由关系代理 (Woebot) 指导的8周数字心理健康干预的用户参与集群:探索性研究
Valerie Hoffman1, Megan Flom1, Timothy Y Mariano1,2,3
1Woebot Health, Inc., San Francisco, CA, United States.
Journal of medical Internet research
|October 13, 2023
概括
在数字心理健康干预 (DMHI) 中出现了三种用户参与模式. "高效的参与者"显示出更高的弹性和更大的症状减少,突出了用户对人工智能驱动的心理健康支持的多样化参与.
科学领域:
- 数字心理健康干预 (DMHIs) 是指数字心理健康干预.
- 医疗保健中的人工智能
- 计算精神病学是一种计算精神病学.
背景情况:
- 由关系代理指导的数字心理健康干预 (DMHI) 的扩散.
- 对与症状改善相关的行为,认知和情感参与组件的有限理解.
- 需要确定子组和干预机制的最佳使用.
研究的目的:
- 在关系代理引导的DMHI中对参与指标应用聚类.
- 检查用户参与集群的流行率和特征.
- 地图参与干预组件和CAPE模型.
主要方法:
- 在参与数据 (n=202) 上使用聚合层次分类的探索性研究.
- 用户 (18+) Woebot (8周的DMHI) 完成了参与和结果评估.
- 聚类分析了行为,情感,认知参与和工作联盟.
主要成果:
- 确定了3个集群:典型的用户 (40%),早期用户 (29%),和高效的参与者 (31%).
- 有效的参与者具有更高的基线性和更大的抑郁和压力减轻.
- 跨集群存在显著的人口和临床差异.
结论:
- 在DMHI中确定了三个不同的用户参与集群.
- 参与模式与人口统计学,临床特征和心理健康结果相关.
- 需要进一步的研究,以针对DMHI参与和组件做出量身定制的建议.
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