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Introduction Participation from racial and ethnic minorities in clinical trials has been burdened by issues surrounding mistrust and access to healthcare. There is emerging use of machine learning (ML) in clinical trial recruitment and evaluation. However, for individuals from groups who are recipients of societal biases, utilisation of ML can lead to the creation and use of biased algorithms. To minimise bias, the design of equitable ML tools that advance health equity could be guided by community engagement processes. The Howard University Partnership with the National Institutes of Health for Equitable Clinical Trial Participation for Racial/Ethnic Communities Underrepresented in Research (HoPeNET) seeks to create an ML-based infrastructure from community advisory board (CAB) experiences to enhance participation of African-Americans/Blacks in clinical trials.Methods and analysis This triphased cross-sectional study (24 months, n=56) will create a CAB of community members and research investigators. The three phases of the study include: (1) identification of perceived barriers/facilitators to clinical trial engagement through qualitative/quantitative methods and systems-based model building participation; (2) operation of CAB meetings and (3) development of a predictive ML tool and outcome evaluation. Identified predictors from the participant-derived systems-based map will be used for the ML tool development.Ethics and dissemination We anticipate minimum risk for participants. Institutional review board approval and informed consent has been obtained and patient confidentiality ensured.

BackgroundInnovative analyses of cardiovascular (CV) risk markers and health behaviors linked to neighborhood stressors are essential to further elucidate the mechanisms by which adverse neighborhood social conditions lead to poor CV outcomes. We propose to objectively measure physical activity (PA), sedentary behavior, and neighborhood stress using accelerometers, GPS, and real-time perceived ecological momentary assessment via smartphone apps and to link these to biological measures in a sample of White and African American women in Washington, DC, neighborhoods. ObjectiveThe primary aim of this study is to test the hypothesis that living in adverse neighborhood social conditions is associated with higher stress-related neural activity among 60 healthy women living in high or low socioeconomic status neighborhoods in Washington, DC. Sub-aim 1 of this study is to test the hypothesis that the association is moderated by objectively measured PA using an accelerometer. A secondary objective is to test the hypothesis that residing in adverse neighborhood social environment conditions is related to differences in vascular function. Sub-aim 2 of this study is to test the hypothesis that the association is moderated by objectively measured PA. The third aim of this study is to test the hypothesis that adverse neighborhood social environment conditions are related to differences in immune system activation. MethodsThe proposed study will be cross-sectional, with a sample of at least 60 women (30 healthy White women and 30 healthy Black women) from Wards 3 and 5 in Washington, DC. A sample of the women (n=30) will be recruited from high-income areas in Ward 3 from census tracts within a 15% of Ward 3’s range for median household income. The other participants (n=30) will be recruited from low-income areas in Wards 5 from census tracts within a 15% of Ward 5’s range for median household income. Finally, participants from Wards 3 and 5 will be matched based on age, race, and BMI. Participants will wear a GPS unit and accelerometer and report their stress and mood in real time using a smartphone. We will then examine the associations between GPS-derived neighborhood variables, stress-related neural activity measures, and adverse biological markers. ResultsThe National Institutes of Health Institutional Review Board has approved this study. Recruitment will begin in the summer of 2021. ConclusionsFindings from this research could inform the development of multilevel behavioral interventions and policies to better manage environmental factors that promote immune system activation or psychosocial stress while concurrently working to increase PA, thereby influencing CV health. International Registered Report Identifier (IRRID)PRR1-10.2196/29191

Introduction A mixed-method, co-design approach to studying the adoption of mobile health (mHealth) technology among African-American (AA) women has not been fully explored. Qualitative data may contextualise existing knowledge surrounding perceptions of mHealth among AA women as part of formative work for designing a physical activity application (app).Methods A convenience sample of 16 AA women completed an informatics survey prior to participating in focus groups exploring their use of mobile technology and health apps. Survey responses provided frequency data, while iterative transcript analysis of focus groups identified themes.Results The majority of participants (mean age=62.1 years, SD=6.6) felt comfortable using a tablet/smartphone (75.0%). Most (68.8%) reported using health-related apps, primarily focused on physical activity and nutrition. Focus groups revealed four overarching concepts, including (1) user attachment, (2) technology adoption, (3) potential facilitators and (4) potential barriers. Important features which may serve as facilitators or barriers to future adoption of a mobile app for an mHealth intervention include individual app tailoring and software concerns, respectively.Discussion Thematic analysis revealed high user attachment to smartphones and described participants’ process for adopting new mHealth technology.Conclusion Early engagement of target end users as a part of a broader co-design and community-based participatory research process for developing mHealth technologies may be useful for sustained adoption of these tools in future mHealth behavioural interventions.