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The purpose of this study is to (a) assess the effectiveness of culturally tailored diabetes prevention interventions in minority populations and (b) develop a novel framework to characterize four key domains of culturally tailored interventions. Prevention strategies specifically tailored to the culture of ethnic minority patients may help reduce the incidence of diabetes.
We searched PubMed, EMBASE, and CINAHL for English-language, randomized controlled trials (RCTs) or quasi-experimental (QE) trials testing culturally tailored interventions to prevent diabetes in minority populations. Two reviewers independently extracted data and assessed risk of bias. Inductive thematic analysis was used to develop a framework with four domains (FiLLM: Facilitating [i.e., delivering] Interventions through Language, Location and Message). The framework was used to assess the overall effectiveness of culturally tailored interventions.
Thirty-four trials met eligibility criteria. Twelve studies were randomized controlled trials, and 22 were quasi-experimental trials. Twenty-five out of 34 studies (74%) that used cultural tailoring demonstrated significantly improved Hemoglobin A1C, fasting glucose, and/or weight loss. Of the 25 successful interventions, 21 (84%) incorporated at least three culturally targeted domains. Seven studies used all four domains and were all successful. The least utilized domain was delivery (4/34) of the intervention’s key educational message.
Culturally tailoring interventions across the four domains of facilitators, language, location, and messaging can be effective in improving risk factors for progression to diabetes among ethnic minority groups. Future studies should evaluate how specific tailoring approaches work compared to usual care as well as comparative effectiveness of each tailoring domain.
(PROSPERO registration: CRD42015016914)
Ethnic minority groups in high-income countries such as the United States (US) and the United Kingdom (UK) suffer disproportionately from diabetes-related complications 1. In the UK, ethnic minority groups such as African Caribbean and South Asians have an estimated 5.7% prevalence rate of type 2 diabetes (T2DM) compared to 1.7% of whites 1. Similarly in the U.S., the risk of diabetes is 77% higher among African Americans and 55% higher in Latino Americans than among non-Latino white Americans 2. While genetic differences may partially account for these differences, failure to consider cultural and social factors may also limit the efficacy of strategies to prevent diabetes in ethnic minority groups.
The landmark US Diabetes Prevention Program (DPP) study showed that modest lifestyle changes (>7% reduction of weight and physical exercise of >150min/ week) reduced the risk of progression of pre-diabetes to diabetes 3. Interventions incorporating such lifestyle changes found similar reductions in diabetes incidence in countries as diverse as Finland, India, and China 4,5. While promising, none of these studies explicitly targeted ethnic minority populations. This gap is important because a growing body of evidence suggests greater effectiveness of targeted health programs compared to generic programs in ethnic minority groups 6,7. Fisher et al.8 noted that prior researchers have used the terms cultural competence, cultural tailoring, and cultural targeting in interchangeable ways to define strategies to address culture. In this paper, the terms cultural targeting and tailoring include strategies that improve the health of a racial and ethnic population by taking into account their cultural practices, attitudes, and beliefs. The distinction between targeting (which is often thought as group level programming), and tailoring (which is thought of as individual level programming as these concepts often overlap in community-based interventions), is not made.
Recently, a number of pilot studies and randomized controlled trials (RCTs) have tested targeted programs to prevent diabetes in specific populations. While reviews evaluating culturally tailored interventions for diabetes management strategies exist 8–13, these do not focus exclusively on diabetes prevention interventions across ethnic groups. Moreover, none of these studies, to our knowledge, to have sought to develop a framework to characterize and evaluate the efficacy of different tailoring domains.
Accordingly, the specific aim of this systematic review is to answer the question: What is the effectiveness of culturally targeted interventions in preventing diabetes onset, improving control, or reducing weight in adult ethnic minority groups? To answer this question, qualitative methods were used to develop a framework that characterizes the modalities of cultural targeting within each intervention to better understand which domains were necessary to build successful interventions.
