Evidence map›Paper›PMID 40106344›Full record

ArticleInteractive journal of medical research2025

Long-Term Engagement of Diverse Study Cohorts in Decentralized Research: Longitudinal Analysis of "All of Us" Research Program Data.

Vijay Yadav, Elias Chaibub Neto, Megan Doerr, Abhishek Pratap, Larsson Omberg

Abstract read
In one paragraph

Article in Interactive journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Weight discrimination and metabolic syndrome: Examining discrimination attributions and frequency across settings.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2026
    Article
  2. Association of neurodevelopmental conditions with Alzheimer's disease and related dementias and Parkinson's disease.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vijay YadavSage Bionetworks, 2901 3rd Ave #330, Seattle, WA, 98121, United States, 1 6466838830.ORCID http://orcid.org/0000-0003-2801-9005
Elias Chaibub NetoSage Bionetworks, 2901 3rd Ave #330, Seattle, WA, 98121, United States, 1 6466838830.ORCID http://orcid.org/0000-0002-9575-861X
Megan DoerrSage Bionetworks, 2901 3rd Ave #330, Seattle, WA, 98121, United States, 1 6466838830.ORCID http://orcid.org/0000-0003-2383-5978
Abhishek PratapSage Bionetworks, 2901 3rd Ave #330, Seattle, WA, 98121, United States, 1 6466838830.ORCID http://orcid.org/0000-0002-5289-6932
Larsson OmbergSage Bionetworks, 2901 3rd Ave #330, Seattle, WA, 98121, United States, 1 6466838830.ORCID http://orcid.org/0000-0002-4719-9120

Funding

Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
NIH HHS U24 OD023176
6 · The paper itself

Abstract

Background: The generalizability of clinical research hinges on robust study designs, which include the recruitment and maintenance of a representative study population. This study examines the evolution of the demographic characteristics of 329,038 participants who enrolled and participated in The All of Us Research Program (AoURP), a decentralized study aimed at representing the diversity of the United States. Objective: The primary objectives of this study were to assess alterations in the demographic composition of the cohort at different protocol stages within AoURP, while analyzing completion rates and timeframes for survey and substudy completion. Additionally, we examined how participant interactions with the program impacted engagement and survey responses. Methods: We conducted a longitudinal analysis of the AoURP data, tracking changes in demographic composition, completion rates, and completion times for surveys and substudies. Comparative analyses were performed to assess differences in engagement and survey completion based on sociodemographic characteristics of participants involved in postenrollment study components. Results: The sociodemographic composition of the cohort that participated in the postenrollment study (eg, optional components) differed significantly from that of the recruited population. The proportion of self-identified White participants increased by 21.2%, whereas the proportion of Black or African American participants decreased by 12.18% (P=.02). Participants who identified as White (n=93,614, 52.7%) and NonHispanic (n=109,279, 42.21%) were more engaged compared to those identifying as Black or African American (n=10,887, 15.76%), Asian (n=4274, 38.72%), or Hispanic (n=12,530, 20.7%; P=.006). Participants' response times to study surveys and completeness varied across all demographic groups (P<.001). Furthermore, those identifying as White skipped fewer survey questions (1.19) compared to those identifying as Black or African American (1.40) or other racial and ethnic identities (P<.001). Conclusions: The AoURP dataset serves as an exceptional resource for investigating diverse public health concerns. However, the longitudinal analysis of participant-level data underscores a significant skew in population diversity, suggesting the need for targeted strategies to enhance engagement and retention across all groups. Ensuring diversity in the cohort is essential for maintaining the study's representativeness and the broad applicability of its findings.

Indexed as

All of Us Research Programdecentralized research cohortsdigital healthengagement behaviorretention

Identifiers

PMID40106344
PMCPMC11966662

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.