Personalisation and recommendation for mental health apps: A scoping review

Matthews, Paul; Rhodes-Maquaire, Clemence

Abstract

Personalisation, which tailors to individual preferences, is considered a possible route for improving engagement with digital mental health (DMH) products. Despite claims about the presence and importance of personalised features, evidence about their extent and impact is limited. The study objective was to review evidence from published research to investigate and characterise the contribution of personalisation to engagement and effectiveness. Research papers were retrieved using keywords, with 139 papers being fully examined and 61 meeting our eligibility criteria. Most of the eligible articles reviewing DMH systems have weak to intermediate forms of personalisation (45). Only nine were coded as having strong, adaptive personalisation. Of the 40 articles which evaluated the personalisation effectiveness, 28 were qualitative indicating user preference for personalised features. The 16 controlled, quantitative designs lacked a non-personalised intervention, making it difficult to determine the added value. Effect sizes calculated from available data showed minimal differences in effectiveness compared to non-personalised apps. Our review indicates mixed evidence of personalisation’s performance in DMH interventions. Generally, there is a lack of good quality evidence to isolate specific contributions of personalisation. Opportunities were identified for improved evaluation, however caution is required when implementing more sophisticated methods of DMH personalisation.

Citation

Matthews, P., & Rhodes-Maquaire, C. (in press). Personalisation and recommendation for mental health apps: A scoping review. Behaviour and Information Technology, https://doi.org/10.1080/0144929x.2024.2356630

• Journal Article Type: Article
• Acceptance Date: Apr 28, 2024
• Online Publication Date: May 27, 2024
• Deposit Date: Jun 4, 2024
• Publicly Available Date: Jun 5, 2024
• Journal: Behaviour & Information Technology
• Print ISSN: 0144-929X
• Electronic ISSN: 1362-3001
• Publisher: Taylor & Francis
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1080/0144929x.2024.2356630
• Public URL: https://uwe-repository.worktribe.com/output/12034334
• Additional Information: Peer Review Statement: The publishing and review policy for this title is described in its Aims & Scope.; Aim & Scope: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tbit20; Received: 2023-05-29; Accepted: 2024-04-28; Published: 2024-05-27