使用实时智能手机监控预测一周的自杀风险:前性队列研究
Maria Luisa Barrigon1,2, Lorena Romero-Medrano3,4, Pablo Moreno-Muñoz3,5
1Department of Psychiatry, Jimenez Diaz Foundation University Hospital, Madrid, Spain.
Journal of medical Internet research
|September 1, 2023
概括
智能手机数据可以提前一周预测自杀风险. 这项研究使用了被动智能手机监控来识别有自杀想法的人的行为变化,为预防自杀提供了一个新的工具.
科学领域:
- 数字精神病学数字精神病学
- 计算精神病学是一种计算精神病学.
- 公共卫生技术 公共卫生技术
背景情况:
- 自杀是一个重要的全球健康问题,其流行率正在增加.
- 现有的自杀风险预测方法缺乏足够的准确性.
- 技术进步为个性化,预测性自杀风险评估提供了潜力.
研究的目的:
- 预测短期 (1周) 自杀风险.
- 用实时智能手机监控来识别行为模式的变化.
- 分析来自有自杀念头的患者的数据.
主要方法:
- 招募了225名有自杀想法/行为史的患者参加SmartCrisis研究.
- 收集了6个月的关于自杀风险和心理健康危机的随访数据.
- 使用被动智能手机监控 (活动,应用程序使用) 来创建每日个人资料并检测变化.
主要成果:
- 该算法识别了行为变化,预测了1周内自杀风险.
- 预测准确度是由0.78.8的曲线下的面积表示的.
- 在随访期间,8%的参与者试图自杀,6.2%的人寻求精神病紧急护理.
结论:
- 介绍了一种创新方法,使用被动收集的智能手机数据来识别心理健康危机.
- 这项技术在患者队伍中识别不同类型的危机方面具有潜在的应用.
- 被动智能手机监控为心理健康危机检测提供了一种新的方法.
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