Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments

Rapid proliferation of mental health interventions delivered through conversational agents (CAs) calls for high-quality evidence to support their implementation and adoption. Selecting appropriate outcomes, instruments for measuring outcomes, and assessment methods are crucial for ensuring that inte...

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Vydáno v:Journal of medical Internet research Ročník 25; číslo 9; s. e44548
Hlavní autoři: Jabir, Ahmad Ishqi, Martinengo, Laura, Lin, Xiaowen, Torous, John, Subramaniam, Mythily, Tudor Car, Lorainne
Médium: Journal Article
Jazyk:angličtina
Vydáno: Canada Journal of Medical Internet Research 19.04.2023
Gunther Eysenbach MD MPH, Associate Professor
JMIR Publications
Témata:
Analysis
Artificial intelligence
Clinical assessment
Clinical outcomes
Cognition & reasoning
Communication
Computational linguistics
Conversation
Data collection
Evaluation
Extraction
Health promotion
Health status
Human-computer interaction
Humans
Intervention
Language processing
Literature reviews
Measurement
Measures
Measuring instruments
Medical screening
Mental disorders
Mental Health
Mental health services
Multimedia
Natural language interfaces
Outcome Assessment, Health Care
Performance evaluation
Post traumatic stress disorder
Psychological assessment
Quality of life
Review
Self evaluation
Sensors
Smartphones
Systematic review
Taxonomy
Telemedicine
Treatment outcomes
Usability
User experience
Validity
Well being
chatbot
mobile health
outcomes
mental health
mHealth
core outcome set
taxonomy
conversational agent
ISSN:1438-8871, 1439-4456, 1438-8871
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Shrnutí:Rapid proliferation of mental health interventions delivered through conversational agents (CAs) calls for high-quality evidence to support their implementation and adoption. Selecting appropriate outcomes, instruments for measuring outcomes, and assessment methods are crucial for ensuring that interventions are evaluated effectively and with a high level of quality. We aimed to identify the types of outcomes, outcome measurement instruments, and assessment methods used to assess the clinical, user experience, and technical outcomes in studies that evaluated the effectiveness of CA interventions for mental health. We undertook a scoping review of the relevant literature to review the types of outcomes, outcome measurement instruments, and assessment methods in studies that evaluated the effectiveness of CA interventions for mental health. We performed a comprehensive search of electronic databases, including PubMed, Cochrane Central Register of Controlled Trials, Embase (Ovid), PsychINFO, and Web of Science, as well as Google Scholar and Google. We included experimental studies evaluating CA mental health interventions. The screening and data extraction were performed independently by 2 review authors in parallel. Descriptive and thematic analyses of the findings were performed. We included 32 studies that targeted the promotion of mental well-being (17/32, 53%) and the treatment and monitoring of mental health symptoms (21/32, 66%). The studies reported 203 outcome measurement instruments used to measure clinical outcomes (123/203, 60.6%), user experience outcomes (75/203, 36.9%), technical outcomes (2/203, 1.0%), and other outcomes (3/203, 1.5%). Most of the outcome measurement instruments were used in only 1 study (150/203, 73.9%) and were self-reported questionnaires (170/203, 83.7%), and most were delivered electronically via survey platforms (61/203, 30.0%). No validity evidence was cited for more than half of the outcome measurement instruments (107/203, 52.7%), which were largely created or adapted for the study in which they were used (95/107, 88.8%). The diversity of outcomes and the choice of outcome measurement instruments employed in studies on CAs for mental health point to the need for an established minimum core outcome set and greater use of validated instruments. Future studies should also capitalize on the affordances made available by CAs and smartphones to streamline the evaluation and reduce participants' input burden inherent to self-reporting.
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ISSN:1438-8871
1439-4456
1438-8871
DOI:10.2196/44548