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Contemporary Clinical Trials Communications logoLink to Contemporary Clinical Trials Communications
. 2021 Jan 11;21:100710. doi: 10.1016/j.conctc.2021.100710

Family model diabetes self-management education and support in faith-based organizations in the republic of the Marshall Islands study protocol

Pearl A McElfish a,, Janine Boyers b, Rachel S Purvis a, Betsy O'Connor b, Ayoola Carleton b, Williamina Bing b, Brett Rowland b, Craig Molgaard c, Ainrik George d, Lydia R Tibon e, Dalton Hoose a, Sheldon Riklon a
PMCID: PMC7815654  PMID: 33506140

Abstract

Background

Marshallese living in the Republic of the Marshall Islands (RMI) experience significant health disparities, with high rates of type 2 diabetes mellitus. In addition to health disparities, the RMI experienced nuclear testing that exposed inhabitants to nuclear fallout, unethical research practices, and contaminated natural food sources.

Objectives

This research uses a community-based participatory research (CBPR) approach to effectively engage community partners and honor their contributions in all stages of the research. A CBPR approach will leverage culturally situated knowledge and practices of the Marshallese community in the RMI to ensure the success of the research.

Methods

This manuscript describes the methods used to test the feasibility of delivering a culturally adapted family model of diabetes self-management education and support in faith-based organizations in the RMI.

Conclusions

This manuscript describes the protocol for creating working with community partners and implementing a feasibility study in the RMI.

Keywords: Pacific islanders, Marshallese, Type 2 diabetes mellitus, Family model of diabetes self-management education and support, Health disparities, Community-based participatory research, Republic of the Marshall Islands

1. Introduction

The Republic of the Marshall Islands (RMI) is an independent United States Affiliated Pacific Islands (USAPI) nation with a population of 77,917 [1]. The RMI signed a Compact of Free Association (COFA) agreement with the United States (US) in 1986 that allows Marshallese residents to live, work, and travel to the US without the need for visa or work certification, and it provides the US with an exclusive lease and control of a military base in a strategic Pacific location [2]. The Marshallese population in the RMI face significant health disparities with especially high prevalence rates of type 2 diabetes mellitus (T2DM) [[3], [4], [5], [6], [7], [8]]. Diabetes among Marshallese adults in the RMI (33.8%) is significantly higher than global (9.3%) and US (13.3%) rates [9]. The International Diabetes Federation ranks the RMI as the country or territory with the highest age-adjusted comparative diabetes prevalence in adults (30.5%) for 2019 [9].

These health disparities are exacerbated by the historical trauma of nuclear testing conducted in the RMI by the US military between 1946 and 1958 [10]. The nuclear testing exposed many Marshallese to nuclear fallout, and impacted the natural environment [10,11]. American scientists studied the effects of nuclear fallout on humans in the RMI with Project 4.1; however, study materials were not translated into Marshallese and participants did not provide informed consent [10]. In addition, these nuclear weapons tests contaminated local food sources and significantly altered the traditional diet of Marshallese [[10], [11], [12]]. Commodity foods such as rice and canned meats replaced locally sourced fresh fish and fruits and vegetables [13,14]; and as a result, Marshallese transitioned to a diet high in simple carbohydrates and fat and low in fresh fruits and vegetables [12,13].

Diabetes self-management education and support (DSMES) is an evidence-based intervention that can improve risk factors, help patients effectively manage their condition, and is critical for persons with diabetes [[15], [16], [17], [18], [19]]. However, positive results are not shared equally across all racial/ethnic groups [[20], [21], [22]]. Culturally-appropriate family models of DSMES using community health workers (CHWs) have been shown to improve diabetes self-management for African-American, Hispanic/Latinx, and Native American communities [[19], [20], [21], [22], [23], [24], [25]]; however, there is limited DSMES research among Marshallese and other Pacific Islanders [26, 27]. There has been one published study of DSMES in the RMI, which was unable to document improvements in glycemic control or other diabetes-related outcomes [28]. Given the epidemic of T2DM in the RMI, it is critically important to determine an effective DSMES intervention and to broadly disseminate and implement the intervention.

The authors developed and tested a culturally adapted family model of DSMES (F-DSMES) with the Marshallese community in Arkansas [29,30]. The F-DSMES intervention was delivered to primary participants and at least one of their family members. The intervention was delivered in primary participants' homes by a bilingual CHW with a certified diabetes educator (CDE) present. The F-DSMES demonstrated effectiveness compared with standard DSMES delivered by CDEs in a group setting [31,32]; however, the methods used in this previous trial may not be directly transferable to the RMI. The RMI lacks the resources to deliver standard DSMES effectively due to a lack of CDEs in the RMI. Furthermore, the size of most homes in the RMI is not conducive to family education. As a result, the present study has several important differences from the prior F-DSMES trial conducted in Arkansas. First, the F-DSMES intervention will be delivered by trained CHWs without a CDE present. Second, the intervention will be delivered in faith-based organizations (FBOs) rather than in participants’ homes. Finally, the study will take place in the RMI, not in the US.

This paper presents the study protocol for a pilot evaluation of the F-DSMES. All study procedures were approved by the University of Arkansas for Medical Sciences Institutional Review Board (IRB #239272).

