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自动在线每月抑郁再筛查项目中的参与者留存情况:模式与预测因素

Participant retention in an automated online monthly depression rescreening program: patterns and predictors.

作者信息

Gill Supria, Contreras Omar, Muñoz Ricardo F, Leykin Yan

机构信息

Palo Alto University, San Francisco.

University of California, San Francisco.

出版信息

Internet Interv. 2014 Mar;1(1):20-25. doi: 10.1016/j.invent.2014.02.003.

Abstract

Internet-based mental health resources often suffer from low engagement and retention. An increased understanding of engagement and attrition is needed to realize the potential of such resources. In this study, 45,142 individuals were screened for depression by an automated online screener, with 2,539 enrolling in a year-long monthly rescreening study; they received a single monthly reminder email to rescreen their mood. We found that, even with such a minimal cohort maintenance strategy, a third of the participants completed 1 or more follow-ups, and 22% completed 2 or more follow-ups. Furthermore, completion of earlier follow-ups was highly predictive of future completions. We also found a number of participant characteristics (e.g., current depression status, previous depression treatment seeking, education level) predicted follow-up rates, singly or in interactions.

摘要

基于互联网的心理健康资源往往存在参与度和留存率较低的问题。为了发挥此类资源的潜力,需要对参与度和损耗情况有更深入的了解。在本研究中,通过自动化在线筛查工具对45142人进行了抑郁症筛查,其中2539人参加了为期一年的月度重新筛查研究;他们每月收到一封提醒邮件,用于重新筛查自己的情绪。我们发现,即使采用这种极为简单的队列维持策略,仍有三分之一的参与者完成了1次或更多次随访,22%的参与者完成了2次或更多次随访。此外,较早完成随访对未来完成随访具有很强的预测性。我们还发现,一些参与者特征(如当前抑郁状态、既往寻求抑郁症治疗情况、教育水平)单独或相互作用时可预测随访率。

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