Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
Abstract 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...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2020-02-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-020-0224-8 |
| _version_ | 1797643133637361664 |
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| author | Abhishek Pratap Elias Chaibub Neto Phil Snyder Carl Stepnowsky Noémie Elhadad Daniel Grant Matthew H. Mohebbi Sean Mooney Christine Suver John Wilbanks Lara Mangravite Patrick J. Heagerty Pat Areán Larsson Omberg |
| author_facet | Abhishek Pratap Elias Chaibub Neto Phil Snyder Carl Stepnowsky Noémie Elhadad Daniel Grant Matthew H. Mohebbi Sean Mooney Christine Suver John Wilbanks Lara Mangravite Patrick J. Heagerty Pat Areán Larsson Omberg |
| author_sort | Abhishek Pratap |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-11T14:10:16Z |
| format | Article |
| id | doaj.art-86d1232336c940b38797a6044e476fd1 |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-11T14:10:16Z |
| publishDate | 2020-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-86d1232336c940b38797a6044e476fd12023-11-02T00:11:29ZengNature Portfolionpj Digital Medicine2398-63522020-02-013111010.1038/s41746-020-0224-8Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participantsAbhishek Pratap0Elias Chaibub Neto1Phil Snyder2Carl Stepnowsky3Noémie Elhadad4Daniel Grant5Matthew H. Mohebbi6Sean Mooney7Christine Suver8John Wilbanks9Lara Mangravite10Patrick J. Heagerty11Pat Areán12Larsson Omberg13Sage BionetworksSage BionetworksSage BionetworksUniversity of CaliforniaColumbia UniversityNovartis Pharmaceutical CorporationGoodRxDepartment of Biomedical Informatics and Medical Education, University of WashingtonSage BionetworksSage BionetworksSage BionetworksDepartment of Biostatistics, University of WashingtonDepartment of Psychiatry & Behavioral Sciences, University of WashingtonSage BionetworksAbstract 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.https://doi.org/10.1038/s41746-020-0224-8 |
| spellingShingle | Abhishek Pratap Elias Chaibub Neto Phil Snyder Carl Stepnowsky Noémie Elhadad Daniel Grant Matthew H. Mohebbi Sean Mooney Christine Suver John Wilbanks Lara Mangravite Patrick J. Heagerty Pat Areán Larsson Omberg Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants npj Digital Medicine |
| 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 |
| url | https://doi.org/10.1038/s41746-020-0224-8 |
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