缓解抑郁和焦虑症状的个性化基于游戏的数字干预:一项试点随机对照试验

Xiaojun Shao, Lu Liu, Xiaotong Zhu, Chunsheng Tian, Dai Li, Liqun Zhang, Xiang Liu, Yanru Liu, Gang Zhu, Lingjiang Li
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引用次数: 0

摘要

本研究评估了基于游戏的数字治疗(DTx)干预抑郁症和焦虑症的初步效果,采用随机对照试验(RCT)设计来检验强化学习(RL)个性化的作用。这项随机对照试验包括223名年龄在18-50岁之间有抑郁症状的个体,分为三组:RL算法组(个性化治疗)、积极对照组(固定治疗)和无干预对照组。干预结合了认知偏差修正和认知行为治疗,结果通过患者健康问卷-9和广泛性焦虑障碍-7进行测量。结果显示,RL算法组的治疗反应和治愈率明显高于无干预组。基于游戏的DTx干预,通过RL个性化增强,有效地减少了抑郁和焦虑症状,支持其心理健康治疗的潜力。该研究已在clinicaltrials.gov注册(NCT06301555)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalized game-based digital intervention for relieving depression and anxiety symptoms: a pilot RCT.

This study assessed the preliminary effectiveness of a game-based digital therapeutics (DTx) intervention for depression and anxiety using a randomized controlled trial (RCT) design to examine the role of reinforcement learning (RL) personalization. This RCT included 223 individuals with depressive symptoms, aged 18-50, divided into three groups: an RL Algorithm group (personalized treatment), an active control group (fixed treatment), and a no-intervention control group. The intervention combined cognitive bias modification and cognitive behavioral therapy, with outcomes measured by the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7. Results showed significantly higher treatment response and recovery rates in the RL Algorithm group compared to the no-intervention group. The game-based DTx intervention, enhanced by RL personalization, effectively reduced depression and anxiety symptoms, supporting its potential for mental health treatment. The study was registered at clinicaltrials.gov (NCT06301555).

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