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Spring Focus on the Social Sciences: Understanding Motivators of and Barriers to Healthy Eating among African American Primary Care Givers with Children Enrolled in a Head Start Program

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Spring Focus on the Social Sciences: Understanding Motivators of and Barriers to Healthy Eating among African American Primary Care Givers with Children Enrolled in a Head Start Program
Series Title:
Journal of Undergraduate Research
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Kokidko, Yekaterina
Smith, Tasia M.
Tucker, Carolyn M.
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Gainesville, Fla.
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University of Florida
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English

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serial ( sobekcm )

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Verbal dysfluency in Parkinson’s disease (PD) is poorly understood. We hypothesized differences in verbal fluency to letter condition versus animal condition and semantic integrity in individuals with PD who had either: a) memory problems (PD-Memory), b) processing speed difficulties (PD-Ex). These individuals were compared to cognitively well PD individuals and non-PD age matched controls. This was an IRB approved investigation of 40 idiopathic PD and 40 demographically matched peers. PD subtypes were based on apriori cognitive test patterns. SPSS-Statistics-v-20.0 was used for univariate ANOVA and independent t-tests. Controls performed better than all PD on both fluency measures [F(1,78)=4.84, p=.03]. PD-Exec performed lower than did PD-Well on both category [t(19)=-3.36, p=.003] and letter fluency [t(19)=-2.38, p=.03]. Groups were similar on a measure of semantic integrity. Thus, reduced verbal fluency is present in all PD subtypes and may be related to rapid recall deficits instead of diminished semantic integrity which is common among other neurodegenerative disorders.

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University of Florida
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University of Florida
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UF00091523_00602 ( sobekcm )

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University of Florida | Journal of Undergraduate Research | Volume 15 Issue 2 | Spring 2014 1 Understanding Motivators of and Barriers to Healthy Eating among African American Primary Care Givers with Children Enrolled in a Head Start Program Yekaterina Kokidko Tasia M. Smith, MS and Carolyn M. Tucker, PhD College of Liberal Arts and Sciences University of Florida Compared to their nonHispanic White counterparts, African American adults and children consistently exhibit a higher risk for and prevalence of obesity and obesity related diseases. Lack of engagement in healthy eating behaviors co ntributes to these health disparities and helps explain the disproportionately higher rates of obesity in African American families. The primary purpos e of this study was to examine socio demographic factors as predictors of motivators and barriers to enga ging in healthpromoting behaviors in an understudied sample of 49 African American primary care givers of children enrolled in a Head Start Program. A second purp ose of this study was to identify the strongest motivators of and barriers to engagement in h ealthy eating among this sample. Findings showed that socio demographic factors were not predictive of motivators or barriers to engagement in healthy eating behaviors. Results also showed that the strongest motivator to engaging in healthy eating behavior s was availability of healthy foods and the strongest barrier was self control. Implications of the studys results for health promotion and future research are discussed. INTRODUCTION Health disparities continue to exist among racial/ethnic minorities, and they disproportionately occur in African American populations (Plescia, Herrick, & Chavis, 2008). African Americans consistently exhibit higher rates of chronic diseases and poorer health outcomes (Rooks et al., 2008). Compared to their nonHispanic W hite counterparts, African Americans report eating fruits and vegetables fewer times per day and consuming fast food more times per day (Dubowitz et al., 2008; Sorkin & Billimek, 2012). Lack of engagement in healthy eating behaviors increases the risk for obesity and obesityrelated diseases such as diabetes, hypertension, and cardiovascular disease (Hildebrand & Shriver, 2010). Compared to 26% of White adults, 37% of African American adults are obese (Schiller et al., 2010). Additionally, African American adults are more likely to be told by a health professional that they have hypertension