Dataset Information

Socio-ecological Model as a Framework for Overcoming Barriers and Challenges in Randomized Control Trials in Minority and Underserved Communities.

ABSTRACT:

Background

Numerous barriers and challenges can hinder the successful enrollment and retention of study participants in clinical trials targeting minority populations. To conduct quality research, it is important to investigate these challenges, determine appropriate strategies that are evidence-based and continue seeking methods of improvement.

Methods

In this paper, we report such experiences in a registered clinical trial in an underserved minority population in the Southern part of United States. This research study is a randomized double-blind controlled clinical trial that tests the efficacy of higher-strength as compared to low-strength/standard of care folic acid to prevent fetal body and brain size reduction in pregnant women who smoke. A unique approach in this socio-behavioral, genetic-epigenetic clinical trial is that we have adopted the socio-ecological model as a functional platform to effectively achieve and maintain high participant recruitment and retention rates.

Results

We highlight the barriers we have encountered in our trial and describe how we have successfully applied the socio-ecological model to overcome these obstacles.

Conclusions and global health implications

Our positive experience will be of utility to other researchers globally. Our fi ndings have far-reaching implications as the socio-ecological model approach is adaptable to developed and developing regions and has the potential to increase recruitment and retention of hard-to-reach populations who are typically under-represented in clinical trials.

SUBMITTER: Salihu HM

PROVIDER: S-EPMC4948176 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Socio-ecological Model as a Framework for Overcoming Barriers and Challenges in Randomized Control Trials in Minority and Underserved Communities.

Salihu Hamisu M HM Wilson Ronee E RE King Lindsey M LM Marty Phillip J PJ Whiteman Valerie E VE

International journal of MCH and AIDS 20150101 1

<h4>Background</h4>Numerous barriers and challenges can hinder the successful enrollment and retention of study participants in clinical trials targeting minority populations. To conduct quality research, it is important to investigate these challenges, determine appropriate strategies that are evidence-based and continue seeking methods of improvement.<h4>Methods</h4>In this paper, we report such experiences in a registered clinical trial in an underserved minority population in the Southern pa ...[more]

PMID: 27621990

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Project description:Policy Points Engaging and involving underrepresented communities when setting research priorities could make the scientific research agenda more equitable, more just, and more responsive to their needs and values. Groups and individuals from minority and underserved communities strongly prioritized child health and mental health research, often choosing to invest at the highest possible level. Groups consisting of predominantly Native American or Arab American participants invested in culture and beliefs research at the highest level, while many groups did not select it at all. The priority given to culture and beliefs research by these groups illustrates the importance of paying special attention to unique preferences, and not just commonly held views, when getting public input on spending priorities for research.ContextA major contributor to health disparities is the relative lack of resources-including resources for science-allocated to address the health problems of those with disproportionately greater needs. Engaging and involving underrepresented communities in setting research priorities could make the scientific research agenda more equitable, more just, and more responsive to their needs and values. We engaged minority and underserved communities in informed deliberations and report here their priorities for health research.MethodsAcademic-community partnerships adapted the simulation exercise CHAT for setting health research priorities. We had participants from minority and medically underserved communities (47 groups, n = 519) throughout Michigan deliberate about health research priorities, and we used surveys and CHAT software to collect the demographic characteristics and priorities selected by individuals and groups.FindingsThe participants ranged in age (18 to 88), included more women than men, and were overrepresented by minority groups. Nearly all the deliberating groups selected child health and mental health research (93.6% and 95.7%), and most invested at the highest level. Aging, access, promote health, healthy environment, and what causes disease were also prioritized by groups. Research on mental health and child health were high priorities for individuals both before and after group deliberations. Access was the only category more likely to be selected by individuals after group deliberation (77.0 vs 84.0%, OR = 1.63, p = .005), while improve research, health policy, and culture and beliefs were less likely to be selected after group deliberations (all, p < .001). However, the level of investment in many categories changed after the group deliberations. Participants identifying as Black/African American were less likely to prioritize mental health research, and those of Other race were more likely to prioritize culture and beliefs research.ConclusionsMinority and medically underserved communities overwhelmingly prioritized mental health and child health research in informed deliberations about spending priorities.

Project description:Computational models of patients and medical devices can be combined to perform an in silico clinical trial (ISCT) to investigate questions related to device safety and/or effectiveness across the total product life cycle. ISCTs can potentially accelerate product development by more quickly informing device design and testing or they could be used to refine, reduce, or in some cases to completely replace human subjects in a clinical trial. There are numerous potential benefits of ISCTs. An important caveat, however, is that an ISCT is a virtual representation of the real world that has to be shown to be credible before being relied upon to make decisions that have the potential to cause patient harm. There are many challenges to establishing ISCT credibility. ISCTs can integrate many different submodels that potentially use different modeling types (e.g., physics-based, data-driven, rule-based) that necessitate different strategies and approaches for generating credibility evidence. ISCT submodels can include those for the medical device, the patient, the interaction of the device and patient, generating virtual patients, clinical decision making and simulating an intervention (e.g., device implantation), and translating acute physics-based simulation outputs to health-related clinical outcomes (e.g., device safety and/or effectiveness endpoints). Establishing the credibility of each ISCT submodel is challenging, but is nonetheless important because inaccurate output from a single submodel could potentially compromise the credibility of the entire ISCT. The objective of this study is to begin addressing some of these challenges and to identify general strategies for establishing ISCT credibility. Most notably, we propose a hierarchical approach for assessing the credibility of an ISCT that involves systematically gathering credibility evidence for each ISCT submodel in isolation before demonstrating credibility of the full ISCT. Also, following FDA Guidance for assessing computational model credibility, we provide suggestions for ways to clearly describe each of the ISCT submodels and the full ISCT, discuss considerations for performing an ISCT model risk assessment, identify common challenges to demonstrating ISCT credibility, and present strategies for addressing these challenges using our proposed hierarchical approach. Finally, in the Appendix we illustrate the many concepts described here using a hypothetical ISCT example.

Dataset Information

Socio-ecological Model as a Framework for Overcoming Barriers and Challenges in Randomized Control Trials in Minority and Underserved Communities.

Background

Methods

Results

Conclusions and global health implications

Publications

Socio-ecological Model as a Framework for Overcoming Barriers and Challenges in Randomized Control Trials in Minority and Underserved Communities.

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