Evidence map›Paper›PMID 35657813›Full record

ArticlePloS one2022

Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.

Sarah Naz-McLean, Andy Kim, Andrew Zimmer, Hannah Laibinis, Jen Lapan, Paul Tyman, Jessica Hung, Christina Kelly, Himaja Nagireddy, Surya Narayanan-Pandit and 8 more

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
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

15 citing papers in PubMed, 17 citations in OpenAlex.

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  3. Optimizing participation in digital health studies: understanding appointment attendance.Journal of the American Medical Informatics Association : JAMIA · 2026
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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

18 authors at 2 institutions in 3 countries.

Sarah Naz-McLeanDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Andy KimDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.ORCID 0000-0001-6551-2881
Andrew ZimmerBroad Institute of MIT and Harvard, Cambridge, MA, United States of America.
Hannah LaibinisDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Jen LapanBroad Institute of MIT and Harvard, Cambridge, MA, United States of America.
Paul TymanBroad Institute of MIT and Harvard, Cambridge, MA, United States of America.
Jessica HungDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Christina KellyDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Himaja NagireddyDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Surya Narayanan-PanditBroad Institute of MIT and Harvard, Cambridge, MA, United States of America.
Margaret McCarthyDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Saee RatnaparkhiDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Henry RutherfordDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Rajesh PatelDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, United States of America.
Scott Dryden-PetersonDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Deborah T HungDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Ann E WoolleyDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.
Lisa A CosimiDivision of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, United States of America.ORCID 0000-0002-5269-1881
Broad Institute · USBrigham and Women's Hospital · US

Funding

Covid-19-related cervical cancer treatment interruption and role of neoadjuvant chemotherapyR01CA236546 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI DRYDEN-PETERSON, SCOTT · 2019 to 2023
$2.5M
NCI NIH HHS R01 CA236546
6 · The paper itself

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.

Indexed as

COVID-19AdolescentAdultAgedAged, 80 and overClinical Trials as TopicCohort StudiesFeasibility StudiesFemaleHumansMaleMiddle AgedPandemicsSARS-CoV-2Young Adult

Identifiers

PMID35657813
PMCPMC9165767
OpenAlexW4281871452

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.