Evidence map›Paper›PMID 40599176›Full record

ArticleJournal of clinical and translational science2025

Participant experiences in a decentralized clinical trial using digital health technologies: The ACTIV-6 study.

Carrie Reale, Janelle Faiman, Russ Beebe, Jessica S Marlin, Sean Collins, David R Boulware, Sarah E Dunsmore, Florence Thicklin, Thomas G Stewart, Adrian F Hernandez and 4 more

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. 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

14 authors.

Carrie RealeCenter for Research and Innovation in Systems Safety (CRISS), Vanderbilt University Medical Center, Nashville, TN, USA.ORCID https://orcid.org/0000-0002-9011-2692
Janelle FaimanCenter for Research and Innovation in Systems Safety (CRISS), Vanderbilt University Medical Center, Nashville, TN, USA.
Russ BeebeCenter for Research and Innovation in Systems Safety (CRISS), Vanderbilt University Medical Center, Nashville, TN, USA.
Jessica S MarlinVanderbilt Institute for Clinical and Translational Research (VICTR), Vanderbilt University Medical Center, Nashville, TN, USA.
Sean CollinsDepartment of Emergency Medicine, Vanderbilt University Medical Center and Veterans Affairs Tennessee Valley Healthcare System, Geriatric Research, Education and Clinical Center (GRECC), Nashville, TN, USA.
David R BoulwareDepartment of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA.ORCID https://orcid.org/0000-0002-4715-0060
Sarah E DunsmoreNational Center for Advancing Translational Sciences, Bethesda, MD, USA.
Florence ThicklinStakeholder Advisory Committee, Pittsburgh, PA, USA.
Thomas G StewartSchool of Data Science, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0002-5138-0758
Adrian F HernandezDuke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA.ORCID https://orcid.org/0000-0003-3387-9616
Russell L RothmanInstitute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Christopher J LindsellDuke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA.ORCID https://orcid.org/0000-0002-3297-2811
Shilo AndersCenter for Research and Innovation in Systems Safety (CRISS), Vanderbilt University Medical Center, Nashville, TN, USA.
Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV)-6 Study Group and Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inadequate recruitment and retention impede clinical trial goals. Emerging decentralized clinical trials (DCTs) leveraging digital health technologies (DHTs) for remote recruitment and data collection aim to address barriers to participation in traditional trials. The ACTIV-6 trial is a DCT using DHTs, but participants' experiences of such trials remain largely unknown. This study explored participants' perspectives of the ACTIV-6 DCT that tested outpatient COVID-19 therapeutics. Methods: Participants in the ACTIV-6 study were recruited via email to share their day-to-day trial experiences during 1-hour virtual focus groups. Two human factors researchers guided group discussions through a semi-structured script that probed expectations and perceptions of study activities. Qualitative data analysis was conducted using a grounded theory approach with open coding to identify key themes. Results: Twenty-eight ACTIV-6 study participants aged 30+ years completed a virtual focus group including 1-4 participants each. Analysis yielded three major themes: perceptions of the DCT experience, study activity engagement, and trust. Participants perceived the use of remote DCT procedures supported by DHTs as an acceptable and efficient method of organizing and tracking study activities, communicating with study personnel, and managing study medications at home. Use of social media was effective in supporting geographically dispersed participant recruitment but also raised issues with trust and study legitimacy. Conclusions: While participants in this qualitative study viewed the DCT-with-DHT approach as reasonably efficient and engaging, they also identified challenges to address. Understanding facilitators and barriers to DCT participation and DHT interaction can help improve future research design.

Indexed as

Decentralized clinical trialsdigital health technologieselectronic data capturerecruitmentresearch participant experience

Identifiers

PMID40599176
PMCPMC12209966

What OpenQuestion holds

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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.