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Pratap A, Homiar A, Waninger L, Herd C, Suver C, Volponi J, Anguera JA, Areán P. Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression. Sci Data 2022; 9:522. [PMID: 36030226 PMCID: PMC9420101 DOI: 10.1038/s41597-022-01633-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 08/15/2022] [Indexed: 11/09/2022] Open
Abstract
Most people with mental health disorders cannot receive timely and evidence-based care despite billions of dollars spent by healthcare systems. Researchers have been exploring using digital health technologies to measure behavior in real-world settings with mixed results. There is a need to create accessible and computable digital mental health datasets to advance inclusive and transparently validated research for creating robust real-world digital biomarkers of mental health. Here we share and describe one of the largest and most diverse real-world behavior datasets from over two thousand individuals across the US. The data were generated as part of the two NIMH-funded randomized clinical trials conducted to assess the effectiveness of delivering mental health care continuously remotely. The longitudinal dataset consists of self-assessment of mood, depression, anxiety, and passively gathered phone-based behavioral data streams in real-world settings. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioral markers and understand the effectiveness of mental health care delivered continuously and remotely.
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Affiliation(s)
- Abhishek Pratap
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada. .,Department of Psychiatry, University of Toronto, Toronto, ON, Canada. .,Vector Institute for Artificial Intelligence, Toronto, ON, Canada. .,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. .,Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
| | - Ava Homiar
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.,School of Interdisciplinary Science, McMaster University, Hamilton, ON, Canada
| | - Luke Waninger
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Calvin Herd
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | | | - Joshua Volponi
- Department of Neurology, University of California San Francisco, San Francisco, WA, USA
| | - Joaquin A Anguera
- Department of Neurology, University of California San Francisco, San Francisco, WA, USA
| | - Pat Areán
- Department of Psychiatry & Behavioral Sciences, University of Washington, Seattle, WA, USA
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Pratap A, Neto EC, Snyder P, Stepnowsky C, Elhadad N, Grant D, Mohebbi MH, Mooney S, Suver C, Wilbanks J, Mangravite L, Heagerty PJ, Areán P, Omberg L. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. NPJ Digit Med 2020; 3:21. [PMID: 32128451 PMCID: PMC7026051 DOI: 10.1038/s41746-020-0224-8] [Citation(s) in RCA: 171] [Impact Index Per Article: 42.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 01/17/2020] [Indexed: 12/13/2022] Open
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.
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Affiliation(s)
- Abhishek Pratap
- Sage Bionetworks, Seattle, WA USA
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA USA
| | | | | | - Carl Stepnowsky
- University of California, San Diego, CA USA
- American Sleep Apnea Association, Washington, DC USA
| | | | - Daniel Grant
- Novartis Pharmaceutical Corporation, East Hanover, NJ USA
| | | | - Sean Mooney
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA USA
| | | | | | | | | | - Pat Areán
- Department of Psychiatry & Behavioral Sciences, University of Washington, Seattle, WA USA
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Abstract
Brief and culturally compatible measures of depression are necessary, yet most depression scales are translated without regard for cultural biases. In this study, 292 medical outpatients completed an English or a Spanish-translated and back-translated version of the Beck Depression Inventory (BDI). The BDI items were analyzed for bias between Spanish and English-speaking patients to determine the equivalence of the scale. A Differential Item Function (DIF) using a Mantel Haenszel Approach for Ordered Response Categories was used to analyze how likely subjects in the two ethnic groups were to endorse each response category. The results suggest that regardless of level of depression, Latinos are more likely to endorse items reflecting tearfulness and punishment, and less likely to endorse inability to work. Cultural interpretations and recommendations for use of the BDI are discussed.
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Affiliation(s)
- F Azocar
- University of California-San Francisco, San Francisco General Hospital, San Francisco, CA, USA
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