinson calls a Â“budding feminist
131 consciousnessÂ” (Stinson 2001: 182). Indeed, Stinson sees wei ght loss support groups as a possible location for empowerment and greater fe minism, since feminist themes (albeit watered-down versions) can already be seen in co nversations about Â“taking care of yourself, self-acceptance, and gender roles and inter personal relationships. These same kinds of conversations also occurred in GIFT classes, ind icating that weight loss groups may be a promising location for empowering indi viduals. Further Connections to the Literature As noted in Chapter 2, Stinson (2001) spent two years a s a participant observer in a commercial weight loss group that bears striking re semblance to GIFT. The findings of this study support many of StinsonÂ’s findings. Stinso n also found, for instance, that her weight loss program experienced extremely high tur nover but a few core participants attended regularly and developed relationships. Stinso n, however, is not particularly troubled by the high turnover, except to note that i t negatively impacts the programÂ’s function as a support group, and even suggests that quit ting may be one way of expressing resistance to the dominant paradigm. Other pa rallels between our studies include using religious terminology like sacrifice and temptation, being surprised by what is considered by nutritionists and dieticians as a Â“serving sizeÂ” or Â“portionÂ”, and the problems associated with using leaders who are only sligh tly more knowledgeable than participants. More importantly, Sintson makes several observations an d critiques that are highly applicable to GIFT and other similar programs. The first is that despite constant reminding that Â“no food is off limitsÂ”; this idea was l ost among participants in her weight loss group. Participants of GIFT also had difficulty gra sping this concept, like the woman who confessed to the group shamefacedly that she had a sl ice of cake on her birthday. This suggests that even when a program explicitly promo tes Â“lifestyle changesÂ” or
132 Â“healthy eatingÂ”, individuals still tend to view Â“eat ing rightÂ” as a diet in which foods are forbidden. The second is that participants struggled g reatly with social situations, and tended to view them as something to be endured rath er than enjoyed. Stinson pointed out that no one in her program questioned giving up enjoyable social outings in order to continue lose weight. A small number of participants in GIFT employed this strategy, but CHAs generally encouraged their participants not to use this tactic. Still, like StinsonÂ’s group, the solution for tricky social situations was iron will and careful planning; enjoyment was never seen as a priority. Finally, Stinso n (2001: 161) critiques her weight loss program for failing to deal with the emotional co mponents of eating and weight loss, saying weight loss is Â“stripped of its emotional compone nts, rationalized and reduced to the relatively simple solutions of education and discipli ne.Â” This is a critique I also share, as I saw firsthand how the emotional component of weig ht loss is often repressed but cannot be eliminated. Implications for Public Health and Anthropology The exploration of five explanatory models has shown that obesity is a complex social, cultural, and medical phenomenon. There is a ten sion between public health and anthropology, between the individual and the social that is not easily resolved. Public health too often proposes individual solutions that amo unt to unintentional victimblaming, while anthropology sometimes emphasizes structu ral constraints to the point of inadvertently discounting the role of personal agency. In this work, much like Moffat (2010), I have tried to find a middle path. I belie ve this middle ground lies in the idea of empowerment, in honest conversations of structural constra ins so that individuals can then make the best choice possible within limited optio ns. Education is critical for empowerment, but not in the way that public health u sually utilizes teaching and knowledge. In this study I have found that individu als already know the basics of
133 nutrition and the mechanics of weight loss, but what th ey do not know is how our food system works or that increased health risks for minoriti es have more do with poverty and discrimination than they do biology. It is this powerfu l knowledge that can inspire individuals to work towards personal and social change in a way that information on 6 oz grain equivalents cannot. I am also in agreement with Moffat (2010) that medi cal and biolcultural anthropologists are uniquely suited to bridging the g ap between biology and the social sciences. Moffat suggests that anthropologists begin by deve loping a new metaphor to describe obesity to replace Â“epidemicÂ”, a suggestion that I wholly embrace. This study has shown clearly that the way in which an issue is framed or explained has enormous implications for the types of solutions implemented. I h ave also shown that individuals accept, combine and resist the five mental models of obe sity to create their own interpretations and explanations for their present we ight. A fuller understanding of the emic perspectives of overweight and obese individuals can help both anthropologists and public health professionals craft programs and heal th messages that better resonate with the lived experiences of the intended recipients. I have tried to do that in this study by highlighting how this particular program meets an d fails to meet participantsÂ’ needs. Many of the unmet needs related to social and emotiona l dimensions of weight loss that are very much a part of participantsÂ’ lived experiences but far outside the rationalized view of a caloric imbalance that must be righted. I be lieve a more effective approach to reducing the health risks associated with obesity would address its social, emotional, structural, and economic aspects. Finally, this study has made contributions to evaluati on anthropology, an emerging subfield within applied anthropology (Butle r 2005; Copeland-Carson 2005). This study has employed traditional anthropological me thods such as participant observation and case studies (Butler 2005). As Patton (2005: 33) points out, Â“Â…only
