ABSTRACT
The lack of diversity in clinical trials and drug development negatively impacts public health. Growing evidence suggests that successful recruitment, retention, and protocol compliance, such as medication adherence, must account for social drivers of health, particularly among underrepresented populations. Implementing novel approaches, such as the wellness and prescription produce program described in this perspective, may bring research to communities in ways that facilitate meaningful inclusion of underrepresented populations in clinical trials and promote health equity.
Keywords: food insecurity, food is medicine, health equity, medication adherence, older adults, prescription produce program, social drivers
1. Overview
The lack of diversity in clinical trials and drug development negatively impacts public health [1]. Minority groups are underrepresented in drug development and clinical trials, yet they experience disproportionate rates of chronic disease burden. For example, among 32,000 Americans who participated in new drug trials in 2020, only 8% were Black, 6% Asian, 11% Hispanic, while 30% were age 65 and older [2]. These statistics highlight the significant underrepresentation of minority groups in drug development and clinical trials. Furthermore, scholars have called attention to the public health impacts of poor protocol compliance, particularly medication adherence, that can lead to increased financial costs for sponsors, diminished research rigor and statistical power, and heightened health risks for participants [3, 4].
Growing evidence suggests that successful recruitment, retention, and protocol compliance, such as medication adherence, must account for social drivers of health, such as food insecurity, that influence participants' experiences during trials [4]. Social drivers of health (SDOH) are nonmedical factors that affect a wide range of health outcomes; SDOH include upstream influences embodied in where and how people live, work, play, and age. Low recruitment and retention of underrepresented groups in clinical trials are shaped by limited stakeholder engagement and mistrust rooted in unethical research and medical practices [4]. SDOH such as social and community context, healthcare access, housing security, transportation access, economic stability and food security have been previously reported to influence recruitment, retention, and medication adherence [4]. Among SDOH, food insecurity, defined as limited or uncertain access to adequate food, was linked to lower odds of medication adherence [5]. The trade‐off between food security and optimal disease management, known as “treat or eat,” disproportionately impacts underrepresented, historically marginalized minority communities (UHMM) [5].
Recommendations for inclusive trial design include investing in long‐term partnerships with community‐based organizations outside of academic medical centers and trial sites, providing individualized support for SDOH like transportation and access to care, and actively incorporating stakeholder input as part of trial design and implementation [1, 4]. Further community‐based approaches that holistically address medication adherence, food insecurity, and other SDOH are needed to promote effective recruitment and retention strategies for underrepresented populations in clinical trials.
2. Putting Communities at the Center: The Mobile Health and Wellness Program
Founded in 2012, the Mobile Health and Wellness (MHWP) has served mainly older adults and adults with disabilities by providing services within urban low‐income housing buildings and a community‐based clinic. MHWP promotes access for underrepresented groups by bringing services to the community, mitigating impacts of SDOH like lack of transportation, housing insecurity, and time or financial constraints. MHWP builds trust and responds to community needs by employing a community‐engaged research approach with tailored recruitment and retention strategies [6]. Further, MHWP invests in long‐standing relationships with partnering sites and community members. Weekly visits have been offered continuously for 14 years at the oldest site and a minimum of 5 years at the newest.
MHWP wellness visits are described elsewhere [6, 7]. Social needs are screened in team visits as previously reported to identify food insecurity, housing insecurity, and reduced access to medical appointments and prescriptions due to lack of transportation [7]. Teams address social needs through referral, coordination, and at times, direct provision of resources (e.g., blood pressure cuffs, rollator repair clinics). Each visit includes a medication review workflow developed as part of the Institute for Health Innovation 4Ms Age‐Friendly Health System designation, available in Figure S1. Participants are asked about medication adherence, changes in any medications since their last MHWP visit, side effects, adverse reactions, and to complete a medication reconciliation if indicated. Medication adherence is assessed using the 1‐item self‐report Modified Drug Adherence Work‐Up tool designed to screen for medication‐taking behavior [8]. Issues with nonadherence are addressed through the identification of individual needs, followed by brief interventions, typically care coordination and medication education. Teams also assist with medication adherence supports, such as providing and setting up pill boxes or arranging medication delivery.
Program data are collected during team visits and managed using REDCap data collection tools (Research Electronic Data Capture), which is a secure, web‐based software platform hosted at Virginia Commonwealth University [9].