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations in conducting this meta-analysis 14. With the assistance of a medical research librarian (MC), we performed serial literature searches for English language articles. MEDLINE via PubMed, CINAHL, and EMBASE were searched for studies published between 1997 and 2016 using Medical Subject Headings (MeSH) and keywords based on diabetes prevention interventions, cultural targeting, and ethnic minority groups (Appendix Table 1: Search strategy). All human studies published in full-text were eligible for inclusion; no publication date or status restrictions were placed. Additional studies of interest were identified by hand searches of bibliographies. The search was last updated on May 5, 2016.
Two reviewers (PL and MH) independently screened titles and abstracts for eligibility. Articles were included if: (1) the intervention targeted ethnic minority groups, defined as people who differing in physical or cultural traits, race, nationality, or religion from the dominant group of the community they live in; (2) the intervention’s objective was diabetes prevention with one or more of the following outcomes: a reduction in Hemoglobin (HgbA1C), fasting glucose, or weight; (3) the participants were adults (18 years or older) at risk for type 2diabetes but not currently having a diagnosis of diabetes; and (4) the study utilized a randomized or quasi experimental trial design. Studies not meeting all of these criteria (e.g., diabetes management, observational designs) were excluded.
Two reviewers used a standardized form adapted from the Cochrane Collaboration 15 to extract data from the included studies independently and in duplicate. For all studies, we extracted the following data: study design, setting, population characteristics, intervention design and duration, cultural strategies (e.g. facilitators, language, location, and message), delivery staff, outcome measures, and major findings. Studies were dichotomized into successful and unsuccessful based on statistical significance of results. Therefore, a study was categorized as being successful if the majority of participants demonstrated a statistically significant (p<0.05) improvement in at least one of the following outcomes: HgbA1C, fasting glucose, or weight loss. If/when a study did not report p-values, we required that greater than 80% of participants had to show improvement in HgbA1C, fasting glucose, or weight loss to be considered successful. We picked this definition of success as the majority of included studies were pilots and were not powered to detect the conventional 5–7% weight loss goal that the original diabetes prevention program study used3.
Two authors (SP and ST) independently assessed risk of bias via the Quality Assessment Tool for Quantitative Studies, an instrument developed by The Effective Public Health Practice Project. This tool utilizes the following elements to assess quality: selection bias, study design, confounders, blinding, data collection methods, and withdrawals and drop-outs. A score of 1 therefore indicates a low risk of bias, while 3 indicates a higher risk of bias. Accordingly, we assigned studies scores of 1 to 3 to all studies 16.
Any discrepancies or disagreements in data review, extraction, or assessment of quality were resolved by a third reviewer (PL).
Prior studies have tried to assess cultural competency with various tools including the Cultural Competency Assessment Tool (CCAT)10. However, this tool only provides an overall competency score that is heavily weighted to assess cultural competency of providers and facilitators and does not intuitively allow evaluators to identify the specific domains of cultural targeting that are utilized by each intervention. In addition, this tool requires an investigator to have the tool accessible to systematically score each study. For this reason, we used an inductive thematic analysis approach to develop a framework to assess cultural targeting, focusing on the underlying intervention within included studies to establish common domains that could more easily be implemented 17.
We began by compiling a list of cultural targeting competent concepts by listing every culturally relevant targeting strategy incorporated into each intervention to create a conceptual model of cultural targeting. Using these constructs, each study was then categorized independently by two coders (SP and ST) into four central domains: facilitators, language, location, and messaging (Fig. 1). For example, strategies that involved targeting the content of the intervention in the areas of faith, food choices, gender or family were collapsed into the messaging domain. Theoretically, facilitators (i.e., who delivers the program) potentially increase participant recruitment, engagement, and efficacy by addressing language (linguistic concordance to local dialect or health literacy), location (faith-based or community-based center as a venue for the intervention), and messaging (targeting either the content or the mode of delivery of the educational message). In comparison, targeting to language, location, and messaging work as individual components that can directly increase participation in interventions regardless of the program facilitators. We named the taxonomy, FiLLM, an acronym for “Facilitating Interventions through Language, Location, and Message.”
