The Current State and Diagnostic Accuracy of Digital Mental Health Assessment Tools for Psychiatric Disorders: Protocol for a Systematic Review and Meta-analysis (Preprint)

Abstract

Despite the rapidly growing number of digital assessment tools for screening and diagnosing mental health disorders, little is known about their diagnostic accuracy.

The purpose of this systematic review and meta-analysis is to establish the diagnostic accuracy of question- and answer-based digital assessment tools for diagnosing a range of highly prevalent psychiatric conditions in the adult population.

The Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) will be used. The focus of the systematic review is guided by the population, intervention, comparator, and outcome framework (PICO). We will conduct a comprehensive systematic literature search of MEDLINE, PsychINFO, Embase, Web of Science Core Collection, Cochrane Library, Applied Social Sciences Index and Abstracts (ASSIA), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) for appropriate articles published from January 1, 2005. Two authors will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any inconsistencies will be discussed and resolved. The two authors will then extract data into a standardized form. Risk of bias will be assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, and a descriptive analysis and meta-analysis will summarize the diagnostic accuracy of the identified digital assessment tools.

The systematic review and meta-analysis commenced in November 2020, with findings expected by May 2021.

This systematic review and meta-analysis will summarize the diagnostic accuracy of question- and answer-based digital assessment tools. It will identify implications for clinical practice, areas for improvement, and directions for future research.

PROSPERO International Prospective Register of Systematic Reviews CRD42020214724; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020214724.

DERR1-10.2196/25382