or diabetes (Schiller et al., 2010). Over 43% of African American adults have hypertension, which is one of the highest rates in the world (American Heart Association, 2010). African American children have disproportionately higher rates of obesity relative to their nonHispanic White peers (24%; 14% respectively, Ogden et al., 2012). Children who are obese are likely to be obese as adults and are at risk for health pro blems such as diabetes and cardiovascular disease (Freedman et al., 2009; Li et al., 2009). Given the less than adequate engagement in health promoting behaviors and the alarming rates of obesity and obesity related diseases among African American children and adults, it is important to understand factors that impact engagement in health promoting behaviors in general and healthy eating in particular among these groups. Previous research has shown that engagement in healthy eating behaviors is influe nced by multiple sociodemographic factors, including age, education, and employment status (Chang, Brown, Baumann, & Nitzke, 2008; Horodynski, Stommel, BrophyHerb, & Weatherspoon, 2010; Skala et al., 2012). Younger and less educated mothers consume less healthy foods such as chips, pretzels, and fast foods (Horodynski et al., 2010) than their older and more educated counterparts. Also, parents with some college or who are college graduates have a higher dietary quality and may have greater motivation for enrolling their children in Head Start programs, which expose parents to nutritioneducation trainings (Hildebrand & Shriver, 2010). Higher education is also a predictor of positive mood self efficacy, which is associated with fried food avoidance behavior s in low income African American mothers (Chang et al., 2008). Among African American families, limited accessibility to fruits and vegetables and lack of employment are associated with consumption of unhealthy foods (Horodynski et al., 2010; Skala et al., 2012). Low workforce participation is also associated with greater rates of hypertension, diabetes, and obesity in minorities, including African Americans (Jones & Sinclair, 2008). Studies have also shown that childrens eating behaviors are influenced by parents eating behaviors (Yeh et al., 2008). To help prevent and/or ameliorate the presence of obesity and obesity related diseases in children and their primary care givers, it is important to understand the

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Y EKATERINA KOKIDKO, TASIA M. SMITH, MS, & CAROLYN M. TUCKER, PHD University of Florida | Journal of Undergraduate Research | Volume 15 Issue 2 | Spring 2014 2 motivators of and barriers to engaging in hea lthy eating behaviors in childrens primary care givers. Motivators such as availability, health benefits (Yeh et al., 2008), routine (Hildebrand & Shriver, 2010), and medical issues motivate primary care givers to eat healthy foods and snacks and to provi de nutritious meals for their children (Tucker et al., 2011). Other important motivators include cost and convenience (Hildebrand & Shriver, 2010). For instance, Skala et al. (2012) found that low income African American families with preschool aged childr en reported purchasing canned or frozen produce due to convenience, shelf life, and lower costs. Some parents also have high self efficacy for serving fruits and vegetables at home (Hildebrand & Shriver, 2010). Another important motivator to healthy eating includes learning skills related to time management, goal setting and healthy food preparation (Burnet et al., 2008). Barriers such as availability (Hildebrand & Shriver, 2010), negative attitudes (Yeh et al., 2008), and self control discourage indiv iduals from engaging in healthy eating behaviors (Burnet et al., 2008; Tucker et al., 2011). For parents, factors that hinder increased fruit and vegetable availability include cost, low self efficacy for preparing foods, and lack of time for planning heal thy food preparation (Hildebrand & Shriver, 2010). The high availability of unhealthy foods as well as preferences for high fat foods contribute to unhealthy food choices among low income African American families (Burnet et al., 2008; Skala et al., 2012). African American families do not identify nutrition and weight loss as top priorities due to several factors including financial pressures and lack of health knowledge (Burnet et al., 2008). The major purpose of this study was to examine socio demog raphic factors (i.e., age, education level, and employment status) as predictors of motivators and barriers to engaging in healthpromoting behaviors (i.e., healthy eating) in an understudied sample of African American primary care givers with children enr olled in a Head Start Program. A second purpose of this study was to identify the strongest motivators of and barriers to engagement in health promoting behaviors (i.e., healthy eating) in this sample. The following hypotheses were tested: 1. Increasing levels of socio demographic factors (i.e., age, educational level, and employment status) are predictive of higher levels of motivation to engage in healthy eating behaviors. 