Evidence map›Paper›PMID 41282692›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Impact of Clinical Trial Virtualization on Recruitment in Underserved Communities for a Type 2 Diabetes mHealth Intervention.

Elizabeth Campbell, Andrea Cassells, T J Lin, Jacqeline Cortez Lainez, Arlene Smaldone, Pooja Desai, Haomiao Jia, George Hripcsak, Jonathan Tobin, Lena Mamykina

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Elizabeth CampbellDepartment of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Andrea CassellsClinical Directors Network, New York, NY, USA.
T J LinClinical Directors Network, New York, NY, USA.
Jacqeline Cortez LainezClinical Directors Network, New York, NY, USA.
Arlene SmaldoneColumbia University School of Nursing, New York, NY USA.
Pooja DesaiDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Haomiao JiaColumbia University School of Nursing, New York, NY USA.
George HripcsakDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Jonathan TobinClinical Directors Network, New York, NY, USA.
Lena MamykinaDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Dynamically Tailoring Interventions for Problem-Solving in Diabetes Self-Management Using Self-Monitoring Data - a Randomized Controlled Trial.R01DK113189 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MAMYKINA, OLENA · 2019 to 2023
$3.3M
NIDDK NIH HHS R01 DK113189NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Objective: Approaches to randomized clinical trial (RCT) implementation greatly changed during the COVID-19 pandemic as clinical trials transitioned to largely virtual implementation; virtual RCT implementation may continue in the future. Without careful consideration, virtual RCTs may exacerbate the historical under-representation of women, the elderly, and racial and ethnic minorities that has occurred in past clinical trials. The following study presents an approach to virtualizing an RCT for an mHealth intervention. Materials and Methods: Participants for the trial were recruited from Federally Qualified Health Centers in medically underserved areas of the New York City metropolitan area. Recruitment began in January 2020 but was paused in March 2020 due to the COVID-19 pandemic's onset. The research team developed a virtual protocol for recruitment, onboarding, and study implementation. Results: Study participants were predominantly from immigrant, low-income, and racial and ethnic minority groups. Our virtualization approach included an easier-to-understand consent form, expanded virtual training materials, and greater one-on-one attention during training. Our approach did not lead to significant changes in the population we recruited into the study or introduce additional biases and restriction. Discussion: Our study represents an early investigation into how the change from in-person clinical trial recruitment and study implementation to virtual during the COVID-19 pandemic may impact recruitment of participants from medically underserved communities into RCTs. Conclusion: This approach may be used in future trials testing mHealth and other technological interventions without exacerbating the under-representation of medically underserved populations.

Indexed as

Clinical Trials VirtualizationHealth EquitymHealthRandomized Clinical Trials

Identifiers

PMID41282692
PMCPMC12636685

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.