Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
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DOI：
10.1038/s41746-020-0224-8
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发表时间：
2020-02-17
影响因子：
15.2
通讯作者：
Omberg, Larsson
中科院分区：
文献类型：
--
作者：
Pratap, Abhishek;Neto, Elias Chaibub;Omberg, Larsson
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。几个远程进行的研究在几个月的时间里招募了数千名参与者，使研究人员能够以传统研究的一小部分成本，大规模收集真实世界的数据。不幸的是，远程研究因参与者大量流失而受到阻碍，这使收集的数据的代表性受到质疑，包括结果的概括性。我们报告了2014-2019年间进行的八项远程数字健康研究的结果，这些研究提供了超过10万名参与者的个人级别研究应用使用数据，在累计参与850,000天的时间内完成了近350万次远程健康评估。八项研究的参与者保留中位数差异很大，从2-26天不等(所有研究的中位数为5.5天)。生存分析表明，有几个因素与参与者保留时间的增加显著相关，包括(I)临床医生转介到研究中(中位保留时间增加40天)；(Ii)参与的补偿(增加22天，1个研究)；(Iii)具有研究中感兴趣的临床条件(与对照组相比增加7天)；以及(Iv)高龄(增加4天)。此外，通过非监督聚类确定了四种不同的日常应用程序使用行为模式，这也与参与者的人口统计相关联。大多数研究未能招募到代表美国种族/民族或地理多样性的样本。总而言之，这些发现可以帮助制定招募和保留战略，使人们能够公平地参与未来的数字健康研究。
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.