2. Materials and methods

2.1. Study aims and design

This study will evaluate the preliminary feasibility, acceptability, and effectiveness of F-DSMES among primary participants and their family members when delivered by CHWs in the RMI. The pilot study will be a one-arm trial with outcomes measured at baseline (pre-intervention) and follow-up (immediate post-intervention, four months post-intervention, and 12 months post-intervention).

2.2. Community-based participatory research

This study will utilize a community-based participatory research (CBPR). CBPR fosters research that is equitable and ethical [[33], [34], [35]]. A CBPR approach is especially important given the historical trauma experienced by the Marshallese people. This trauma comes from their experience with the nuclear weapons tests conducted in the RMI by the US military and the resulting unethical scientific research on those Marshallese who were exposed to the nuclear fallout [10]. CBPR engages community partners and honors their unique contributions at all stages of the research [[36], [37], [38], [39], [40], [41], [42], [43]]. CBPR also ensures Marshallese cultural knowledge will inform the research, so that it is culturally acceptable and, as a result, increases the likelihood of implementation and sustainability [33,34,44]. Grounding the study in CBPR methods will allow the team to integrate and leverage the contextually- and culturally-situated knowledge, practices, and resources of the Marshallese community in the RMI.

2.3. Community partners

Community partners in the RMI include the RMI Ministry of Health and Human Services (MHHS), the Marshallese Educational Initiative (MEI), and Kora In Jiban Lolorjake Ejmour (KIJLE) (roughly translated to “Women for Health”). The RMI Constitution designated the MHHS as the state health agency to help researchers appropriately implement research activities in the RMI [45]. MEI is a non-profit organization headquartered in Springdale, Arkansas, that promotes cultural, intellectual, and historical awareness of the Marshallese people. A CHW contracted by MEI and living in the RMI will help teach F-DSMES classes and will be an important factor in community and participant engagement. KIJLE is a nonprofit women's group that collaborates with the MHHS to engage the community in public health initiatives. KIJLE's members will function as CHWs for the study, reminding participants about classes and doctors' appointments, as well as coordinating participants' transportation to data collection events. CHWs participate in 20 h of research training and 40 h of F-DSMES training over 10 weeks. KIJLE is important to maintaining cultural congruence during implementation as they represent the matriarchal leadership of the RMI. The research team will establish two local offices in the RMI: one in the MHHS and a second with KIJLE.

2.4. Sample size

The pilot study will be conducted with 72 primary participants (defined as patients with T2DM) and up to 144 family members (1–2 family members per primary participant). Approximately 12 primary participants will be enrolled at each of the six FBO settings.

2.5. Study setting

Group educational classes for primary participants and family members will be held at the six FBO settings in the RMI. In this study, all of the faith-based organizations will be churches. Churches play an important role in Marshallese culture and prior needs assessments have shown that 96.5% of Marshallese report regular church attendance [46].

2.6. Theoretical framework

The study's overall conceptual framework is based on Social Cognitive Theory (SCT), which recognizes the dynamic and reciprocal interaction between individuals, their environment, and their behaviors [47,48]. SCT recognizes that human health is often a social matter, not just an individual endeavor [48]. This is particularly important for the successful implementation of a DSMES intervention in the RMI. Poor self-management, while frequently attributed to the patient, is often the product of her/his social and environmental context [24,25,[49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60]]. Marshallese collectivist culture situates family at the center of decision-making [61]. Through their communications, habits, and attitudes, family members can greatly influence primary participants' decisions to follow recommended treatment and self-care regimens [13,25,[53], [54], [55],57,58,[60], [61], [62], [63], [64]]. In the F-DSMES intervention, primary participants and family members learn, increase motivation, develop strategies, and set goals together. The F-DSMES is designed to increase social support (family support) as a mechanism for changing behavior and ultimately improving health outcomes [47,48]. F-DSMES works to increase the support primary participants' receive from their family and to increase self-efficacy for managing T2DM. The F-DSMES teaches participants and family members to recognize supportive and non-supportive health behaviors that affect self-management, as well as factors in the families' physical environment that serve as facilitators and barriers to change.

2.7. Intervention

Primary participants and family members will participate in 10 h of diabetes education over an 8 week period, followed by a 2 week window for makeup classes. Group educational classes for primary participants and family members will be held at the participating church. The F-DSMES culturally adapted and translated curriculum includes eight core elements that are consistent with the American Association of Diabetes Educators’ (AADE) seven self-care behaviors: 1) healthy eating; 2) being active; 3) understanding blood glucose and following doctor prescribed medications; 4) problem-solving; 5) reducing risks and healthy coping; 6) mitigating complications of diabetes; and 7) goal setting [65]. F-DSMES is based on a collectivist approach and uses familiar contexts and analogies such as the role of spirituality, nature analogies, the value of traditional Pacific medicine, and “talk story.” [66] F-DSMES includes family members as secondary participants and focuses on family motivational interviewing, setting goals as a family, and family behavioral change [29,66]. The curriculum is designed to provide participants with education on supportive and non-supportive family behaviors [29,66]. The curriculum is asset-based and works to overcome barriers facing Marshallese participants by leveraging culturally specific facilitators of healthy behavioral change. The intervention is specifically designed for low literacy and low health literacy. All materials are provided in both English and Marshallese.

