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Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants

Digital technologies such as smartphones are transforming the way scientists conduct biomedical research. Several remotely conducted studies have recruited thousands of participants over a span of a few months allowing researchers to collect real-world data at scale and at a fraction of the cost of...

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Autores principales: Pratap, Abhishek, Neto, Elias Chaibub, Snyder, Phil, Stepnowsky, Carl, Elhadad, Noémie, Grant, Daniel, Mohebbi, Matthew H., Mooney, Sean, Suver, Christine, Wilbanks, John, Mangravite, Lara, Heagerty, Patrick J., Areán, Pat, Omberg, Larsson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026051/
https://www.ncbi.nlm.nih.gov/pubmed/32128451
http://dx.doi.org/10.1038/s41746-020-0224-8
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author Pratap, Abhishek
Neto, Elias Chaibub
Snyder, Phil
Stepnowsky, Carl
Elhadad, Noémie
Grant, Daniel
Mohebbi, Matthew H.
Mooney, Sean
Suver, Christine
Wilbanks, John
Mangravite, Lara
Heagerty, Patrick J.
Areán, Pat
Omberg, Larsson
author_facet Pratap, Abhishek
Neto, Elias Chaibub
Snyder, Phil
Stepnowsky, Carl
Elhadad, Noémie
Grant, Daniel
Mohebbi, Matthew H.
Mooney, Sean
Suver, Christine
Wilbanks, John
Mangravite, Lara
Heagerty, Patrick J.
Areán, Pat
Omberg, Larsson
author_sort Pratap, Abhishek
collection PubMed
description Digital technologies such as smartphones are transforming the way scientists conduct biomedical research. Several remotely conducted studies have recruited thousands of participants over a span of a few months allowing researchers to collect real-world data at scale and at a fraction of the cost of traditional research. Unfortunately, remote studies have been hampered by substantial participant attrition, calling into question the representativeness of the collected data including generalizability of outcomes. We report the findings regarding recruitment and retention from eight remote digital health studies conducted between 2014–2019 that provided individual-level study-app usage data from more than 100,000 participants completing nearly 3.5 million remote health evaluations over cumulative participation of 850,000 days. Median participant retention across eight studies varied widely from 2–26 days (median across all studies = 5.5 days). Survival analysis revealed several factors significantly associated with increase in participant retention time, including (i) referral by a clinician to the study (increase of 40 days in median retention time); (ii) compensation for participation (increase of 22 days, 1 study); (iii) having the clinical condition of interest in the study (increase of 7 days compared with controls); and (iv) older age (increase of 4 days). Additionally, four distinct patterns of daily app usage behavior were identified by unsupervised clustering, which were also associated with participant demographics. Most studies were not able to recruit a sample that was representative of the race/ethnicity or geographical diversity of the US. Together these findings can help inform recruitment and retention strategies to enable equitable participation of populations in future digital health research.
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spelling pubmed-70260512020-03-03 Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants Pratap, Abhishek Neto, Elias Chaibub Snyder, Phil Stepnowsky, Carl Elhadad, Noémie Grant, Daniel Mohebbi, Matthew H. Mooney, Sean Suver, Christine Wilbanks, John Mangravite, Lara Heagerty, Patrick J. Areán, Pat Omberg, Larsson NPJ Digit Med Article Digital technologies such as smartphones are transforming the way scientists conduct biomedical research. Several remotely conducted studies have recruited thousands of participants over a span of a few months allowing researchers to collect real-world data at scale and at a fraction of the cost of traditional research. Unfortunately, remote studies have been hampered by substantial participant attrition, calling into question the representativeness of the collected data including generalizability of outcomes. We report the findings regarding recruitment and retention from eight remote digital health studies conducted between 2014–2019 that provided individual-level study-app usage data from more than 100,000 participants completing nearly 3.5 million remote health evaluations over cumulative participation of 850,000 days. Median participant retention across eight studies varied widely from 2–26 days (median across all studies = 5.5 days). Survival analysis revealed several factors significantly associated with increase in participant retention time, including (i) referral by a clinician to the study (increase of 40 days in median retention time); (ii) compensation for participation (increase of 22 days, 1 study); (iii) having the clinical condition of interest in the study (increase of 7 days compared with controls); and (iv) older age (increase of 4 days). Additionally, four distinct patterns of daily app usage behavior were identified by unsupervised clustering, which were also associated with participant demographics. Most studies were not able to recruit a sample that was representative of the race/ethnicity or geographical diversity of the US. Together these findings can help inform recruitment and retention strategies to enable equitable participation of populations in future digital health research. Nature Publishing Group UK 2020-02-17 /pmc/articles/PMC7026051/ /pubmed/32128451 http://dx.doi.org/10.1038/s41746-020-0224-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Pratap, Abhishek
Neto, Elias Chaibub
Snyder, Phil
Stepnowsky, Carl
Elhadad, Noémie
Grant, Daniel
Mohebbi, Matthew H.
Mooney, Sean
Suver, Christine
Wilbanks, John
Mangravite, Lara
Heagerty, Patrick J.
Areán, Pat
Omberg, Larsson
Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
title Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
title_full Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
title_fullStr Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
title_full_unstemmed Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
title_short Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
title_sort indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026051/
https://www.ncbi.nlm.nih.gov/pubmed/32128451
http://dx.doi.org/10.1038/s41746-020-0224-8
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