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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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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. |
format | Online Article Text |
id | pubmed-7026051 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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