2.8. Study team

The study team includes a principal investigator and co-investigators who have prior experience conducting randomized controlled trials and other research studies with Marshallese participants in the US. The project manager for the study has 15 years of community health and research experience, and is a native of the RMI. The project manager relocated to the RMI and will manage all local CHWs and research staff. The local CHWs and research staff have completed CITI, HIPAA, blood borne pathogen, biometric data collection, and study-specific trainings. The CHWs will also complete Arkansas Faith-Academic Initiatives for Transforming Health Network training, which focuses on delivering health programs and education to faith communities.

2.9. Participant recruitment

Recruitment will be conducted by bilingual staff (Marshallese and English) who have extensive CBPR research training and experience. Staff will contact church leadership to determine interest and work with leadership to coordinate informational sessions with church attendees. An informational session will be held at the church to discuss the study and begin recruiting participants. All recruitment information will be provided in both English and Marshallese and will use plain language summaries of the study. Both male and female adults will be eligible to participate and will be targeted for equal representation. Recruitment began in March 2019 and will continue until recruitment goals are met.

2.10. Eligibility determination

Study staff and the data safety monitoring team will review the eligibility-screening instrument to determine enrollment in the study. The data safety monitoring team includes a Marshallese family practice doctor and a health researcher. To determine eligibility, the instrument will ask potential participants to verify: they are Marshallese; have been diagnosed with T2DM by a health care professional; have a family member willing to participate in the study with them; have participated in a DSMES program in the past five years, or have any medical conditions that would exclude them from participation. The data safety monitoring team will review the eligibility screening instrument to determine if persons have clinically significant medical conditions that will exclude them from participating in the study.

2.11. Participant inclusion criteria

Marshallese adults (aged 18 or older) with T2DM (defined as having an HbA1c ≥ 6.5) and at least one family member willing to take part in and attend all of the educational sessions and data collection events will be eligible for the study.

2.12. Participant exclusion criteria

Persons who are not Marshallese, have received DSMES in the past five years, have plans to move out of the geographic region, or have a condition that makes it unlikely that they will be able to follow the protocol will not be eligible to participate in the study.

2.13. Family member inclusion criteria

For the purposes of this study, a family member is defined as a relative living in the same household as the primary participant. Family members must be 18 years of age or older to consent and participate.

2.14. Informed consent

Consent materials will be in English or Marshallese and will use plain language study summaries. Bilingual staff will explain the study to participants and provide sufficient time for questions and answers. After participants have read the consent forms fully and had time to ask questions, they will be given the opportunity to provide consent. Written consent with the participant's signature will serve as documentation. Family members who are willing to participate will also complete the same consent process.

2.15. Data collection

Data will be collected pre-intervention, immediately post-intervention, four months post-intervention, and 12 months post-intervention. In the event missing data is identified, participants will be contacted to collect the missing data. All data collection staff will have prior experience collecting biometric and survey data. REDCap will be utilized to manage study data [67]. To prevent/minimize missing data, REDCap includes a missing data report in the Quality Assurance tool [67]. This will allow for convenient quality assurance validation and monitoring, as well as prompt collection of missing data. Instruments will be chosen collaboratively with Marshallese stakeholders, and they will be translated into Marshallese. Data collection events will take place in the FBO or a location of the participants’ choice, and will take about 1 h per data collection event.

2.16. Biometric data

The primary study outcome will be glycemic control as measured by change in HbA1c. Secondary biometric measures include: glucose, weight, height, BMI, blood pressure, and fasting lipids (total cholesterol, LDL, HDL, and triglycerides). Participants’ weight (without shoes) will be measured to the nearest 0.5 pound using a calibrated digital scale. Height (without shoes) will be measured to the nearest 0.25 inch using a stadiometer. Weight and height will be used to compute a continuous measure of BMI (weight in pounds/[height in inches] [2]). Systolic and diastolic blood pressure will be measured using a digital blood pressure device with the participant seated and arm elevated. Point of care tests will be used to collect HbA1c, fasting glucose, and fasting lipids. Staff will be using a Siemens DCA Vantage Analyzer to collect HbA1c, Cholestech LDX to collect fasting glucose, and a commercial lipid panel kit and Cholestech LDX to collect fasting lipids via a finger prick blood collection [68].

2.17. Survey data

The survey instrument for the study was developed with input from Marshallese stakeholders and utilizes adapted modules from the Diabetes Care Profile (DCP) [69] and the Behavioral Risk Factor Surveillance System (BRFFS) [70]. The survey instruments will be translated into Marshallese. Surveys will be administered at the pre-intervention data collection events and all post-intervention data collection events. All surveys will be collected on paper and then entered into a REDCap database with double data entry. The survey can be either interviewer-administered or self-administered, depending on the preference and/or literacy of the participant.