2. Increasing levels of socio demographic factors (i.e, age, educational level and employment status) are predictive of lower levels of barriers to engaging in healthy eating behaviors. Additionally, the following resear ch question was addressed: What are the strongest motivators of and barriers to engagi ng in healthy eati ng behaviors among the participating African American primary care givers? METHOD Participants This study used data from the Health Smart Head Start Workshop, which was conducted to promote awareness of national childhood obesity in the United States. Th e workshop was an abbreviated version of Dr. Carolyn M. Tuckers six week Health Smart Behavior Program, which has been shown to be effective in increasing health promoting behaviors (e.g., healthy eating behaviors) in culturally diverse families. Particip ants in the present study were 49 African American primary care givers with a child or children enrolled in Alachua Countys Head Start Program, who participated in the workshop, which was conducted at Upper Room Church of God in Christ. Participants were recruited from four Head Start sites that were selected based on proximity to the location of the workshop. Participants were ages 18 63 ( M =34.30, SD =10.825). Most participants reported their level of education as high school or GED (52.5%) and employment status as work full time (36.2%). Additional demographic characteristics of the sample are in Table 1. Table 1. Demographic Characteristics of the Sample Variable n % Age Young Adult (18 39) 28 57.1 Middle Age (40 59) 11 22.4 Senior (60 +) 1 2.0 Unspecified 9 18.4 Education Junior High/Middle School 1 2.5 High School or GED 21 42.9 2 year college/trade school 15 37.5 4 year college 2 4.1 Graduate School 1 2.5 Employment Work full time 17 36.2 Work pa rt time 11 23.4 Currently unemployed but looking for a job 7 14.9 Do not work (stay at home parent, retired, on disability, etc.) 12 25.5 Measures Demographic Data Questionnaire (DDQ). The DDQ was constructed by the Principal Investi gator of the study to obtain the following participant information: (a) age, (b)

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HEALTH BEHAVIORS IN AFRICAN AMERICAN PRIMARY CARE GIVERS University of Florida | Journal of Undergraduate Research | Volume 15 Issue 2 | Spring 2014 3 highest level of education completed, and (c) employment status. The Motivators of and Barriers to Health Smart Behaviors Inventory (MB HSBI). The MB HSBI is a 127item inven tory designed to assess various motivators and barriers to engaging in healthpromoting behaviors (Tucker et al., 2011). The MB HSBI consists of four domains of health promoting (healthsmart) behaviors. These domains include eating a healthy breakfast, ea ting healthy foods and snacks, drinking healthy drinks, and engaging in physical activity (Tucker et al., 2011). The MB HSBI also consists of eight scales (i.e., a motivators scale and barriers scale for each of the four domains), sixteen motivators subsca les (e.g., routine, health benefits, medical issues, convenience), and twelve barriers subscales (e.g., negative attitudes, availability, self control). The present study used the scale scores (i.e., separate motivators and barriers scores) for the Healthy Foods and Snacks domain. Additionally, the following motivators subscales of the Healthy Foods and Snacks domain were used: motivators subscalesavailability (e.g., available fruits and vegetables in the home, and minimal to no preparation time for fruits and vegetables), routine (e.g., including healthy foods in daily routine and establishing goals for eating healthy foods), health benefits (e.g., preference for fruits and vegetables in maintaining weight and physical health), and medical issues (e.g., co nsuming fruits and vegetables to decrease the risk of developing hypertension, diabetes, and heart disease). Additionally, the following barriers subscales were used: negative attitudes (e.g., dislike for the taste of fruits and vegetables), availability ( e.g., lack of available healthy food options in snack machines and restaurants ), and self control (e.g., lack of self control in social settings and presence of cravings for unhealthy foods; Tucker et al, 2011). The MB HSBI instructs participants to rate their level of agreement with each item on it using a 4 point Likert scaling range from 1 ( strongly disagree ) to 4 ( strongly agree ). Scale and subscale scores are calculated by obtaining the mean for