Martin-Key Nayra A, Spadaro Benedetta, Funnell Erin, Barker Eleanor Jane, Schei Thea Sofie, Tomasik Jakub, Bahn Sabine
Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.
University of Cambridge Medical Library, University of Cambridge, Cambridge, United Kingdom.
JMIR Ment Health. 2022 Mar 30;9(3):e32824. doi: 10.2196/32824.
Given the role digital technologies are likely to play in the future of mental health care, there is a need for a comprehensive appraisal of the current state and validity (ie, screening or diagnostic accuracy) of digital mental health assessments.
The aim of this review is to explore the current state and validity of question-and-answer-based digital tools for diagnosing and screening psychiatric conditions in adults.
This systematic review was based on the Population, Intervention, Comparison, and Outcome framework and was carried out in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, Embase, Cochrane Library, ASSIA, Web of Science Core Collection, CINAHL, and PsycINFO were systematically searched for articles published between 2005 and 2021. A descriptive evaluation of the study characteristics and digital solutions and a quantitative appraisal of the screening or diagnostic accuracy of the included tools were conducted. Risk of bias and applicability were assessed using the revised tool for the Quality Assessment of Diagnostic Accuracy Studies 2.
A total of 28 studies met the inclusion criteria, with the most frequently evaluated conditions encompassing generalized anxiety disorder, major depressive disorder, and any depressive disorder. Most of the studies used digitized versions of existing pen-and-paper questionnaires, with findings revealing poor to excellent screening or diagnostic accuracy (sensitivity=0.32-1.00, specificity=0.37-1.00, area under the receiver operating characteristic curve=0.57-0.98) and a high risk of bias for most of the included studies.
The field of digital mental health tools is in its early stages, and high-quality evidence is lacking.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/25382.
鉴于数字技术在未来精神卫生保健中可能发挥的作用，有必要对数字心理健康评估的现状和有效性（即筛查或诊断准确性）进行全面评估。
本综述旨在探讨基于问答的数字工具在诊断和筛查成人精神疾病方面的现状和有效性。
本系统综述基于人群、干预措施、对照和结局框架，并按照PRISMA（系统评价和Meta分析的首选报告项目）指南进行。对MEDLINE、Embase、Cochrane图书馆、ASSIA、科学引文索引核心合集、护理学与健康领域数据库和心理学文摘数据库进行系统检索，以查找2005年至2021年期间发表的文章。对研究特征和数字解决方案进行描述性评估，并对纳入工具的筛查或诊断准确性进行定量评估。使用修订后的诊断准确性研究质量评估工具2评估偏倚风险和适用性。
共有28项研究符合纳入标准，评估最频繁的疾病包括广泛性焦虑障碍、重度抑郁症和任何抑郁症。大多数研究使用现有纸质问卷的数字化版本，结果显示筛查或诊断准确性从差到优（灵敏度=0.32-1.00，特异度=0.37-1.00，受试者工作特征曲线下面积=0.57-0.98），且大多数纳入研究存在较高的偏倚风险。
数字心理健康工具领域尚处于早期阶段，缺乏高质量证据。
国际注册报告识别号（IRRID）：RR2-10.2196/25382。
