坚持公开可用的自导数字心理健康干预措施的预测因素
Mercedes G Woolley1, Korena S Klimczak1, Carter H Davis1
1Department of Psychology, Utah State University, Logan, USA.
很少有用户完成自我指导的数字心理健康干预 (DMHI). 年轻的用户,轻度抑郁症患者,以及对心理健康护理新手的个人,对这些数字心理健康计划的坚持更好.
科学领域:
- 数字心理健康干预数字心理健康干预
- 心理健康研究 心理健康研究
- 用户坚持研究的研究.
背景情况:
- 对自导数字心理健康干预措施 (DMHI) 的低坚持挑战了它们在现实世界的有效性.
- 对DMHIs的自然主义用户数据很少,这限制了遵守评估.
- 了解遵守对于优化数字心理健康解决方案至关重要.
研究的目的:
- 为了分析3年的用户数据,从一个公开启动,12个会话的自动引导DMHI.
- 为了确定整体程序的坚持率.
- 在现实环境中识别坚持的预测因素.
主要方法:
- 从公开可用的DMHI中分析了984名注册用户的数据.
- 评估12个课程课程中的模块完成率.
- 用户特征的统计探索,预测用户的坚持.
主要成果:
- 只有14.8%的用户完成了所有12个模块;68.6%完成了不到一半.
- 年轻的使用者,轻度抑郁症患者和对心理健康护理新手的个人表现出更高的坚持.
- 拒绝每周电子邮件更新与增加模块完成相关.
结论:
- 在现实世界中,对自我引导的DMHIs的坚持明显低于对照试验.
- 用户数据分析可以识别坚持预测因素,并告知干预个性化.
- 研究结果表明,定制DMHIs可能会提高特定用户群体的参与度.
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