134 open, inductive fieldwork can turn up unanticipated pro gram outcomes and the side effects of intended interventions.Â” By making particip ant observation a critical component of this evaluation, I was able to show both positive un intended effects (positive influences on friends and family) and negative (disco uragement because of BMI). I have also worked to build rapport to better understand th e perspectives and underlying values of diverse stakeholders within a single cultural system (i.e. the program) (Butler 2005). Limitations There were several major limitations of this study. F irst, this evaluation lacked a control group, so the effects seen cannot be ascribed to t he program with any certainty. However, this study employed multiple sources of infor mation and utilized several different methods for gathering and analyzing data. Second, the data for the quantitative analysis was limited due to uneven record keeping and the fact that participants enter and exit the program at different times. Missing data was so prevalent that many of the results were really from subsets of the wider data set, and may not be generalizable to all participants of GIFT. Similarly, the interviews a nd observations both had small, nonrepresentative samples and so the experiences recorded m ay not be true for all participants of GIFT. Finally, this study did not incl ude Spanish-speaking groups in the observations or interviews because of my inability to spea k Spanish. Spanish-speaking groups were included in the quantitative analysis, howe ver. Despite these limitations, there was a great deal of convergence when these multi ple sources and methods were triangulated, providing more confidence in the validi ty of the findings than would be otherwise possible.
135 Recommendations Recommendations for GIFT In addition to acknowledging the many accomplishments and strengths of GIFT, I made several recommendations to Hillsborough County Hea lth Department in order to improve the program. Many of these revolved around i mproving data collection, management and analysis in order to improve quality m onitoring in the future. First, I recommended that they use existing, validated instrumen ts to measure changes in physical activity and fruit and vegetable consumption rat her than the patchwork, retrospective approach currently in use and provided sug gestions for appropriate scales. A second recommendation was to cease recording weight on the food diaries, since many participants do not feel it is necessary to complete a food diary for six weeks and much valuable data is being lost with this arrangement I designed a weekly form (found in Appendix J) they could use to track weight, fruit a nd vegetable consumption, physical activity, and progress towards goals, eliminating many o f the issues that were contributing to missing data. A revised version of the E valuation Form was provided, using a less-confusing format and shifting questions that require identification to other forms to make the Evaluation Form completely anonymou s. The revised forms I created can be found in Appendices J-L. I also advised Hillsborou gh County Health Department to consider building their capacity for data management and analysis, including additional training for staff and/or seeking candidate s with strong research skills in future hiring decisions. Several recommendations regarding the training of CH As were also made. I suggested they include facilitation skills as part of CH A training, so CHAs can better lead group discussions and more effectively deal with strong personalities within their groups. SMART objectives are another area that CHAs could bene fit from learning about during their training, so they can in turn teach their groups how to write specific, measurable
136 and achievable goals in their weekly action plans. Curr ently, many of the goals are vague and therefore difficult to achieve (Shilts, et a l. 2004). CHAs also need more guidance regarding the physical activity portion of the class, particularly the volunteer CHAs. Flexible exercise plans would probably go a long way in making physical activity a more consistently implemented component of the classes. Finally, I made two additional recommendations that w ere more broadly based. One is to shift emphasis away from BMI, and instead me et participants where they are and allow them to set their own goals regarding ideal weight. As an alternative, I recommended encouraging participants to focus on losing 5 -10% of their body weight. This better fits the short time frame of GIFT, and re flects current research regarding weight loss (Blackburn 1995; Goldstein 1992a; Oster, et al. 1999; Vidal 2002a). Further, setting a goal of 5-10% would not conflict with parti cipantsÂ’ existing weight loss goals. It would also reduce the possibility of participants becomin g discouraged right as they