2.18. Feasibility data

Feasibility will be determined by evaluating: 1) fidelity of intervention delivery by CHWs; 2) recruitment and retention rates; and 3) attendance/dosage rates. The study manager will also observe intervention sessions to ensure fidelity and adherence to the curriculum. Intervention delivery will be monitored for fidelity using the F-DSMES fidelity checklist (developed with our prior study). Participant enrollment will be tracked and reported weekly. Participant retention will be tracked and reported at each data collection event. Attendance of primary participants and family members for each intervention session will be recorded and reported weekly by CHWs.

2.19. Qualitative data

Up to 20 participants will be asked to take part in qualitative interviews that will be used to gain patient feedback regarding their experiences and the cultural acceptability of the intervention. A semi-structured interview guide will be used to allow participants to speak in-depth about their experiences and ensure that all interviews cover the same topics. Interviews will take approximately 30 min to complete.

2.20. Remuneration

Remuneration will be provided to both primary participants and family members for their participation. Participants will be given $20 cash as compensation for their time for each data collection event they complete. Each participant will be eligible to collect four $20 incentives, for a total of $80 for those who participate in all four data collection events. Those who participate in the qualitative interviews will receive an additional $20.

2.21. Data analysis

2.21.1. Quantitative data analysis

Analyses will be performed with SAS/STATv14.1 [71]. The proposed research will be pilot study with the primary goal of testing feasibility and acceptability. Therefore, the study will not be powered to test specific hypotheses. In addressing the question of preliminary effectiveness, pilot study data will be used to estimate parameters and effect sizes needed to plan a larger study. Using pilot data, we will estimate the mean difference in measures at pre-intervention and post-intervention (immediate post-intervention, four months post-intervention, and 12 months post-intervention), the standard deviations, and the standard effect size. We will focus on point estimates and confidence intervals rather than p-values. Judgement of the preliminary effectiveness of the intervention will be based on the estimated mean differences in outcomes and the range of plausible values for that parameter from confidence intervals. For people with T2DM, a reduction of ~1% can have significant improvements clinical outcomes. For each 1% reduction in HbA1c patients see a 14% decrease in risk for heart attack, a 12% decrease in risk for stroke, a 37% decrease in risk for microvascular complications, and a 21% decrease in risk for death related to diabetes [72]. We will be looking to see if the effect is in the right direction (consistent with the intervention being effective) and whether the estimate would be clinically meaningful.

2.21.2. Feasibility analysis

The feasibility of the study will be determined through analysis of the fidelity of the intervention delivered by the CHWs, recruitment and retention rates, and attendance/dosage rates. For the study to be considered feasible, the intervention will be delivered with fidelity of at least 90% using the F-DSMES fidelity checklist. Recruitment rates of at least 75%, a retention rate of 75% for all four data collection events, and at least 75% of participants receiving a minimum of 50% of the intervention will further demonstrate feasibility.

2.21.3. Qualitative analysis

Qualitative interviews will be used to evaluate participants’ experiences and perceptions of the intervention and its acceptability. All interviews will be audio recorded, transcribed verbatim, and translated from Marshallese to English. Data will be imported into MAXQDA qualitative software [73] and analyzed using content analysis and thematic coding related to the acceptability of the intervention. A sample set of transcripts will first be coded independently by two researchers with extensive qualitative research experience. A codebook will be developed that includes both a priori and emergent themes and will be refined at least two times through discussions with the study team during data analysis. A third confirmation coder will review all coded transcripts and any discrepancies will be discussed and decided by consensus of the study team.

2.21.4. Dissemination plan

Through an existing CBPR collaborative, study staff will also provide a summary of the results back to the Marshallese community, ensuring that participant confidentiality is maintained. Through previous research, the study team has found that individual in-person meetings, church meetings, town hall meetings, using infographics, and plain language summaries are the culturally preferred methods for dissemination of study results [74]. Individual participant results will be shared with participants after each data collection event. Following data collection events, aggregated de-identified results will be shared with the entire congregation at participating churches and at community-wide town halls. Town hall meetings will be announced through Facebook, newspaper, and radio. CBPR partners will co-host town hall dissemination events. Culturally and linguistically appropriate infographics and plain language summaries will be created and used as flyers and posters to be distributed at community events and in-person meetings and posted on Facebook. A summary of the results will be provided in a formal report and presentation to the RMI MHHS. Additionally, results of this study will be used for academic presentations, posters, or publications.

3. Summary

This study will be based on a CBPR approach, which engages Marshallese community members and allows UAMS researchers to build trust among Marshallese in the RMI and overcome barriers created by the historical trauma of nuclear testing. This study will build upon a growing body of literature on family models of DSMES. The Marshallese collectivist culture puts family at the center of communication, decision-making, and behaviors [24,25,75]. Family members greatly influence primary participants’ decisions to engage in self-care. This study will provide new and innovative information about the effects of F-DSMES in a low-resource country with a collectivist, family-centered culture. The results will be important for future research in other parts of the USAPI, other collectivist cultures, and other low- and middle-income countries.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to thank our community partners; the Republic of Marshall Islands Ministry of Health and Human Services (MOHHS), the Marshallese Education Initiative (MEI), and Kora In Jiban Lolorjake Ejmour (KIJLE) for their contributions in designing this study protocol.

