Quality and Methodological Challenges in Internet-Based Mental Health Trials

作者
Xibiao Ye,Sunita Bayyavarapu Bapuji,Shannon Winters,Colleen Metge,Melissa Raynard
出处
期刊:Telemedicine Journal and E-health [Mary Ann Liebert, Inc.]
卷期号:20 (8): 744-747 被引量:3
标识
DOI:10.1089/tmj.2013.0298
摘要

OBJECTIVE: To review the quality of Internet-based mental health intervention studies and their methodological challenges. MATERIALS AND METHODS: We searched multiple literature databases to identify relevant studies according to the Population, Interventions, Comparators, Outcomes, and Study Design framework. Two reviewers independently assessed selection bias, allocation bias, confounding bias, blinding, data collection methods, and withdrawals/dropouts, using the Quality Assessment Tool for Quantitative Studies. We rated each component as strong, moderate, or weak and assigned a global rating (strong, moderate, or weak) to each study. We discussed methodological issues related to the study quality. RESULTS: Of 122 studies included, 31 (25%), 44 (36%), and 47 (39%) were rated strong, moderate, and weak, respectively. Only five studies were rated strong for all of the six quality components (three of them were published by the same group). Lack of blinding, selection bias, and low adherence were the top three challenges in Internet-based mental health intervention studies. CONCLUSIONS: The overall quality of Internet-based mental health intervention needs to improve. In particular, studies need to improve sample selection, intervention allocation, and blinding.

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