are getting started on the path towards a healthier life style. The second broad recommendation was to re-think the lesson s in order to help participants address the social and emotional aspects of w eight loss, as well as structural barriers (such as access and cost of healthy food, etc). I have included in Appendix L an example of an activity that participant s could complete to help them determine what their biggest barriers are. I also reco mmended including more hands-on activities that allow participants to interact with each other and really engage in the learning process and provided a couple of ideas as exam ples. Finally, I recommended eliminating the lesson on BMI, waist circumference and b ody fat % in Week 2. The lesson is very short and covers material that is already d iscussed during Week 1 when participants have their measurements taken. I suggeste d moving some of the materials from the very content-heavy Week 1 to Week 2, leaving W eek 1 for doing measurements, setting goals, and helping participants get to know each other. If
137 participants feel engaged and connected to the group b y the end of Week 1, they may be more likely to return week after week. Broader Recommendations As discussed above, I recommend that medical and biocultura l anthropologists work to bridge the gap between competing explanatory models and work to find a more effective metaphor for obesity than an Â“epidemicÂ”. I also recommend that future programs and policies be grounded in the lived experie nces of overweight and obese individuals and better address the social, emotional, an d structural aspects of weight loss. In addition, I believe we need to fundamentally rethink our approach to nutrition and fitness behavior change programs one two fronts. First, we need to transition from a deficit-based approach to a strength-based approach, and second, we need to take a health-centered approach rather than a weight-centere d approach. The feelings of loss of control and negativity seen in this study may be due deficit-based approach that weight loss programs tend to take. GIFT, perhaps unconsciously or inadvertently takes a deficit-based app roach, but is far from alone in this respect among weight loss programs. The underlyin g assumption behind weight loss programs and diets of all stripes is that there is a Â“rightÂ” way to eat that must be adhered to in order for individuals to be successful. In the interviews, several respondents talked of wanting or trying to Â“eat righ tÂ” and were somewhat taken aback when I asked them to define Â“eating rightÂ”, as if t he meaning was patently obvious. In classes, the paid CHAs would often try to help participan ts Â“diagnoseÂ” what they were doing wrong and suggest changes to improve their eati ng habits. For example, one woman didnÂ’t understand why she couldnÂ’t lose weight b ecause she did not eat any processed foods, refined flour or sugar. Her diet consist ed of mostly brown rice, fruits
138 and vegetables, and after talking for a few minutes the CHA determined she was eating too much rice and not enough vegetables. In contrast, a strengths-based approach takes what a per son is doing right and builds upon in. In the previous example, the woman wa snÂ’t given any credit for avoiding processed foods (and the accompanying sodium), sugar and r efined flour, and appeared crestfallen after her Â“diagnosisÂ” by the CHA. In my wor k in systems of care for childrenÂ’s mental health I have seen the powerful way in which si mply acknowledging a personÂ’s strengths and positive behaviors can turn around a diffi cult situation and empower families to deal with their problems in a more produ ctive way. Although weight loss is in many ways dissimilar from childrenÂ’s mental health, stre ngths-based is the kind of fundamental philosophy that can be applied to a numbe r of health issues. Along this same line of thinking, recent studies out of the field of psychology about self-compassion that indicate that those who are ki nder or more compassionate to themselves are less likely to overeat (Adams and Leary 2 007; Parker-Pope 2011). One psycotherapy and self-compassion advocate put it this way, Â“Self-compassion is the missing ingredient in every diet and weight-loss plan. Most plans revolve around selfdiscipline, deprivation and neglectÂ” (Parker-Pope 201 1: para 15). Rather than falling into a vicious cycle of self-criticism and negativity, those with self-compassion forgive themselves (but still accept responsibility for their acti ons) and move on (Parker-Pope 2011). I also echo early calls by Cogan (1999) and Stinson (20 01) to take a healthcentered, rather than weight-centered, approach. We ne ed to do a better job of promoting good nutrition and fitness for their own sa ke rather than as means to an end. Perhaps once the intense pressure to lose weight has been removed, we can reclaim a healthier relationship with food and our bodies and reduce the considerable stigma levied against the obese.
139 Conclusion This chapter provided a summary of the major findings o f this study, organized by research question. First the effects of the GIFT prog ram were articulated, then the way in which the program meets and fails to meet parti cipantsÂ’ needs was discussed. Following that, the explanatory model used by partici pants was covered, as well as the role of empowerment within the program. This chapter concluded with a discussion of the implications of this study for both anthropology and public health, as well as recommendations for GIFT and weight loss programs in gen eral.