The community engagement efforts and research are supported by UAMS Translational Research Institute funding provided by the National Center for Research Resources and National Center for Advancing Translational Sciences of the National Institutes of Health (NIH) (1U54TR001629-01A1). The study is also funded in part by an award from the Sturgis Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or Sturgis Foundation.

Contributor Information

Pearl A. McElfish, Email: pamcelfish@uams.edu.

Janine Boyers, Email: jmboyers@uams.edu.

Rachel S. Purvis, Email: rspurvis@uams.edu.

Betsy O'Connor, Email: geoconnor@uams.edu.

Ayoola Carleton, Email: acarelton@uams.edu.

Williamina Bing, Email: wibing@uams.edu.

Brett Rowland, Email: mbrowland@uams.edu.

Craig Molgaard, Email: camolgaard@uams.edu.

Ainrik George, Email: aingeo@outlook.com.

Lydia R. Tibon, Email: lrtibon@gmail.com.

Dalton Hoose, Email: dhoose@uams.edu.

Sheldon Riklon, Email: sriklon@uams.edu.

References

  • 1.Central Intelligence Agency World factbook: Marshall Islands. https://www.cia.gov/library/publications/the-world-factbook/geos/rm.html
  • 2.108th United States Congress . U.S. Government Printing Office; 2003. Compact of Free Association Amendments Act of 2003.http://www.gpo.gov/fdsys/pkg/PLAW-108publ188/html/PLAW-108publ188.htm [Google Scholar]
  • 3.Palafox N., Buenconsejo-Lum L., Riklon S., Waitzfelder B. Improving health outcomes in diverse populations: competency in cross-cultural research with indigenous Pacific islander populations. Ethn. Health. 2002;7(4):279–285. doi: 10.1080/1355785022000060736. [DOI] [PubMed] [Google Scholar]
  • 4.Compact of Free Association Community Advocacy Network Citizens of oceania: COFACAN statement and call to action. http://www.healthypacific.org/1/post/2014/04/citizens-of-oceania-cofacan-statement-and-call-to-action.html?fb_action_ids=10100243451727714&fb_action_types=weeblyapp%3Ashare
  • 5.Ichiho H.M., deBrum I., Kedi S., Langidrik J., Aitaoto N. An assessment of non-communicable diseases, diabetes, and related risk factors in the republic of the Marshall Islands, majuro atoll: a systems perspective. Hawai‘i J. Med. Public Health. 2013;vol. 5(1):87–97. [PMC free article] [PubMed] [Google Scholar]
  • 6.Minegishi M., Fujimori K., Nakajima N. Diabetes mellitus and obesity among participants receiving screening for cancer in the republic of the Marshall Islands. Diabetes mellitus and obesity among participants receiving screening for cancer in the republic of the Marshall Islands. Diabetes rates Marshallese. Journal of International Health. 2007;22(3):133–141. [Google Scholar]
  • 7.World Health Organization Diabetes fact sheet. http://www.who.int/news-room/fact-sheets/detail/diabetes
  • 8.Hawley N., McGarvey S. Obesity and diabetes in Pacific Islanders: the current burden and the need for urgent action. Curr. Diabetes Rep. 2015;15(5):29. doi: 10.1007/s11892-015-0594-5. [DOI] [PubMed] [Google Scholar]
  • 9.Federation I.D. IDF diabetes atlas. 2019. https://www.diabetesatlas.org
  • 10.Barker H. Cengage Learning; 2012. Bravo for the Marshallese: Regaining Control in a Post-Nuclear. Post-Colonial World. [Google Scholar]
  • 11.Guyer R. Radioactivity and rights: clashes at bikini atoll. Nuclear effects. Am. J. Publ. Health. 2001;91(9):1371–1376. doi: 10.2105/AJPH.91.9.1371. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Pollock N. Health transitions, fast and nasty: exposure to nuclear radiation. Nutrtion. Pacific Health Dialog. 2002;9(2):275–282. [PubMed] [Google Scholar]
  • 13.Gittelsohn J., Haberle H., Vastine A., Dyckman W., Palafox N. Macro- and microlevel processes affect food choice and nutritional status in the Republic of the Marshall Islands. J. Nutr. 2003;133(1):310S–313S. doi: 10.1093/jn/133.1.310S. [DOI] [PubMed] [Google Scholar]
  • 14.Ahlgren I., Yamada S., Wong A. Rising oceans, climate change, food aid, and human rights in the Marshall Islands. Health and Human Rights. 2014;16(1) [PubMed] [Google Scholar]
  • 15.Yuan C., Lai C.W., Chan L.W., Chow M., Law H.K., Ying M. The effect of diabetes self-management education on body weight, glycemic control, and other metabolic markers in patients with type 2 diabetes mellitus. J. Diabetes Res. 2014 doi: 10.1155/2014/789761. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Brunisholz K.D., Briot P., Hamilton S. Diabetes self-management education improves quality of care and clinical outcomes determined by a diabetes bundle measure. J. Multidiscip. Healthc. 2014;7:533–542. doi: 10.2147/jmdh.s69000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Atak N., Gurkan T., Kose K. The effect of education on knowledge, self-management behaviours and self efficacy of patients with type 2 diabetes. Aust. J. Adv. Nurs. 2008;26:66–74. [Google Scholar]