To assess the performance of our novel framework and for informational purposes (as no gold standard tool to assess cultural targeting exists), we compared performance to an available cultural competency assessment tool (CCAT) 10. Each evaluated intervention was scored from 0–100% on a scale of cultural competency 10. The CCAT score was then compared to the number of culturally targeted domains (1–4) each study addressed (Appendix Table 2).
Within the facilitators (i.e. the staff who delivered the intervention) domain, community health workers (CHWs) were defined as formally trained health personnel from the community who shared cultural, economic, linguistic or other core characteristics with the patients they are serving. Community-based facilitators were defined as members from the community of the same racial and ethnic identity that spoke the same language who did not undergo any formal health related training. Health care professionals encompassed physicians, nurses, or research investigators. Within the language domain, linguistic concordance was defined as the translation of presentation or materials to the preferred language of the participants 18. Literacy was defined as a modification of the curriculum to fit the language competence of the target population. The location domain encompassed the setting or venue where the intervention took place and was hypothesized to improve health outcomes by improving access to health interventions. The messaging domain included both the educational content of the intervention as well as the mode of delivery of the intervention. Message content targeting clustered into four subcategories: diet, faith, family, and gender. Community-based participatory research (CBPR) was defined as engaging the community in all aspects of the research process (i.e. study design, implementation, and evaluation), whereas community engagement has some, but limited, input from community members 19.
Our literature search retrieved a total of 1242 articles. Initial screening eliminated 1149 articles at the title and abstract level for not fitting the inclusion criteria of targeting adult ethnic minority groups, focusing on diabetes prevention with a measurable outcome of Hemoglobin A1C, fasting glucose, or weight change, or not utilizing a randomized or quasi-experimental trial design. Following full review of each remaining article, 39 articles were eliminated because they were either: (1) not interventions, (2) not addressing diabetes prevention, or (3) not culturally targeted (Fig. 2). Three studies screened for diabetes at the onset of the study and did include some participants with a diagnosis of diabetes. These studies were included as the primary focus was diabetes prevention and the majority of participants did not carry a diagnosis of diabetes 20–22. The 34 articles that met the eligibility criteria are summarized in Table 1.
Twenty-six studies were based in the United States, 2 in India, 2 in Canada, 1 in New Zealand, 1 in the United Kingdom, 1 in Norway, and 1 in the Netherlands. Participants in the studies included African American (11), Hispanic/Latino (10), Arab American (1), Native Hawaiian and Other Pacific Islander (2), Native North American (2), Alaskan Eskimo (1), Canadian Aboriginals (1), South Asian (5), Chinese Americans (1), Korean Americans (1) ethnic groups. Eighteen studies explicitly stated that the intervention targeted low-income populations.
The majority of included studies (22/34) were quasi-experimental trials; twelve studies were randomized controlled trials (RCT). Two-thirds (22/34) of the studies engaged the community: fourteen studies used CBPR principles in the intervention, and the other 8 studies used community engagement. The majority of interventions were set in a community center (32/34) with two set in a healthcare clinic 19,23. Interventions were delivered by a number of individuals including CHW (14/34), community-based facilitators (10/34), or health care professionals/others (10/34). Only 9/34 studies had interventions lasting longer than 12 months. Table 2 describes the study characteristics in detail. Specifics on how each intervention used the four FiLLM domains are provided in the next four sections.
Of the 34 included studies, two-thirds (27/34) were conducted by members of the community. These individuals were from the same cultural and social background as the ethnic minority group, thus furthering the cultural targeting of the intervention. Fourteen studies used CHWs as facilitators 24–36. Balagopal et al. specifically stated that CHWs were selected to strengthen the links among project personnel, the community, and existing community networks 37. Ethnically similar facilitators were purposefully selected to help break down the mistrust of research and researchers in the community in one study 38. Gutierrez et al., a study located in a faith-based location, selected facilitators based on religious orientation 39.
All but eight (N=27) of the interventions that used culturally targeted facilitators were successful. Faridi et al., one unsuccessful study, used CHWs yet found no significant difference in weight loss, BMI, physical activity, or dietary habits between intervention and control 29. Although this study used CHWs as facilitators, the authors noted that the CHWs designed their own curricula and subsequently had varied approaches with participants, an inconsistency that may explain the negative results observed 29. Ho et al., the second unsuccessful study, noted that their facilitators did engage the community members while planning a culturally appropriate activities however they often had limited time to work with the community as they were only employed part-time 22.
