从智能手机数据到临床相关预测:对抑郁症的数字表型化方法的系统审查
Imogen E Leaning1, Nessa Ikani2, Hannah S Savage1
1Donders Institute for Brain, Cognition and Behaviour Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands.
Neuroscience and biobehavioral reviews
|January 12, 2024
概括
智能手机数字表型显示出对主要抑郁症 (MDD) 监测的前景. 目前的方法面临着数据复杂性和验证方面的挑战,但时间分析可能会改善患者监测.
科学领域:
- 数字健康数字健康
- 心理健康技术 心理健康技术
- 计算精神病学是一种计算精神病学.
背景情况:
- 基于智能手机的数字表型为收集真实世界的数据提供了一种新的方法,以监测患有重大抑郁障碍 (MDD) 的人.
- 这项技术有可能增强临床监测,并为MDD提供干预信息.
- 本系统性审查审查了在MDD研究中使用的当前数字表型特征和方法.
结论:
- 虽然在将数字表型与MDD的临床变量联系起来方面取得了进展,但许多研究都专注于时间平均特征.
- 未来的研究应该探索更直接研究时间动态的方法,以改善患者监测.
- 这些发现强调了在心理健康的数字表型化中需要强有力的验证和先进的分析技术.
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