Evidence map›Paper›PMID 40215482›Full record

ArticleJournal of medical Internet research2025

Approach to Design and Evaluate Digital Tools to Enhance Young Adult Participation in Clinical Trials: Co-Design and Controlled Intercept Study.

Tim Mackey, Raphael E Cuomo, Qing Xu, Tiana J McMann, Zhuoran Li, Mingxiang Cai, Christine Wenzel, Joshua S Yang

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Tim MackeyGlobal Health Program, Department of Anthropology, University of California San Diego, La Jolla, CA, United States.ORCID https://orcid.org/0000-0002-2191-7833
Raphael E CuomoGlobal Health Policy and Data Institute, San Diego, CA, United States.ORCID https://orcid.org/0000-0002-8179-0619
Qing XuS-3 Research, San Diego, CA, United States.ORCID https://orcid.org/0000-0002-4507-1094
Tiana J McMannGlobal Health Program, Department of Anthropology, University of California San Diego, La Jolla, CA, United States.ORCID https://orcid.org/0000-0003-1964-5549
Zhuoran LiGlobal Health Policy and Data Institute, San Diego, CA, United States.ORCID https://orcid.org/0000-0001-6192-4301
Mingxiang CaiS-3 Research, San Diego, CA, United States.ORCID https://orcid.org/0000-0001-6816-5192
Christine WenzelS-3 Research, San Diego, CA, United States.ORCID https://orcid.org/0000-0002-6219-9196
Joshua S YangDepartment of Public Health, California State University, Fullerton, Fullerton, CA, United States.ORCID https://orcid.org/0000-0002-9224-6053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCertain populations are underrepresented in clinical trials, limiting the generalizability of new treatments and their efficacy and uptake in these populations. It is essential to identify and understand effective strategies for enrolling young adults in clinical trials, as they represent a vital and key demographic for future clinical trial participation.

objectiveThis study aimed to develop, test, and evaluate digital tools designed to encourage the participation of young adults in the clinical trial process. An interdisciplinary approach, incorporating social listening, qualitative focus groups, and co-design workshops, was used to achieve this goal.

methodsDigital tools were designed and evaluated using a 4-phase approach that included: (1) social listening to characterize lived experiences with COVID-19 trials as self-reported by online users, (2) qualitative focus groups with young adults to explore specific lived attitudes and experiences related to COVID-19 clinical research hesitancy and engagement, (3) a series of cocreation and co-design workshops to build digital tools aimed at encouraging clinical trial participation, and (4) a controlled intercept study to assess the usability and specific outcome measures of the co-designed digital tools among young adults.

resultsA significantly higher change in the likelihood of participating in a clinical trial post exposure was observed among study participants when exposed to prototypes of a mobile app (Δ=0.74 on a 10-point scale, P<.01) and website (Δ=0.93, P<.01) compared to those exposed to a Facebook ad (Δ=0.21) but not a digital flyer (Δ=0.58). Furthermore, those exposed to the mobile app (x̅=5.76, P=.04) and electronic flier (x̅=5.72, P=.04), but not the website (x̅=5.55), exhibited significantly higher postexposure interest in learning about clinical trials when compared to participants exposed to the Facebook (Meta) ad (x̅=5.06). Participants in the intercept study were more likely to consider joining a clinical trial after seeing a mobile app (Δ=0.74, P<.01) or website (Δ=0.93, P<.001) compared to a Facebook ad (Δ=0.21), but the digital flyer (Δ=0.58) did not show a significant difference. In addition, those who saw the mobile app (x̅=5.76, P=.04) or the digital flyer (x̅=5.72, P=.04) showed more interest in learning about clinical trials than those who saw the Facebook ad (x̅=5.06), though the website (x̅= 5.55) did not significantly impact interest.

conclusionsMobile apps and web pages co-designed with young diverse adults may represent effective digital tools to advance shared goals of encouraging inclusive clinical trials.

Indexed as

Clinical Trials as TopicPatient ParticipationPatient SelectionAdolescentAdultCOVID-19FemaleFocus GroupsHumansMaleSARS-CoV-2Young Adultclinical trialscoronavirus diseaseCOVID-19digital healthhealth

Identifiers

PMID40215482
PMCPMC12032498

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.