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153 Appendix A: Florida Department of Health IRB Determ ination INSTITUTIONAL REVIEW BOARD NON-RESEARCH DETERMINATI ON June 15, 2010 To: Emily Koby Protocol Title: Exploring the Effects of the Get Into Fitness Today (GIFT) Program DOH IRB Number: H10102 Funding Agency: Submission Type: Protocol H10102 Review Type: IRB Decision: Activity does NOT involve research Based on the information provided, the Department of Health Institutional Review Board, or representative, determined your activity does not involve research, as defined in DOH policy and federal regulation, to me an Â“systematic investigationÂ…designed to develop or contribute to gene ralizable knowledgeÂ” (Â§ 45 CFR 46.102(d)) The determination means the project does not meet one or more criteria DOH uses to determine whether an activity falls under the regul atory definition of research. This project is not (at least one of the following is no t present): An investigation (inquiry, examination, or search for facts, usually involving the formulation or testing of a hypothesis) conducted a ccording to a plan, organized method, or procedure for testing or formula ting a question or hypothesis and interpreting results); or Systematic (conducted according to a plan, organized met hod, or procedure for testing or formulating a question or hypothesis and interpreting results); or Designed (planned, purposed, or conducted to apply to phenomena outside the observed data) to contribute to generalizable knowle dge (observations, findings, information, or results that have been demonst rated with enough confidence and significance to confirm or alter the consensu s within the professional norms of a community or discipline) or deve lop such knowledge If the design of the project changes, so that it might b ecome systematic, or generalzable, then it is the responsibility of the rese archer to submit the project for review by the DOH IRB. If you have questions about wh ether your activity may
154 Appendix A: Florida Department of Health IRB Determ ination (Continued) require IRB approval, please contact the human research p rotection program office so we may determine whether the additional activities come under the category of research. If you have questions, want to offer suggestions, or tal k with someone about this or other projects, please contact the Department of Health IRB at (850) 245-4585 or toll-free in Florida (866)-433-2775. You may also visit our website at: http://flpublichealthethics.net/ Thank you for your cooperation with the IRB. Sincerely, Robert Hood, Ph.D. State Public Health Ethicist Ethics and Human Research Protection Program Federal Wide Assurance#: 00004682
155 Appendix B: Knowledge Pre-Test
156 Appendix C: Where Am I? Form
157 Appendix D: Commitment and Contract to Change (Curr ent Version)
158 Appendix E: Client Screening Form
159 Appendix F: Evaluation Form (Current Version)
160 Appendix G: Food Diary and Weekly Action Plan
161 Appendix H: Full Interview Guide Introduction: Explanation of GIFT evaluation and my role, promise of confidentiality, informed consent Background 1. What did you think of the program? 2. Why did you decide to be in the program? 3. What were your goals going into the program? 4. Have you tried to lose weight before? How did tha t go? 5. Was your time in GIFT different from previous wei ght loss efforts? In what ways? Specific Aspects of the Program 6. Looking back, what was the most useful thing you le arned? 7. What was the least useful thing you learned? 8. What was something you would have liked to learn a bout, but didnÂ’t? 9. How much of the information was new to you? 10. Did you enjoy talking about your goals with the other people in GIFT? 11. Did you know anyone in your group before you sta rted? 12. Have you kept in touch with any of the other peo ple in your group? 13. Did you do the food diary/tracker? a. If yes, did you find it helpful? Why or why not? b. If no, why not? 14. Did you enjoy the physical activity portion of the class? Why or why not? 15. Were you able to attend all of the classes? Why or why not? Changes 16. What changes have you made since you were in the pr ogram? 17. What has made it difficult to stick with the chang es? 18. What has made it easier to stick with the changes? 19. Have the changes youÂ’ve made affected others? In w hat way? 20. Were you able to lose weight? a. If so, how much? b. Have you been able to keep it off?
162 Appendix H: Full Interview Guide (Continued) 21. Do you feel like you met your goals for the pro gram? Why or why not? Friends and Family 22. Have you shared the information you learned wit h friends and family? a. If yes, which topics? With whom? What did they think of the information? b. If no, why not? 23. Did family members and friends support you when y ou were in GIFT? Why or why not? Wrap-up 24. What would you do differently if you were to te ach the class or run the program? 25. Is there anything that we didnÂ’t cover that youÂ’d like to talk about?
163 Appendix I: Abridged Interview Guide Introduction: Explanation of GIFT evaluation and my role, promise of confidentiality, informed consent Questions: 1. What did you think of the program? 2. Did you make any changes because of the program? a. If yes, what were they? b. Have you stuck with them? 3. What has made it hard for you to make changes? 4. What has made it easier for you to make changes? 5. What were your goals when you started the program? a. Do you feel that you met your goals? Why or why n ot? 6. Did you lose weight? 7. Were you able to keep off the weight you lost? 8. Did you know anyone in the group before you start ed? a. If yes, did knowing someone help? 9. Have you kept in touch with anyone? 10. Did family members and friends support you when y ou were in GIFT? Why or why not? 11. Did you share the information you learned with a nyone else? a. If yes, what information? What did they think of i t? 12. Were you able to attend all of the sessions? Why or why not?
164 Appendix J: Suggested Weekly Progress Form
165 Appendix J: Suggested Weekly Progress Form (Continu ed)
166 Appendix K: Suggested Revised Evaluation Form
167 Appendix K: Suggested Revised Evaluation Form (Cont inued)
168 Appendix L: Suggested Replacement for Week 1 Goal F orm