ArticleHealth affairs (Project Hope)2021
Respecting Autonomy And Enabling Diversity: The Effect Of Eligibility And Enrollment On Research Data Demographics.
Article in Health affairs (Project Hope), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Associations of Individual- and Neighborhood-Level Factors with Racial and Ethnic Disparities in Timely Dementia Diagnosis.Journal of general internal medicine · 2026Observational
- "I make my own decisions": Views on precision medicine research participation decisions from adults with intellectual disability.HGG advances · 2026Article
- Artificial intelligence integrated multi-omics and multimodal studies promote the efficacy of neoadjuvant chemotherapy in breast cancer: opportunities, challenges, and future perspectives.Breast cancer research : BCR · 2026Review
- Factors for Patient Trust and Acceptance of Medical Artificial Intelligence.JAMA network open · 2026Article
- eConsent vs traditional consent among prospective biobank participants: a randomized study within a study trial.npj digital public health · 2026Article
- The Genetic Data Market: Institutional Governance of Academic/Industry Research Partnerships for the Public Good.The American journal of bioethics : AJOB · 2025Article
- eConsent vs. Traditional Consent Among Prospective Biobank Participants: A Randomized Trial.medRxiv : the preprint server for health sciences · 2025Article
- Lessons for a learning health system: Effectively communicating to patients about research with their health information and biospecimens.Learning health systems · 2025Article
- Artificial Intelligence to Promote Racial and Ethnic Cardiovascular Health Equity.Current cardiovascular risk reports · 2024Article
- Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart Association.Circulation · 2023Review
- Use of Bland-Altman Analysis to Examine the Racial and Ethnic Representativeness of Study Populations in Community-Based Pediatric Health Research.JAMA network open · 2023Article
- The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients.Cell genomics · 2023Article
- "Consent Does Not Scale": Laying Out the Tensions in Balancing Patient Autonomy with Public Benefit in Commercializing Biospecimens.The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics · 2023Review
- Social determinants of health data in solid organ transplantation: National data sources and future directions.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2022Review
- Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning.Proceedings of machine learning research · 2022Article
- Promoting Ethical Deployment of Artificial Intelligence and Machine Learning in Healthcare.The American journal of bioethics : AJOB · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Many promising advances in precision health and other Big Data research rely on large data sets to analyze correlations among genetic variants, behavior, environment, and outcomes to improve population health. But these data sets are generally populated with demographically homogeneous cohorts. We conducted a retrospective cohort study of patients at a major academic medical center during 2012-19 to explore how recruitment and enrollment approaches affected the demographic diversity of participants in its research biospecimen and data bank. We found that compared with the overall clinical population, patients who consented to enroll in the research data bank were significantly less diverse in terms of age, sex, race, ethnicity, and socioeconomic status. Compared with patients who were recruited for the data bank, patients who enrolled were younger and less likely to be Black or African American, Asian, or Hispanic. The overall demographic diversity of the data bank was affected as much (and in some cases more) by which patients were considered eligible for recruitment as by which patients consented to enroll. Our work underscores the need for systemic commitment to diversify data banks so that different communities can benefit from research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.