Acceptability of Digital Mental Health Interventions for Depression and Anxiety: Systematic Review.

Autor:	Lau CKY; Department of Psychiatry, Women's College Hospital, Toronto, ON, Canada.; Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada., Saad A; Department of Psychiatry, Women's College Hospital, Toronto, ON, Canada., Camara B; Department of Immunology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada., Rahman D, Bolea-Alamanac B; Department of Psychiatry, Women's College Hospital, Toronto, ON, Canada.; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
Jazyk:	angličtina
Zdroj:	Journal of medical Internet research [J Med Internet Res] 2024 Oct 28; Vol. 26, pp. e52609. Date of Electronic Publication: 2024 Oct 28.
DOI:	10.2196/52609
Abstrakt:	Background: Depression and anxiety disorders are common, and treatment often includes psychological interventions. Digital health interventions, delivered through technologies such as web-based programs and mobile apps, are increasingly used in mental health treatment. Acceptability, the extent to which an intervention is viewed positively, has been identified as contributing to patient adherence and engagement with digital health interventions. Acceptability, therefore, impacts the benefit derived from using digital health interventions in treatment. Understanding the acceptability of digital mental health interventions among patients with depression or anxiety disorders is essential to maximize the effectiveness of their treatment. Objective: This review investigated the acceptability of technology-based interventions among patients with depression or anxiety disorders. Methods: A systematic review was performed based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines. We searched PubMed, Web of Science, and Ovid in May 2022. Studies were included if they evaluated digital interventions for the treatment of depression or anxiety disorders and investigated their acceptability among adult patients. Studies were excluded if they targeted only specific populations (eg, those with specific physical health conditions), investigated acceptability in healthy individuals or patients under the age of 18 years, involved no direct interaction between patients and technologies, used technology only as a platform for traditional care (eg, videoconferencing), had patients using technologies only in clinical or laboratory settings, or involved virtual reality technologies. Acceptability outcome data were narratively synthesized by the direction of acceptability using vote counting. Included studies were evaluated using levels of evidence from the Oxford Centre for Evidence-Based Medicine. The risk of bias was assessed using a tool designed for this review and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Results: A total of 143 articles met the inclusion criteria, comprising 67 (47%) articles on interventions for depression, 65 (45%) articles on interventions for anxiety disorders, and 11 (8%) articles on interventions for both. Overall, 90 (63%) were randomized controlled trials, 50 (35%) were other quantitative studies, and 3 (2%) were qualitative studies. Interventions used web-based programs, mobile apps, and computer programs. Cognitive behavioral therapy was the basis of 71% (102/143) of the interventions. Digital mental health interventions were generally acceptable among patients with depression or anxiety disorders, with 88% (126/143) indicating positive acceptability, 8% (11/143) mixed results, and 4% (6/143) insufficient information to categorize the direction of acceptability. The available research evidence was of moderate quality. Conclusions: Digital mental health interventions seem to be acceptable to patients with depression or anxiety disorders. Consistent use of validated measures for acceptability would enhance the quality of evidence. Careful design of acceptability as an evaluation outcome can further improve the quality of evidence and reduce the risk of bias. Trial Registration: Open Science Framework Y7MJ4; https://doi.org/10.17605/OSF.IO/SPR8M. (©Carrie K Y Lau, Anthony Saad, Bettina Camara, Dia Rahman, Blanca Bolea-Alamanac. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.10.2024.)
Databáze:	MEDLINE
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