  • 18.Wattana C., Srisuphan W., Pothiban L., Upchurch S. Effects of a diabetes self-management program on glycemic control, coronary heart disease risk, and quality of life among Thai patients with type 2 diabetes. Nurs. Health Sci. 2007;9:135–141. doi: 10.1111/j.1442-2018.2007.00315.x. [DOI] [PubMed] [Google Scholar]
  • 19.Lavelle D., Zeitoun J., Stern M., Butkiewicz E., Wegner E., Reinisch C. Diabetes self-management education in the home. Cureus. 2016;8(7) doi: 10.7759/cureus.710. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Creamer J., Attridge M., Ramsden M., Cannings-John R., Hawthorne K. Culturally appropriate health education for Type 2 diabetes in ethnic minority groups: an updated Cochrane Review of randomized controlled trials. Diabet. Med. 2016;33(2):169–183. doi: 10.1111/dme.12865. [DOI] [PubMed] [Google Scholar]
  • 21.Hawthorne K., Robles Y., Cannings-John R., Edwards A.G.K. Culturally appropriate health education for Type 2 diabetes in ethnic minority groups: a systematic and narrative review of randomized controlled trials. Diabet. Med.: J. Br. Diab. Assoc. 2010;27(6):613–623. doi: 10.1111/j.1464-5491.2010.02954.x. [DOI] [PubMed] [Google Scholar]
  • 22.Ricci-Cabello I., Ruiz-Perez I., Rojas-Garcia A., Pastor G., Rodriguez-Barranco M., Goncalves D.C. Characteristics and effectiveness of diabetes self-management educational programs targeted to racial/ethnic minority groups: a systematic review, meta-analysis and meta-regression. BMC Endocr. Disord. 2014;14:60. doi: 10.1186/1472-6823-14-60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Anderson R., Funnell M., Nwankwo R., Gillard M., Oh M., Fitzgerald J. Evaluating a problem-based empowerment program for African Americans with diabetes: results of a randomized controlled trial. Ethn. Dis. 2005;15(4):671–678. [PubMed] [Google Scholar]
  • 24.Baig A., Benitez A., Quinn M., Burnet D. Family interventions to improve diabetes outcomes for adults. Ann. N Y Acad. Sci. Sep. 2015;1353:89–112. doi: 10.1111/nyas.12844. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Pamungkas R.A., Chamroonsawasdi K., Vatanasomboon P. A systematic review: family support integrated with diabetes self-management among uncontrolled type II diabetes mellitus patients. Behav. Sci. 2017;7(3) doi: 10.3390/bs7030062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.McElfish P.A., Purvis R.S., Esquivel M.K. Diabetes disparities and promising interventions to address diabetes in native Hawaiian and pacific islander populations. Curr. Diabetes Rep. 2019;19(5):19. doi: 10.1007/s11892-019-1138-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Hawley N.L., Suss R., Cash H.L. Diabetes prevention and care programs in the US-affiliated pacific Islands: challenges, innovation, and recommendations for effective scale-up. Curr. Diabetes Rep. 2019;19(5):24. doi: 10.1007/s11892-019-1139-0. [DOI] [PubMed] [Google Scholar]
  • 28.Reddy R., Trinidad R., Seremai J., Nasa J. Marshallese diabetic health improvement pilot project in Ebeye. Previous Marshallese Diabetes Interventions. Califor. J. Health Promot. 2009;7:125–130. [Google Scholar]
  • 29.Yeary K.H.K., Long C.R., Bursac Z., McElfish P.A. Design of a randomized controlled comparative effectiveness trial testing a Family Model of Diabetes Self-Management Education (DSME) vs. standard DSME for Marshallese in the United States. Contemp Clin. Trials Commun. 2017;6:97–104. doi: 10.1016/j.conctc.2017.03.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.McElfish P.A., Ayers B.L., Felix H.C. How stakeholder engagement influenced a randomized comparative effectiveness trial testing two Diabetes Prevention Program interventions in a Marshallese Pacific Islander Community. J. Transl. Med. 2019;17(1):42. doi: 10.1186/s12967-019-1793-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.McElfish P.A., Long C.R., Kohler P.O. Comparative effectiveness and maintenance of diabetes self-management education interventions for Marshallese patients with type 2 diabetes: a randomized controlled trial. Diabetes Care. 2019;42(5):849–858. doi: 10.2337/dc18-1985. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.McElfish P.A., Long C.R., Bursac Z. Diabetes self-management education exposure and glycated haemoglobin levels among Marshallese participants in a randomized controlled study. Diabet. Med. 2019 doi: 10.1111/dme.14189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Schensul J.J. Community, culture and sustainability in multilevel dynamic systems intervention science. Am. J. Community Psychol. 2009;43(3–4):241–256. doi: 10.1007/s10464-009-9228-x. [DOI] [PubMed] [Google Scholar]