3. Building Research Around Community‐Identified Areas of Need
In 2020, after assessing community‐specific barriers associated with a high prevalence of food insecurity, the MHWP clinical team developed a Prescription Produce Program (PPP) to address participants' needs for accessing and consuming healthy food. Briefly, MHWP‐PPP integrates a medication adherence intervention within a person‐centered lifestyle counseling approach to address three primary goals: (1) to screen and intervene for food insecurity and other SDOH; (2) to increase food security and access by providing six bags of fresh produce either weekly or twice monthly; and (3) to support chronic disease management by providing nutrition education, medication adherence support and goal setting techniques [7]. Participants were recruited at MHWP sites during team visits and by word of mouth. The MHWP‐PPP inclusion criteria were: (a) an MHWP participant 18 years old or older; (b) reporting a nutrition‐related chronic disease; and (c) willing to attend at least three team visits. See Figure 1 for a representation of this novel approach.
FIGURE 1.

This figure depicts a novel approach to inclusive clinical trial design that places the community at the top by bringing research to communities in the places people live. Interventions addressing social drivers of health such as stakeholders' involvement, food security, and transportation access must be implemented before or concurrently with clinical trials to promote recruitment and retention of underrepresented groups. Outside of traditional clinical trial sites and academic medical centers, this approach engages community stakeholders to inform the design and implementation of research that responds to community‐identified needs.
4. Descriptive Findings to Illustrate Recruitment, Retention, and Adherence
Quality improvement findings from a retrospective review of the 2022 and 2023 PPP seasons suggest program acceptability (determined not human subjects research by the VCU Institutional Review Board HM20025302 and HM20031302). In 2022, 60 participants enrolled and 53 completed the program, which represents an 88% retention rate. In 2023, 79 participants enrolled and 61 completed the program (77% retention rate). A total of 88 unique participants engaged over the 2‐year period. Nearly one‐third of participants completed the program in both years (i.e., 2022 and 2023, n = 27) and the remainder completed a single year of the MHWP‐PPP (i.e., 2022 or 2023, n = 61).
Participants reported social drivers and demographic characteristics at program start. Of the 88 unique participants, most were female (65%), Black (84%), older adults (M = 66.5, range 28–89 years old) with a high school degree or less (48.9%) as shown in Table 1. While income was not assessed, participants in four of five sites live in housing with low‐income requirements. Participants are largely covered by Medicare and/or Medicaid (80%). Most participants reported polypharmacy, managing an average of 10 medications and/or supplements (SD = 5.9). Participants reported multimorbidity, with the most prevalent conditions being hypertension (74%), type 2 diabetes (48%), and arthritis (33%). The most commonly reported SDOH was food insecurity (49%), followed by reduced healthcare access due to lack of transportation (34%). These characteristics and SDOH may be common in groups typically underrepresented in clinical trials.
TABLE 1.
Demographic characteristics of participants in the Mobile Health and Wellness Prescription Produce Program in 2022 and 2023 overall and by years completed.
| Characteristics | Unique participants (N = 88) | 1 year participant (n = 61) | 2 years participant (n = 27) | |||
|---|---|---|---|---|---|---|
| M | SD | M | SD | M | SD | |
| Age (years) | 66.5 | 10.2 | 66.5 | 11.1 | 66.6 | 8.0 |
| Number of medications | 10.2 | 5.9 | 9.9 | 5.9 | 10.9 | 5.8 |
| N | % | n | % | n | % | |
|---|---|---|---|---|---|---|
| Gender | ||||||
| Female | 57 | 64.8 | 38 | 62.3 | 19 | 70.4 |
| Male | 31 | 35.2 | 23 | 37.7 | 8 | 29.6 |
| Race and ethnicity | ||||||