each scale or subscale. Higher means scores indicate hig her levels of motivators or barriers to engage in the identified health promoting behaviors. In the current sample, the internal reliabilities fo r the subscales are as follows: Healthy Foods and Snacks Motivators (.89), which includes routine (.88), availa bility (.76), health benefits (.89), medical issues (.88), and convenience (.59); and Healthy Foods and Snacks Barriers (.76) which includes negative attitudes (.89), availability (.60), and self control (.66). Procedure After institutional review board approval for this study was obtained, potential sites for recruitment of participants for the workshop were identified by the Alachua County Head Start Program Director. Sites were selected based on student numbers and proximity to the location of the wor kshop. After participating sites were identified, potential participants were recruited via distribution of participant recruitment flyers that identified the purpose of the workshop; the date, time, and location of the workshop; workshop activities; and c ontact information. The purpose of the workshop was to help primary care givers improve the health of their children and other family members. Reminder fliers were also sent home with children the day before the event. Workshop activities included informat ion on healthy foods and snacks, fun physical activities, door prizes, and healthy snacks. At the workshop, participants read, signed, and returned an informed consent form; completed a Demographic Data Questionnaire; and completed an assessment battery, which took approximately 30 minutes to complete. Research assistants briefly scanned the returned questionnaires to ensure that participants did not unintentionally skip questions on the page. To ensure participant confidentiality, any identifying informat ion that linked participants to the study was removed and the assessments were coded. RESULTS The first hypothesis, which examined the relationship between sociodemographic variables and motivation to engage in healthy eating, was tested using a regressio n analysis (see Table 2). The following socio demographic variables were entered as independent variables: age, educational level, and employment status. Motivators to eating healthy foods and snacks was entered as the criterion variable. The results revea led that increasing levels of socio demographic factors (i.e., age, educational level, and employment status) were not predictive of higher levels of overall motivation to engage in healthy eating behaviors, R2 = .16, F (3, 28) = 1.83, p = .165. Table 2. U nstandardized and Standardized Regression Equations for the Prediction of Higher Levels of Motivation from SocioDemographic Factors Unstandardized Coefficients Standardized Coefficients B SE t (Constant) 2.12 .51 4.15 Age .01 .01 .23 1.22 Edu .11 .13 .16 .86 Emply .13 .09 .29 1.51 The second hypothesis, which examined the relationship between sociodemographic variables and barriers to engage in healthy eating, was tested using a regression analysis (see Table 3). The following socio demographic variables were entered as independent variables: age, educational level, and employment status. Barriers to eating healthy foods and snacks was entered as the criterion variable. The regression analysis revealed that increasing levels of socio demographic factors (i.e., age,

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Y EKATERINA KOKIDKO, TASIA M. SMITH, MS, & CAROLYN M. TUCKER, PHD University of Florida | Journal of Undergraduate Research | Volume 15 Issue 2 | Spring 2014 4 educational level, and employment status) were not predictive of lower levels of overall barriers to engage in healthy eating behaviors, R2 = .15, F (3, 28) = 1.63, p = .205. Table 3. Unstandardized and Standardized Regressi on Equations for the Prediction of Higher Levels of Motivation from SocioDemographic Factors Variable Unstandardized Coefficients Standardized Coefficients B SE t Constant 2.12 .51 4.15 Age .01 .01 .23 1.22 Edu .11 .13 .16 .86 Emply .13 .09 .29 1.51 A means table was used to answer the research question, which sought to identify the strongest motivators of and barriers to engaging in healthy eating behavi ors among the participating African American primary care givers. Means and standard deviations were calculated for all healthy foods and snacks subscales (see Table 4 and Table 5). The strongest motivator was availability ( M =3.43, SD =.66), followed by hea lth benefits ( M =3.39, SD =.70), routine ( M =3.12, SD =.77), convenience ( M =3.04, SD =.66), and medical issues ( M =2.87, SD =1.03). The strongest barrier was self control ( M =2.94, SD =.71), followed by availability ( M =2.34, SD =.79), and negative attitudes ( M =1.95, SD =.78). Table 4. Descriptive Data for