Twenty-two of the 34 studies used language as a strategy to culturally target their intervention with bilingual facilitators provided in 21of these interventions. In addition, a few studies incorporated linguistically appropriate curriculum materials targeted to their participants’ preferred language 27,28,38,40–44. For example, Islam et al. targeted Sikh Asian Indians and therefore developed curriculum materials in English, translated them into Punjabi and reviewed the material with bilingual study staff 28. Similarly, Ockene et al. printed questionnaires in Spanish and English and administered the intervention orally in Spanish for its Caribbean Latino participants. Ockene et al. also utilized visual adaptation and hands-on experiences of the materials to simplify complex concepts 43.
Eleven studies also used low-literacy materials in their interventions 20,27,34,35,40,43–48. For example, Kaholokula et al. rewrote the Diabetes Prevention Program Lifestyle Intervention to simplify the language into “plain language” and Balagopal et al. adjusted the curriculum for low levels of health literacy as 41% of its target population of rural Indians had less than a 5th grade education.
Almost all interventions that used language as a cultural targeting strategy were successful with a statistically significant change in HgbA1C, fasting glucose, or weight loss (19/22; p<0.05).
The majority of studies used location as a strategy to culturally target their interventions (30/34). Nine of these studies used a faith-based center (e.g. church) in hopes of increasing trust, engagement, and recruitment in their respective populations 24,29,31,39,42,44,49–51. For example, both Simmons et al. and Gutierrez et al. reported selecting churches as the venue for their program since the population targeted used the church as a source of support and frequently attended church 39,42.
Twenty two studies (22/34) used community-based centers such as senior centers, social service agencies, cultural centers, and schools to culturally target their intervention. Ruggiero et al. noted that community-based centers were chosen as a location to increase access for participants 32. Seven of the 30 studies using location as a means of cultural targeting were unsuccessful. Four out of the seven unsuccessful studies used community centers, such as schools and stores, and found no significant change in BMI or weight loss20,22,34,52 and three studies were conducted in a faith-based centers 29,51,53.
More than half of the studies (27/34) targeted the content of the message of their intervention, with three studies targeting the mode of delivery. Twenty studies tailored their intervention message content to the diet of the participants 21,23,27,28,30,33–35,39,41–43,48,51,52,54–57. For example, Ebbesson et al. targeting Alaskan Eskimos worked to reverse the trends of acculturation by encouraging more traditional, healthier foods and less consumption of store-bought unhealthy foods 21. Ockene et al. also used customized traditional recipes for a Caribbean Latino population 43. Similarly, Vincent et al. conducted cooking demonstrations using a low-fat version of traditional Mexican American foods to incorporate the traditional dietary patterns of his Hispanic population 30.
Twelve studies targeted their content based on faith 24,28,31,39,41,42,44,49–51,54,58. Conlon et al. focused on honoring spiritual beliefs and “encouraged Black and Hispanic/Latino participants to use spirituality and their spiritual community as a coping mechanism54.” Amongst a Sikh Asian Indian community, Islam et al. discussed the “Saint-Soldier,” a concept in Sikhism that emphasizes discipline in spiritual practice and social responsibilities 28.
Five studies tailored messages based on participant gender 37,41,48,52,59. Jaber et al. hypothesized that Arab American women tend to have more influence over the family’s nutritional intake, so specifically targeted the health messaging towards women41. In addition, this study created gender-specific sessions and segregated physical activity classes. Balagopal et al. also tailored the messaging for health education based on gender 37.
Eight studies targeted content based on family 23,33,35,36,41,44,45,56. For example, Jaber et al., noting the central role of the family among Arab Americans, actively recruited family members to participate in activities and sessions 41. Family was also utilized to enhance male participation and promote communication within the family about healthy food participation41. Another study targeting Native Hawaiians and other Pacific Islanders, similarly noted that participants endorsed strong family values during orientation and sought to identify and focus on social/community and family factors in their curriculum45. Vincent et al. invited the participants to bring a support person because of the cultural importance of family amongst his target population of Hispanics 30.