| Black or African American | 74 | 84.1 | 51 | 83.6 | 23 | 85.2 |
| White | 10 | 11.4 | 7 | 11.5 | 3 | 11.1 |
| Hispanic or Latino | 2 | 2.3 | 1 | 1.6 | 1 | 3.7 |
| Multiracial | 1 | 1.1 | 1 | 1.6 | 0 | 0 |
| Asian | 1 | 1.1 | 1 | 1.6 | 0 | 0 |
| Education | ||||||
| Nursery/preschool to 8th grade | 5 | 5.7 | 4 | 5.6 | 1 | 3.7 |
| Some high school, no diploma | 18 | 20.5 | 15 | 24.6 | 3 | 11.1 |
| High school graduate or GED | 20 | 22.7 | 10 | 16.4 | 10 | 37.0 |
| Trade/technical training | 8 | 9.1 | 6 | 9.8 | 2 | 7.4 |
| Some college | 19 | 21.6 | 11 | 18.0 | 8 | 29.6 |
| Associate degree | 4 | 4.5 | 1 | 1.6 | 3 | 11.1 |
| Bachelor degree | 5 | 5.7 | 5 | 9.2 | 0 | 0 |
| Graduate degree | 1 | 1.1 | 1 | 1.6 | 0 | 0 |
| Insurance coverage category | ||||||
| Medicaid/Medicare | 39 | 44.3 | 26 | 42.6 | 13 | 48.1 |
| Medicare a | 17 | 19.3 | 14 | 23.0 | 4 | 11.1 |
| Medicaid a | 14 | 15.9 | 10 | 16.4 | 4 | 14.8 |
| Private‐only | 7 | 8.0 | 5 | 8.2 | 2 | 7.4 |
| VA‐only | 3 | 3.4 | 2 | 3.3 | 1 | 3.7 |
| Missing | 6 | 6.8 | 3 | 4.9 | 3 | 11.1 |
| Prevalence of diet‐dependent chronic diseases | ||||||
| Hypertension | 65 | 73.9 | 27 | 44.3 | 21 | 77.8 |
| Other | 46 | 52.3 | 23 | 37.7 | 18 | 66.7 |
| Diabetes | 42 | 47.7 | 21 | 34.4 | 13 | 48.1 |
| Arthritis | 29 | 33.0 | 12 | 19.7 | 12 | 44.4 |
| Depression | 19 | 21.6 | 8 | 13.1 | 9 | 33.3 |
| Heart disease | 15 | 17.0 | 8 | 13.1 | 6 | 22.2 |
| Kidney disease | 7 | 8.0 | 4 | 6.6 | 2 | 7.4 |
| Cancer | 4 | 4.5 | 2 | 3.3 | 2 | 7.4 |
| Alzheimers | 1 | 1.1 | 0 | 0.0 | 0 | 0 |
| Social driver of health needs b | ||||||
| Food insecurity | 43 | 48.9 | 25 | 41.0 | 18 | 66.7 |
| Housing insecurity | 19 | 21.6 | 20 | 32.8 | 10 | 37.0 |
| Reduced healthcare access due to lack of transportation | 30 | 34.1 | 10 | 16.4 | 9 | 33.3 |
| None | 35 | 39.8 | 22 | 36.1 | 13 | 48.1 |
Medicare and Medicaid coverage includes those with private and VA supplements.
Multiple health‐related social needs could be selected; therefore the total is more than 100%.
Out of the 61 participants who completed a single year of the MHWP‐PPP (2022 or 2023), 87.8% reported medication adherence at program start compared to 87.5% at program end. Out of the 27 participants who completed the program in both 2022 and 2023, 82.4% reported medication adherence at baseline in 2022 compared to 85.2% after completing the program in 2023. The proportion of those reporting medication adherence in this community group was higher than global estimates around 50% [10].
We examined how retention over a 2‐year period may influence medication adherence. A Chi‐squared analysis showed a nonsignificant difference in medication adherence (χ 2 = 0.142, p = 0.706) among participants who completed a single year of the MHWP‐PPP. However, among individuals who completed both years, Chi‐squared results showed a significant difference in medication adherence (χ 2 = 14.603, p < 0.001) after completing the second PPP season in 2023 compared to the baseline in 2022, with greater adherence rates at the end of the second year. This result suggests that continued engagement over multiple years may be associated with higher self‐reported medication adherence.
It is possible that MHWP +PPP effectively recruits and retains already motivated and adherent individuals. It may also be that engaging with MHWP helps to maintain medication adherence, a complex behavior, particularly given polypharmacy and the range of conditions reported in this project that are also more common in UHHM older adults. Global self‐reported medication adherence has benefits and limitations [10].
5. Future Directions
Implementing novel community‐based approaches, such as those described here, may bring research to communities in ways that facilitate meaningful inclusion of underrepresented groups in clinical trials and promote health equity.
Use of a self‐reported medication adherence tool, along with wellness programs, may support protocol compliance measures and potential clinical trial success. Suggestions for reporting and use of medication adherence in practice and clinical trials are available [3, 10].
