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远程数字健康研究中的留存指标:对10万名参与者的跨研究评估

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

作者信息

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

机构信息

1Sage Bionetworks, Seattle, WA USA.

2Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA USA.

出版信息

NPJ Digit Med. 2020 Feb 17;3:21. doi: 10.1038/s41746-020-0224-8. eCollection 2020.

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.

摘要

智能手机等数字技术正在改变科学家进行生物医学研究的方式。几项远程进行的研究在短短几个月内招募了数千名参与者,使研究人员能够大规模收集真实世界的数据,且成本仅为传统研究的一小部分。不幸的是,远程研究受到了大量参与者流失的阻碍,这使得所收集数据的代表性,包括结果的可推广性受到质疑。我们报告了2014年至2019年间进行的八项远程数字健康研究中关于招募和留存的结果,这些研究提供了来自10万多名参与者的个人层面的研究应用程序使用数据,他们累计参与85万天,完成了近350万次远程健康评估。八项研究中参与者留存时间的中位数差异很大,从2天到26天不等(所有研究的中位数为5.5天)。生存分析揭示了几个与参与者留存时间增加显著相关的因素,包括:(i)临床医生将患者推荐至该研究(中位数留存时间增加40天);(ii)参与研究获得补偿(增加22天,一项研究);(iii)患有研究中关注的临床疾病(与对照组相比增加7天);以及(iv)年龄较大(增加4天)。此外,通过无监督聚类识别出了四种不同的每日应用程序使用行为模式,这些模式也与参与者的人口统计学特征相关。大多数研究未能招募到能够代表美国种族/族裔或地域多样性的样本。这些研究结果共同有助于为招募和留存策略提供信息,以使未来数字健康研究中的人群能够公平参与。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb0d/7026051/d206496394fa/41746_2020_224_Fig1_HTML.jpg

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