在精神分裂症谱系障碍中诊断数字表型:系统性审查
Ivan Vecchio1, Lucas Mifsud1, Sofia Castro E Almeida1
1Institute of Systems Neuroscience, Medical University of Innsbruck, Innsbruck, Austria.
NPJ digital medicine
|December 1, 2025
概括
数字表型显示出对精神分裂症谱系障碍 (SSD) 评估的潜力,特别是在认知表现和行为方面. 然而,显著的异质性和需要标准化,多式联运的方法是显而易见的,可靠的诊断和预测.
科学领域:
- 数字健康数字健康
- 精神病学是一个精神病学.
- 计算神经科学是一种计算神经科学.
背景情况:
- 数字表型化为评估精神分裂症谱系障碍 (SSD) 提供了新的方法.
- 目前的方法是异质的,需要对其诊断和预测实用性的全面审查.
研究的目的:
- 系统地审查和分析SSD中的数字表型的诊断和预测价值.
- 确定最有效的数字化措施,并突出未来研究领域.
主要方法:
- 按照PRISMA指南进行系统审查.
- 来自142项同行评审研究 (2004-2024) 的数据综合,涉及6294名参与者.
- 分析基于智能手机和可穿戴设备的数据,包括主动和被动传感方法.
主要成果:
- 认知表现显示了区分SSD的最大效果大小 (g≈1.20),其次是行为/活动 (g≈0.62),尽管两者都有很高的异质性 (I2>70%).
- 智能手机和可穿戴传感器占主导地位;只有约20%的研究使用了主动/被动组合方法.
- 复发预测模型显示有希望 (AUC高达0.8),但缺乏标准化;与PANSS的相关性有限.
结论:
- 数字表型,特别是认知和行为测量,对SSD评估具有潜力.
- 迫切需要标准化报告,多式联运数据集成和各种纵向研究,以提高SSD的诊断和预测准确性.
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