Researchers exploring opportunities to engage underrepresented groups may benefit from partnering with existing and well‐established community‐based programs to mitigate some of the common SDOH barriers to recruitment, retention and medication adherence in clinical trials.
Conflicts of Interest
The authors declare no conflicts of interest. As an Associate Editor for Clinical and Translational Science, Elvin Price was not involved in the review or decision process for this paper.
Supporting information
Figure S1: cts70385‐sup‐0001‐FigureS1.docx.
Acknowledgments
The authors thank the program participants, as well as the faculty, staff, and students of the Mobile Health and Wellness Program. The authors also wish to thank community partners, including each housing community and Shalom Farms. The authors thank the Virginia Center on Aging for their financial support of the program. The project described was in part supported by CTSA award No. UM1TR004360 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health.
Regal R., Williams J., Falls K., et al., “Informing Inclusive Engagement in Clinical Research: Insights From a Long‐Standing Community‐Based Wellness and Prescription Produce Program,” Clinical and Translational Science 18, no. 11 (2025): e70385, 10.1111/cts.70385.
Funding: The Prescription Produce Program received a Geriatric Training and Education grant from the Virginia Center on Aging. J.W., E.T.P., K.B., A.F.D. are supported by the Virginia Commonwealth University ConvergenceLabs@VCU—Health Outcomes.
References
- 1. Kelsey M. D., Patrick‐Lake B., Abdulai R., et al., “Inclusion and Diversity in Clinical Trials: Actionable Steps to Drive Lasting Change,” Contemporary Clinical Trials 116 (2022): 106740, 10.1016/j.cct.2022.106740. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. U.S. Food & Drug Administration , 2020 Drug Trials Snapshots Summary Report (U.S. Food & Drug Administration, 2020), https://www.fda.gov/media/145718/download. [Google Scholar]
- 3. Eliasson L., Clifford S., Mulick A., Jackson C., and Vrijens B., “How the EMERGE Guideline on Medication Adherence Can Improve the Quality of Clinical Trials,” British Journal of Clinical Pharmacology 86, no. 4 (2020): 687–697, 10.1111/bcp.14240. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. King S., Trabanino S., Azizi Z., and Rodriguez F., “Leveraging Social Determinants of Health to Enhance Recruitment of Underrepresented Populations in Clinical Trials,” Methodist DeBakey Cardiovascular Journal 20, no. 5 (2024): 81–88, 10.14797/mdcvj.1447. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Berkowitz S. A., Seligman H. K., and Choudhry N. K., “Treat or Eat: Food Insecurity, Cost‐Related Medication Underuse, and Unmet Needs,” American Journal of Medicine 127, no. 4 (2014): 303–310.e3, 10.1016/j.amjmed.2014.01.002. [DOI] [PubMed] [Google Scholar]
- 6. Diallo A. F., Mackiewicz M., Sargent L., et al., “Cultivating Relationships as a Community‐Based Recruitment Strategy in Transdisciplinary Aging Research: Lessons From an Academic‐Community Partnership,” Family & Community Health 47, no. 1 (2024): 32–40, 10.1097/FCH.0000000000000383. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Battle K., Falls K., Regal R., et al., “A Prescription Produce Program Integrating Lifestyle Behavior Counseling and Health Education: A Program Description and Evaluation,” Translational Behavioral Medicine 15, no. 1 (2025): ibae067, 10.1093/tbm/ibae067. [DOI] [PubMed] [Google Scholar]
- 8. Lee S., Bae Y. H., Worley M., and Law A., “Validating the Modified Drug Adherence Work‐Up (M‐DRAW) Tool to Identify and Address Barriers to Medication Adherence,” Pharmacy 5, no. 3 (2017): 52, 10.3390/pharmacy5030052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Harris P. A., Taylor R., Minor B. L., et al., “The REDCap Consortium: Building an International Community of Software Platform Partners,” Journal of Biomedical Informatics 95 (2019): 103208, 10.1016/j.jbi.2019.103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Stewart S. F., Moon Z., and Horne R., “Medication Nonadherence: Health Impact, Prevalence, Correlates and Interventions,” Psychology & Health 38, no. 6 (2023): 726–765, 10.1080/08870446.2022.2144923. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1: cts70385‐sup‐0001‐FigureS1.docx.