There was significant overlap among the four subcategories of content (food choices, faith, family, and gender) and 14 out of 27 studies tailored to more than one subcategory.
Only three studies considered how to deliver the message to the target population 20,22,43. Ockene et al noted that watching soap operas was a popular activity among Caribbean Latinos and thus used a telenovela to deliver part of the intervention 43. In addition, Daniel et al. targeted Canadian Aboriginals by using local television and radio stations to “carry stories” to the community 20. Ho et al. altered the timing of the delivery of the message based on community recommendations and conducted the demonstrations at stores on pay-days to increase participation in the intervention 22.
Eleven studies that used all four FillM domains were successful 27,28,30,35–37,39,41,43,45,57. Of the 25 successful studies, 21 (84%) incorporated at least three culturally targeted domains in their study. In contrast, only one of the nine unsuccessful studies tailored to all four domains34.
The majority of studies culturally tailored to location of intervention (30/34), but fewer tailored to language (22/34), message (25/34) and program facilitators (27/34). Of the messaging domain, however, a very small minority (4/34) tailored the mode the delivery.
In addition, there was some concordance with the CCAT tool and the number of FiLLM domains utilized irrespective if they were categorized as successful. Twelve studies, irrespective of if they were successful or not, used all four domains and all of these scored on average 95% on the CCAT tool. In contrast, 10 studies used 2 or less FiLLM domains and their average CCAT score was 75% (Appendix Table 2).
Using the Quality Assessment Tool for Quantitative Studies 60, 27 of the studies were determined to be at low risk of bias20,22,23,25–29,31,32,34,35,37,39–41,43–49,51,52,54,57,59,60, whereas seven were rated as having a moderate risk of bias21,24,33,36,42,50,55. Of those four studies, three scored as having a higher risk of bias due to participant withdrawals and drop-outs21,24,33,55. Simmons et al. scored as higher risk due to data collection methods, as the participants were highly mobile and the population changed as measurements were taken 42. O’Brien et al. and Davis-Smith et al. were scored at a higher risk due to study design with small sample sizes36,61.
In this systematic review of culturally tailored diabetes prevention programs among adults belonging to ethnic minority groups, a majority (25/34) of the reviewed interventions were effective at reducing HbA1C, weight and BMI. Overall, studies that tailored interventions to all four domains of facilitators (program deliverers), location, language, and messaging, were successful. Conversely, the unsuccessful studies targeted to fewer domains. Finally, the least utilized domain was culturally targeted messaging content and delivery.
Our findings reinforce the fact that cultural tailoring is a necessary means to adapt interventions to specific ethnic minority populations. In addition, our findings expand on prior work by better identifying how the effectiveness of an intervention might vary according to the number and type of culturally specific domains included. For example, within the facilitators domain, we found that the majority of studies employed CHWS or program facilitators similar to the target population in language and ethnicity. Our results align with a prior review that found that interventions delivered through CHWs are an especially promising strategy for improving diabetes outcomes specifically in low-income and racial and ethnic minority populations 62. CHWs and other facilitators theoretically improve their relationships with participants by working through FiLLM’s three other domains of language, location, and messaging. In addition, our review found that interventions resulted in better patient outcomes when linguistic concordance and literacy were taken into account. These results are in agreement with prior research that has shown that ethnic minority patients were more likely to trust their providers when there were interpreters or when the physician spoke their language 63. Finally, with respect to location, we found that almost every study (30/34) chose a culturally specific location, making location the most utilized cultural targeting domain. By tailoring to location, these studies theoretically created a safe, comfortable environment and also increased convenience by picking locations that were familiar to the participants.