  • 34.Schensul J.J., Trickett E. Introduction to multi-level community based culturally situated interventions. Am. J. Community Psychol. 2009;43(3–4):232–240. doi: 10.1007/s10464-009-9238-8. [DOI] [PubMed] [Google Scholar]
  • 35.Gorin S.S., Badr H., Krebs P., Prabhu Das I. Multilevel interventions and racial/ethnic health disparities. J. Natl. Cancer Inst. Monogr. 2012;2012(44):100–111. doi: 10.1093/jncimonographs/lgs015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Minkler M., Wallerstein N., editors. Community-Based Participartory Research for Health: from Process to Outcomes. Jossey-Bass Publishers; 2008. [Google Scholar]
  • 37.Cornwall A., Gaventa J. Bridging the gap: citizenship, participation and accountability. PLA Notes. 2001;40:32–35. [Google Scholar]
  • 38.Gaventa J., Cornwall A. Challenging the boundaries of the possible: participation, knowledge and power. IDS Bull. 2006;37(6):122–128. doi: 10.1111/j.1759-5436.2006.tb00329.x. [DOI] [Google Scholar]
  • 39.Minkler M., Blackwell A.G., Thompson M., Tamir H. Community-based participatory research: implications for public health funding. Am. J. Publ. Health. 2003;93(8):1210–1213. doi: 10.2105/ajph.93.8.1210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Israel B., Schulz A., Parker E., Becker A. Review of community-based research: assessing partnership approaches to improve public health. Am. J. Publ. Health. 1998;19(1):173–202. doi: 10.1146/annurev.publhealth.19.1.173. [DOI] [PubMed] [Google Scholar]
  • 41.Mendenhall T., Berge J., Harper P. The family diabetes education series (FEDS): community-based participatory research with a midwestern American Indian community. Family diabetes education. Nurs. Inq. 2010;17(4):359–372. doi: 10.1111/j.1440-1800.2010.00508.x. [DOI] [PubMed] [Google Scholar]
  • 42.O'Toole T.P., Aaron K.F., Chin M.H., Horowitz C., Tyson F. Community-based participatory research. J. Gen. Intern. Med. 2003;18(7):592–594. doi: 10.1046/j.1525-1497.2003.30416.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Viswanathan M., Ammerman A., Eng E. Community-based participatory research: assessing the evidence. Evid. Rep. Technol. Assess. 2004;(99):1–8. [PMC free article] [PubMed] [Google Scholar]
  • 44.Trickett E.J. Multilevel community-based culturally situated interventions and community impact: an ecological perspective. Am. J. Community Psychol. 2009;43(3–4):257–266. doi: 10.1007/s10464-009-9227-y. [DOI] [PubMed] [Google Scholar]
  • 45.Health RotMIMo . October 2017- September 2019. 3 Year Rolling Strategic Plan; p. 56. [Google Scholar]
  • 46.McElfish P.A., Moore R., Laelan M., Ayers B.L. Using CBPR to address health disparities with the Marshallese community in Arkansas. Ann. Hum. Biol. 2018;45(3):264–271. doi: 10.1080/03014460.2018.1461927. [DOI] [PubMed] [Google Scholar]
  • 47.McAlister A.L., Perry C.L., Parcel G.S. How individuals, environments, and health behaviors interact: social cognitive theory. In: Glanz K., Rimer B.K., Viswanath K., editors. Health Behavior and Health Education: Theory, Research, and Practice. fourth ed. ed. Jossey-Bass; 2008. [Google Scholar]
  • 48.Bandura A. Prentice Hall; 1986. Social Foundations of Thought and Action: A Social Cognitive Theory. [Google Scholar]
  • 49.Peyrot M., Burns K.K., Davies M. Diabetes Attitudes Wishes and Needs 2 (DAWN2): a multinational, multi-stakeholder study of psychosocial issues in diabetes and person-centred diabetes care. Diabetes Res. Clin. Pract. 2013;99(2):174–184. doi: 10.1016/j.diabres.2012.11.016. [DOI] [PubMed] [Google Scholar]
  • 50.Kovacs Burns K., Nicolucci A., Holt R.I. Diabetes attitudes, wishes and needs second study (DAWN2): cross-national benchmarking indicators for family members living with people with diabetes. Diabet. Med. 2013;30(7):778–788. doi: 10.1111/dme.12239. [DOI] [PubMed] [Google Scholar]
  • 51.Nicolucci A., Kovacs Burns K., Holt R.I. Diabetes Attitudes, Wishes and Needs second study (DAWN2™): cross-national benchmarking of diabetes-related psychosocial outcomes for people with diabetes. Diabet. Med. 2013;30(7):767–777. doi: 10.1111/dme.12245. [DOI] [PubMed] [Google Scholar]
  • 52.Holt R.I., Nicolucci A., Kovacs Burns K. Diabetes Attitudes, Wishes and Needs second study (DAWN2™): cross-national comparisons on barriers and resources for optimal care--healthcare professional perspective. Diabet. Med. 2013;30(7):789–798. doi: 10.1111/dme.12242. [DOI] [PubMed] [Google Scholar]
  • 53.Rintala T.M., Jaatinen P., Paavilainen E., Astedt-Kurki P. Interrelation between adult persons with diabetes and their family: a systematic review of the literature. J. Fam. Nurs. 2013;19(1):3–28. doi: 10.1177/1074840712471899. [DOI] [PubMed] [Google Scholar]
