Literature DB >> 33589742

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

Abhishek Pratap1,2, Elias Chaibub Neto3, Phil Snyder3, Carl Stepnowsky4,5, Noémie Elhadad6, Daniel Grant7, Matthew H Mohebbi8, Sean Mooney9, Christine Suver3, John Wilbanks3, Lara Mangravite3, Patrick J Heagerty10, Pat Areán11, Larsson Omberg3.   

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.

Year:  2020        PMID: 33589742     DOI: 10.1038/s41746-020-0224-8

Source DB:  PubMed          Journal:  NPJ Digit Med        ISSN: 2398-6352


  59 in total

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Authors:  Steven R Steinhubl; Evan D Muse; Eric J Topol
Journal:  Sci Transl Med       Date:  2015-04-15       Impact factor: 17.956

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Authors:  Michael Snyder; Wenyu Zhou
Journal:  Lancet Digit Health       Date:  2019-08-29

Review 3.  A systematic review of discontinued trials suggested that most reasons for recruitment failure were preventable.

Authors:  Matthias Briel; Kelechi Kalu Olu; Erik von Elm; Benjamin Kasenda; Reem Alturki; Arnav Agarwal; Neera Bhatnagar; Stefan Schandelmaier
Journal:  J Clin Epidemiol       Date:  2016-08-03       Impact factor: 6.437

4.  The Use of Smartphones for Health Research.

Authors:  E Ray Dorsey; Yu-Feng Yvonne Chan; Michael V McConnell; Stanley Y Shaw; Andrew D Trister; Stephen H Friend
Journal:  Acad Med       Date:  2017-02       Impact factor: 6.893

Review 5.  Mobile Devices and Health.

Authors:  Ida Sim
Journal:  N Engl J Med       Date:  2019-09-05       Impact factor: 91.245

6.  Microplate method for retrovirus-induced transformation of normal human T-cells.

Authors:  K Sugamura; M Sakitani; Y Hinuma
Journal:  J Immunol Methods       Date:  1984-10-26       Impact factor: 2.303

7.  Fluctuating cognition in dementia with Lewy bodies and Alzheimer's disease is qualitatively distinct.

Authors:  J Bradshaw; M Saling; M Hopwood; V Anderson; A Brodtmann
Journal:  J Neurol Neurosurg Psychiatry       Date:  2004-03       Impact factor: 10.154

8.  When there's more than one way to target a cancer.

Authors:  Mike May
Journal:  Nat Med       Date:  2019-08       Impact factor: 53.440

9.  Digital medicine, on its way to being just plain medicine.

Authors:  Steven R Steinhubl; Eric J Topol
Journal:  NPJ Digit Med       Date:  2018-01-15

Review 10.  Use of Mobile Devices to Measure Outcomes in Clinical Research, 2010-2016: A Systematic Literature Review.

Authors:  Brian Perry; Will Herrington; Jennifer C Goldsack; Cheryl A Grandinetti; Kaveeta P Vasisht; Martin J Landray; Lauren Bataille; Robert A DiCicco; Corey Bradley; Ashish Narayan; Elektra J Papadopoulos; Nirav Sheth; Ken Skodacek; Komathi Stem; Theresa V Strong; Marc K Walton; Amy Corneli
Journal:  Digit Biomark       Date:  2018-01-31
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