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Persuasive Systems Design Features of Smartphone Apps for Psychosis: Systematic Review
Theresa Taylor1, Jasmin Peat1, David Kell1
1Department of Psychology, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom, +44 1225 383843.
JMIR Human Factors
|May 7, 2026
Summary
This review found that smartphone apps for psychosis often use personalization and reminders but lack social support and credibility features. Increasing persuasive features may enhance user engagement in mental health apps.
Area of Science:
- Digital Health
- Mental Health Technology
- Psychosis Management
Background:
- Engagement in smartphone apps for psychosis varies, with persuasive features potentially explaining differences.
- Understanding the role of persuasive features is crucial for developing effective digital mental health tools.
Purpose of the Study:
- To systematically review persuasive features in smartphone apps for psychosis.
- To examine the association between persuasive features and user attrition or adherence.
- To assess the quality of included psychosis apps.
Main Methods:
- Systematic search of PsycINFO, PubMed, and Google Scholar (2013-2025).
- Inclusion of apps designed for psychosis with published empirical studies.
- Data extraction on adherence, attrition, and coding of persuasive features using the Persuasive Systems Design (PSD) model.
Main Results:
- 22 psychosis apps were identified, utilizing features like personalization (18 apps) and reminders (15 apps).
- Social support and system credibility features were underused.
- No association found between the number of persuasive features and attrition; adherence association could not be assessed.
- App quality assessment was hindered by the inaccessibility of most apps.
Conclusions:
- Psychosis apps could enhance engagement by incorporating a wider range of persuasive features, particularly social support and system credibility.
- Further research is needed to determine the impact of increased persuasive features on app engagement and identify the most effective features.
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