  • 54.Mayberry L.S., Rothman R.L., Osborn C.Y. Family members' obstructive behaviors appear to be more harmful among adults with type 2 diabetes and limited health literacy. J. Health Commun. 2014;19(2):132–143. doi: 10.1080/10810730.2014.938840. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Bennich B., Roder M., Overgaard D. Supportive and non-supportive interactions in families with a type 2 diabetes patient: an integrative review. Diebetol. Metabol. Syndr. 2017;9:57–65. doi: 10.1186/s13098-017-0256-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Mayberry L.S., Osborn C.Y. Family support, medication adherence, and glycemic control among adults with type 2 diabetes. Diabetes Care. 2012;35(6):1239–1245. doi: 10.2337/dc11-2103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Fisher L., Chesla C., Bartz R. The family and type 2 diabetes: a framework for intervention. Diabetes Educat. 1998;24(5):599–607. doi: 10.1177/014572179802400504. [DOI] [PubMed] [Google Scholar]
  • 58.Denham S.A., Ware L.J., Raffle H., Leach K. Family inclusion in diabetes education: a nationwide survey of diabetes educators. Diabetes Educat. Jul-Aug 2011;37(4):528–535. doi: 10.1177/0145721711411312. [DOI] [PubMed] [Google Scholar]
  • 59.Felix H., Rowland B., Long C.R. Diabetes self-care behaviors among Marshallese adults living in the United States. J. Immigr. Minority Health. Dec 2017 doi: 10.1007/s10903-017-0683-4. [DOI] [PubMed] [Google Scholar]
  • 60.Felix H., Xiaocong L., Rowland B., Long C., Yeary K., McElfish P. Physical activity and diabetes-related health beliefs of Marshallese adults. Am. J. Health Behav. 2017;41(5):553–560. doi: 10.5993/AJHB.41.5.4. [DOI] [PubMed] [Google Scholar]
  • 61.Cortes L., Gittelsohn J., Alfred J., Palafox N. Formative research to inform intervention development for diabetes prevention in the Republic of the Marshall Islands. Health Educ. Behav. 2001;28(6):696–715. doi: 10.1177/109019810102800604. [DOI] [PubMed] [Google Scholar]
  • 62.Baig A.A., Benitez A., Quinn M.T., Burnet D.L. Family interventions to improve diabetes outcomes for adults. Ann. N. Y. Acad. Sci. Sep 2015;1353:89–112. doi: 10.1111/nyas.12844. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Mayberry L.S., Osborn C.Y. Family support, medication adherence, and glycemic control among adults with type 2 diabetes. Diabetes Care. 2012;35(6):1239–1245. doi: 10.2337/dc11-2103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Felix H., Rowland B., Long C.R. Diabetes self-care behaviors among Marshallese adults living in the United States. J. Immigr. Minority Health. Dec 2018;20(6):1500–1507. doi: 10.1007/s10903-017-0683-4. [DOI] [PubMed] [Google Scholar]
  • 65.AADE. 2014. AADE Self-Care Behaviors. [Google Scholar]
  • 66.Yeary K.H., Aitaoto N., Sparks K. Cultural adaptation of diabetes self-management education for Marshallese residing in the United States: lessons learned in curriculum development. Prog. Commun. Health Partner. 2017;11(3):253–261. doi: 10.1353/cpr.2017.0030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Harris P., Taylor R., Thielke R., Payne J., Gonzalez N., Conde J. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inf. 2009;42(2):377–381. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Lenters-Westra E., Slingerland R.J. Six of eight hemoglobin A1c point-of-care instruments do not meet the general accepted analytical performance criteria. Clin. Chem. 2010;56(1):44–52. doi: 10.1373/clinchem.2009.130641. [DOI] [PubMed] [Google Scholar]
  • 69.Fitzgerald J.T., Davis W.K., Connell C.M., Hess G.E., Funnell M.M., Hiss R.G. Development and validation of the diabetes care profile. Eval. Health Prof. 1996;19(2):208–230. doi: 10.1177/016327879601900205. [DOI] [PubMed] [Google Scholar]
  • 70.Centers for Disease Control and Prevention Behavioral risk factor surveillance System (BRFSS) 2019. http://www.cdc.gov/brfss/
  • 71.SAS/STAT. Version 14.1. 2015. http://www.sas.com/en_us/home.html [Google Scholar]
  • 72.Stratton I.M., Adler A.I., Neil H.A.W. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321(7258):405–412. doi: 10.1136/bmj.321.7258.405. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.MAXQDA, Software for Qualitative Data Analysis. VERBI Software; 1989-2015. http://www.maxqda.com/ [Google Scholar]
  • 74.Purvis R., Long C., James L. Dissemination protocol for community-based participatory research partnerships with Marshallese Pacific Islanders in Arkansas. Prog Community Health Partnersh. Forthcoming 2021 doi: 10.1353/cpr.2021.0039. Accepted December 15, 2020. [DOI] [PubMed] [Google Scholar]
  • 75.McElfish P.A., Post J., Rowland B., Long C.R. Family models of diabetes self-management education: the current evidence and critical gaps in knowledge. EMJ Diab. 2019;7(1):59–61. [Google Scholar]

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