ArticlePloS one2022
Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 17 citations in OpenAlex.
- Patient-reported outcomes and home-based self-swabs for influenza-like illness events - lessons learned from the 2023/2024 DANFLU-2 Homeswab PRO substudy.Journal of patient-reported outcomes · 2025Trial
- A 40-week phase 2B randomized, multicenter, double-blind, placebo-controlled study evaluating the safety and efficacy of memantine in amyotrophic lateral sclerosis.Muscle & nerve · 2025Trial
- Optimizing participation in digital health studies: understanding appointment attendance.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Ethical Challenges and Considerations in Decentralized Clinical Trials (DCTs): Insights from a Scoping Review.Therapeutic innovation & regulatory science · 2026Article
- Article
- The OurHealth Study: A digital genomic cohort for cardiometabolic risk mechanisms in US South Asians.NPJ digital medicine · 2026Review
- Increasing Retention in a Large-Scale Decentralized Clinical Trial: Learnings From the COVID-RED Trial.Mayo Clinic proceedings. Digital health · 2025Article
- Participant engagement in a national longitudinal study of COVID-19: Insights from the INSPIRE study.PloS one · 2025Article
- Reliability of the Italian Version of the Fugl-Meyer Upper Extremity Scale Administered Remotely.Journal of clinical medicine · 2024Article
- Quantitative biomechanical analysis in validating a video-based model to remotely assess physical frailty: a potential solution to telehealth and globalized remote-patient monitoring.Biomedical engineering letters · 2024Article
- Impact of financial compensation on enrollment and participation in a remote, mobile-app based research study.Journal of clinical and translational science · 2024Article
- Article
- At-home Testing and Risk Factors for Acquisition of SARS-CoV-2 Infection in a Major US Metropolitan Area.Open forum infectious diseases · 2022Article
- Sleep patterns of patients receiving home parenteral nutrition: A home-based observational study.JPEN. Journal of parenteral and enteral nutrition · 2022Observational
- At-home Testing and Risk Factors for Acquisition of SARS-CoV-2 Infection in a Major US Metropolitan Area.medRxiv : the preprint server for health sciences · 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
18 authors at 2 institutions in 3 countries.
Funding
Abstract
Longitudinal clinical studies traditionally require in-person study visits which are well documented to pose barriers to participation and contribute challenges to enrolling representative samples. Remote trial models may reduce barriers to research engagement, improve retention, and reach a more representative cohort. As remote trials become more common following the COVID-19 pandemic, a critical evaluation of this approach is imperative to optimize this paradigm shift in research. The TestBoston study was launched to understand prevalence and risk factors for COVID-19 infection in the greater Boston area through a fully remote home-testing model. Participants (adults, within 45 miles of Boston, MA) were recruited remotely from patient registries at Brigham and Women's Hospital and the general public. Participants were provided with monthly and "on-demand" at-home SARS-CoV-2 RT-PCR and antibody testing using nasal swab and dried blood spot self-collection kits and electronic surveys to assess symptoms and risk factors for COVID-19 via an online dashboard. Between October 2020 and January 2021, we enrolled 10,289 participants reflective of Massachusetts census data. Mean age was 47 years (range 18-93), 5855 (56.9%) were assigned female sex at birth, 7181(69.8%) reported being White non-Hispanic, 952 (9.3%) Hispanic/Latinx, 925 (9.0%) Black, 889 (8.6%) Asian, and 342 (3.3%) other and/or more than one race. Lower initial enrollment among Black and Hispanic/Latinx individuals required an adaptive approach to recruitment, leveraging connections to the medical system, coupled with community partnerships to ensure a representative cohort. Longitudinal retention was higher among participants who were White non-Hispanic, older, working remotely, and with lower socioeconomic vulnerability. Implementation highlighted key differences in remote trial models as participants independently navigate study milestones, requiring a dedicated participant support team and robust technology platforms, to reduce barriers to enrollment, promote retention, and ensure scientific rigor and data quality. Remote clinical trial models offer tremendous potential to engage representative cohorts, scale biomedical research, and promote accessibility by reducing barriers common in traditional trial design. Barriers and burdens within remote trials may be experienced disproportionately across demographic groups. To maximize engagement and retention, researchers should prioritize intensive participant support, investment in technologic infrastructure and an adaptive approach to maximize engagement and retention.
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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.