By separating the specific cultural targeting domains and the effectiveness of each of these domains, we highlight gaps in the current literature and opportunities for future research. Most notably, none of the studies in our review were designed to specifically evaluate the mechanisms by which different forms of cultural targeting affect patient outcomes. In order to maximize the benefits from targeting interventions to culture, future studies must focus on potential mediators of such effects including level of trust, understanding, satisfaction with information, support, self-efficacy, and level and type of motivation. This level of tailoring has been termed deep structure tailoring and evaluates what cultural values and experiences change populations’ perceptions of their health and their health related behavior64. This deep level of tailoring also accounts for acculturation, which was not well measured in the majority of the studies or specifically evaluated as an effect modifier in any of these studies. In addition, it will be useful to assess characteristics of participants who most benefit from different forms of cultural tailoring and how that also may enhance participation retention. Furthermore, only four studies specifically designed a culturally targeted mode of delivery for the messaging. As health systems utilize innovative health technology and mobile health tools, researchers should study how to build culturally competent messaging and delivery models to engage a diverse population65. Finally, as policy makers consider widespread implementation and dissemination of diabetes prevention programs, future studies should further elucidate the types of cultural targeting most successful in increasing recruitment, engagement, and maintenance in intervention programs. More detail is necessary on the strategies used to culturally tailor the content and delivery approaches of interventions as well as on the extent to which evidence-based behavioral strategies were used in the interventions to promote behavior change, and if so, which ones.
This study has important limitations. First, we restricted our literature search to English language articles. Therefore, relevant studies published in other languages may have been missed. Second, due to variability in outcomes and a limited number of randomized trials a formal meta-analyses was not conducted. However, the search did yield three protocols published in the last two years for randomized controlled trials that will provide updated evidence and may allow formal meta-analyses in the coming years 66–68. This study will help guide such future research with respect to evaluation of intervention efficacy and fidelity across four domains while considering potential mediators of health outcomes (e.g. engagement, trust). Third, success was defined as a dichotomous outcome based on statistical significance and p-value of <0.05, an approach that may overestimate the number of successful studies and not capture clinical significance. With only nine unsuccessful studies included, predictions on what cultural tailoring factors may lead another study to be unsuccessful cannot be made. Fourth, comparisons between ethnic populations could not be performed, as some ethnic subgroups had too few studies to make such comparisons. Theoretically, different domains may not be weighted equally for all populations. For example language may not be as important as facilitators and messaging in an African-American population compared to a Latino population. Finally, the majority of the studies included did not have a comparison group, and none evaluated the comparative effectiveness of different tailoring strategies. Future work should also compare which specific types of tailoring within each domain are most effective.
This study also has notable strengths. First, to our knowledge this is the first systematic review that focuses on cultural targeting in diabetes prevention among ethnic minority groups. Diabetes prevention programs are currently a priority for policy and community advocacy groups worldwide 49. Thus, the focus on studies that evaluate prevention and not diabetes management interventions among ethnic minority populations addresses a critically important need 3–5. Second, this study introduces a novel four-domain taxonomy, FiLLM, to both evaluate and explicate results. Third, it identifies domains that can be easily harnessed and utilized by researchers, community leaders, and policy experts who are interested in designing and implementing culturally targeted interventions addressing a range of health conditions in ethnic minority groups. Fourth, this study shows gaps and highlights avenues for future research in examining mediators and moderators within targeted interventions.
In conclusion, this systematic review presents the state of evidence on culturally tailored diabetes prevention interventions in ethnic minority groups. It further identifies a framework of four key domains that can be easily adopted and utilized when designing and evaluating future culturally targeted interventions. By targeting interventions across all four of these domains, future interventions can more effectively help ethnic minority populations adopt healthier behaviors to reduce their risk of diabetes and other preventable conditions. As diabetes prevalence continues to increase worldwide, sound research design and evaluation of culturally targeted diabetes prevention needs to be a key priority amongst researchers and policy makers.
The authors would like to acknowledge Marisa Conte, our medical research librarian for assistance with development of the electronic search strategy and Kasia Klasa for research assistance.
PRIMARY FUNDING SOURCE: Robert Wood Johnson Clinical Scholars Foundation and Grant Number P30DK092926 (MCDTR) from the National Institute of Diabetes and Digestive and Kidney Diseases.
CONFLICTS OF INTEREST: none