Xiaojun Shao, Lu Liu, Xiaotong Zhu, Chunsheng Tian, Dai Li, Liqun Zhang, Xiang Liu, Yanru Liu, Gang Zhu, Lingjiang Li
{"title":"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","authors":"Xiaojun Shao, Lu Liu, Xiaotong Zhu, Chunsheng Tian, Dai Li, Liqun Zhang, Xiang Liu, Yanru Liu, Gang Zhu, Lingjiang Li","doi":"10.1038/s44184-025-00141-x","DOIUrl":null,"url":null,"abstract":"<p><p>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).</p>","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"27"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229681/pdf/","citationCount":"0","resultStr":"{\"title\":\"Personalized game-based digital intervention for relieving depression and anxiety symptoms: a pilot RCT.\",\"authors\":\"Xiaojun Shao, Lu Liu, Xiaotong Zhu, Chunsheng Tian, Dai Li, Liqun Zhang, Xiang Liu, Yanru Liu, Gang Zhu, Lingjiang Li\",\"doi\":\"10.1038/s44184-025-00141-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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).</p>\",\"PeriodicalId\":74321,\"journal\":{\"name\":\"Npj mental health research\",\"volume\":\"4 1\",\"pages\":\"27\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229681/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Npj mental health research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s44184-025-00141-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Npj mental health research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s44184-025-00141-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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).