在被动感知家庭寄宿的早期变化预测在数字行为激活期间抑郁症症状的改善
Carter J Funkhouser1, Lauren S Weiner2, Ryann N Crowley3
1Department of Psychiatry, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA.
Behaviour research and therapy
|July 4, 2025
概括
在抑郁症的数字行为激活 (BA) 期间,智能手机传感器测量了在家花费时间的早期减少,预测了更大的症状减少. 这一发现有助于识别不响应者,以便及时进行治疗调整.
科学领域:
- 数字心理健康数字心理健康
- 临床心理学 临床心理学
- 行为科学是一种行为科学.
背景情况:
- 数字行为激活 (BA) 是一种有效的,可扩展的抑郁症干预措施.
- 早期识别那些不响应数字BA的个体对于适应性治疗至关重要.
- 被动感应为早期预测治疗反应提供了潜在的潜力.
研究的目的:
- 为了调查被动感知行为的早期变化是否预测应用程序为基础的BA期间抑郁症症状变化.
- 确定智能手机传感器数据是否可以识别可能从数字BA中受益的个人.
主要方法:
- 47名患有抑郁症状的年轻人使用Vira应用程序12周.
- 该应用程序通过智能手机传感器提供了BA,评估了情绪,并通过智能手机传感器被动感知了行为 (例如,住宿,走路).
- 模拟了早期的行为变化 (前2周),并测试了它们对抑郁症症状减少 (PHQ-8) 的预测能力.
主要成果:
- 在被动感知在家度过的时间 (家庭住宿) 的较大早期减少显著预测了更大的抑郁症症状减少.
- 其他被动感知行为的早期变化没有预测症状变化.
- 这些发现支持这样一个假设:行为变化可以预测治疗结果.
结论:
- 在基于应用程序的BA期间,被动监测家庭住宿的早期变化可以帮助识别有症状持续风险的个人.
- 这种监测可能有助于在分步护理模式中更早地调整干预措施.
- 被动传感在数字心理健康干预中提供客观的,早期的治疗反应指标.
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