Motivators of Engaging in Healthy Eating Behaviors Variable M (SD) Availability 3.43 (.77) Health Benefits 3.39 (.66) Routine 3.12 (.77) Convenience 3.04 (.66) Medical Issues 2.87 (1.03) Table 5. Descripti ve Data for Barriers to Engaging in Healthy Eating Behaviors Variable M (SD) Self Control 2.94 (.71) Availability 2.34 (.79) Negative Attitudes 1.95 (.78) DISCUSSION The purpose of the present study was to examine the relationship between socio demogr aphic variables (i.e., age, educational level, and employment status) and motivators of and barriers to engagement in healthy eating behaviors. Another purpose of the study was to determine the strongest motivators of and barriers to engaging in healthy eating behaviors among the participating African American primary care givers. Hypothesis 1 stated that increasing levels of socio demographic factors (i.e., age, educational level, and employment status) will be predictive of higher levels of motivation to engage in healthy eating behaviors. The results did not provide support for this hypothesis. In other words, as age, educational level, and employment status increased, participants were not more motivated to engage in healthy eating behaviors. The second hypothesis, which stated that increasing levels of socio demographic factors (i.e, age, educational level, and employment status) will be predictive of lower levels of barriers to engage in healthy eating behaviors, was also not supported by the findings. T hese findings are quite surprising given that healthy eating behaviors are generally greater among older, more educated, and employed parents (Chang et al., 2008; Hildebrand & Shriver, 2010; Horodynski et al., 2010; Jones & Sinclair, 2008). It is possib le that examining the overall motivation and barriers to engagement in healthy eating behaviors masked the individual effects of specific motivators and barriers that are especially pertinent to African American families. Finally, the results of the anal yzed research question are noteworthy. The question sought to identify the strongest motivators of and barriers to engaging in healthy eating behaviors in the understudied sample of African American primary care givers. The strongest identified motivator w as availability of healthy foods. However, health benefits, routine, convenience, and medical issues were all fairly strongly motivators as well. These findings support previous research, which indicated the importance of availability and access to healthy foods (e.g., fruits and vegetables) as motivators of healthy eating behaviors (Yeh et al., 2008). Previous studies also found that health benefits (Yeh et al., 2008), routine, convenience (Hildebrand & Shriver, 2010) and medical issues (Tucker et al., 201 1) were significant motivators for increased familial engagement in healthy eating behaviors. The strongest identified barrier to healthy eating behaviors was self control. Availability and negative attitudes were less endorsed barriers among the sample. Self control may be the strongest barrier due to high availability of unhealthy foods and snacks at home and in social settings ( Burnet et al., 2008; Tucker et al., 2011). Previous research showed that lack of accessibility to healthy foods (e.g., fruits a nd vegetables) contributes to the consumption of unhealthy foods (Hildebrand & Shriver, 2010; Skala et al., 2012). It is important to note several strengths of the current study. First, the sample included African Americans primary care givers with childr en enrolled in a Head Start Program, which is a population overrepresented in chronic health conditions but understudied in research. Second, this study expands our understanding of eating behaviors in African American primary care givers. Since primary care givers significantly influence their childrens health behaviors (Yeh et al., 2008), it is essential to understand and address the

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HEALTH BEHAVIORS IN AFRICAN AMERICAN PRIMARY CARE GIVERS University of Florida | Journal of Undergraduate Research | Volume 15 Issue 2 | Spring 2014 5 motivators of and barriers to health behaviors that reduce childhood obesity and other obesityrelated illnesses in childr en. It is also important to point out the limitations of this study. One limitation of this study is that it was conducted with a small sample, which does not allow much statistical variance to establish significance. Also, the generalization of the f indings is limited to African American primary care givers with children enrolled in the Head Start Program focused on in this study. Additionally, this study was based entirely on self report measures. Social desirability may have affected the extent to w hich participants reported motivation of and barriers to engagement in