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

Nayra A Martin-Key; Thea S Schei; Eleanor J Barker; Benedetta Spadaro; Erin Funnell; Jiri Benacek; Jakub Tomasik; Sabine Bahn

doi:10.2196/25382

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

JMIR Res Protoc. 2021 Jan 8;10(1):e25382. doi: 10.2196/25382.

Authors

Nayra A Martin-Key^#¹, Thea S Schei^#², Eleanor J Barker³, Benedetta Spadaro¹, Erin Funnell², Jiri Benacek¹, Jakub Tomasik¹, Sabine Bahn¹

Affiliations

¹ Department of Chemical Engineering and Biotechnology, Cambridge Centre for Neuropsychiatric Research, University of Cambridge, Cambridge, United Kingdom.
² Psyomics Ltd, Cambridge, United Kingdom.
³ University of Cambridge Medical Library, University of Cambridge, Cambridge, United Kingdom.

^# Contributed equally.

PMID: 33416508
PMCID: PMC7822724
DOI: 10.2196/25382

Abstract

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

Objective: 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.

Methods: 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.

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

Conclusions: 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.

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

International registered report identifier (irrid): DERR1-10.2196/25382.

Keywords: diagnostic accuracy; digital mental health; digital questionnaire; meta-analysis; psychiatry; systematic review.

©Nayra A Martin-Key, Thea S Schei, Eleanor J Barker, Benedetta Spadaro, Erin Funnell, Jiri Benacek, Jakub Tomasik, Sabine Bahn. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 08.01.2021.