healthy eating behaviors. That is, levels of motivation and levels of barriers may not have been accurately reported by participants. Lastly, the African American primary care givers in the present study were volunteers. Individuals that decided to participate may have been more motivated and may have been more exposed to nutrition programs in the Head Start Program that was the focus of the present study. Future similar research should include a larger and randomly selected sample, which will increase the generalizability of the findings. Despite the limitations of this study, the findings are noteworthy given their identification of important motivators and barriers of engaging in healt hy eating behaviors among African American primary givers. If the findings in the present study are supported by future studies, support will be provided for developing interventions that focus on increasing motivators that enhance engagement in healthy eating behaviors and decreasing barriers that prevent engagement in healthy eating behaviors among African American primary caregivers. Further research should focus on a similar, larger sample to better understand which sociodemographic factors are predict ive of higher levels of overall motivation and lower levels of overall barriers to engaging in healthy eating behaviors. Findings from such research will enable health care providers to establish culturally sensitive interventions that increase healthy eat ing behaviors in African American populations. In turn, the risk for and prevalence of obesity and obesity related diseases such as diabetes, hypertension, and cardiovascular disease in African American adults and children will likely decrease. REFERENCES American Heart Association. (2010). Heart disease and stroke statistics -2010 update: A report from the american heart association. Circulation, 121 (7), e46 215. doi: http://dx.doi.org/10.1161/CIRCULATIONAHA.109.192667 Burnet, D. L., Plaut, A. J., Ossows ki, K., Ahmad, A., Quinn, M. T., Radovick, S., Gorawara Bhat, R., & Chin, M. H. (2008). Community and family perspectives on addressing overweight in urban, african american youth. JGIM: Journal of General Internal Medicine, 23 (2), 175 179. doi: 10.1007/s1 1606 007 0469 9 Chang, M., Brown, R. L., Baumann, L. J., & Nitzke, S. A. (2008). Self efficacy and dietary fat reduction behaviors in obese african american and white mothers. Obesity, 16 (5), 992 1001. doi: 10.1038/oby.2008.20 Dubowitz, T., Heron, M., Bi rd, C. E., Lurie, N., Finch, B. K., Basurto Davila, R., Hale, L., & Escarce, J. J. (2008). Neighborhood socioeconomic status and fruit and vegetable intake among whites, blacks, and mexican americans in the united states. The American Journal of Clinical N utrition, 87 (6), 1883 1891. Freedman, D. S., Wang, J., Thornton, J. C., Mei, Z., Sopher, A. B., Pierson, R., J., Deitz W.H., & Horlick, M. (2009). Classification of body fatness by body mass index for age categories among children. Archives of Pediatrics & Adolescent Medicine, 163 (9), 805 811. doi: http://dx.doi.org/10.1001/archpediatrics.2009.104 Hildebrand, D. A., & Shriver, L. H. (2010). A quantitative and qualitative approach to understanding fruit and vegetable availability in low income african american families with children enrolled in an urban head start program. Journal of the American Dietetic Association, 110 (5), 710 718. doi: 10.1016/j.jada.2010.02.012 Horodynski, M. A., Stommel, M., Brophy Herb, H., & Weatherspoon, L. (2010). Mealtime televisi on viewing and dietary quality in low income african american and caucasian mother toddler dyads. Maternal and Child Health Journal, 14 (4), 548 556. doi: 10.1007/s10995 009 0501 2 Jones, G. C., & Sinclair, L. B. (2008). Multiple health disparities among mi nority adults with mobility limitations: An application of the ICF framework and codes. Disability & Rehabilitation, 30 (12), 901 915. doi: 10.1080/09638280701800392 Li, C., Ford, E. 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Y EKATERINA KOKIDKO, TASIA M. SMITH, MS, & CAROLYN M. TUCKER, PHD University of Florida | Journal of Undergraduate Research | Volume 15 Issue 2 | Spring 2014 6 Tucker, C. M., Rice, K. G., Hou, W., Kaye, L. B., Nolan, S. E. M., Grandoit, D. J., Gonzales, L., Smith, M. B., & Desmond, F. F. (2011). Development of the motivators of and barriers to health smart behaviors inventory. Psychological Assessment, 23 (2), 487 503. doi: 10.1037/a0022299; 10.1037/a0022299.supp (Supplemental) Yeh, M. C., Ickes S. B., Lowenstein, L. M., Shuval, K., Ammerman, A. S., Farris, R., & Katz, D. L. (2008). Understanding barriers and facilitators of fruit and vegetable consumption among a diverse multi ethnic population in the USA. Health Promotion International, 23 (1), 42 51. doi: http://dx.doi.org/10.1093/heapro/dam044