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Characteristics and Outcomes of mHealth Interventions in Psychosis: Systematic Mapping Review
Pei Yi Loh1, Laura Martinengo1,2, Creighton Heaukulani3
1Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Journal of Medical Internet Research
|December 23, 2024
Summary
Mobile health (mHealth) interventions for psychosis show diverse outcomes. A holistic evaluation combining clinical and patient-centered results is recommended for complex mHealth interventions.
Area of Science:
- Psychiatry
- Digital Health
- Mental Health Technology
Background:
- Mobile health (mHealth) interventions are increasingly used in psychiatric care for adults with psychosis.
- There is growing interest in using mHealth to support individuals with severe mental illness in community settings.
- However, mixed outcomes reported in studies hinder direct comparisons due to variations in interventions and outcome measures.
Purpose of the Study:
- To critically review the outcome measures used in evaluating mHealth interventions for adults with psychosis.
- To analyze the relationship between outcome measures and the characteristics of mHealth interventions.
Main Methods:
- A systematic mapping review was conducted, searching major scientific databases (PubMed, CINAHL, Embase, PsycINFO, Cochrane Libraries) from 1973 to the present.
- Included studies were randomized controlled trials (RCTs) of mHealth interventions for adults with schizophrenia spectrum disorders.
- Data extraction and screening were performed independently by pairs of reviewers, adhering to PRISMA-ScR guidelines.
Main Results:
- 23 studies were included, revealing a wide range of mHealth interventions, primarily psychological therapy, psychoeducation, and self-monitoring, often delivered via smartphone applications.
- Interventions frequently targeted multiple biopsychosocial well-being aspects and promoted self-management, mainly in outpatient/community settings, often blended with in-person or remote support.
- The most common outcome measured was psychosis symptom severity (positive symptoms, mood/anxiety, overall psychopathology), alongside patient-centric outcomes like well-being, quality of life, and user experience (feasibility, acceptability, engagement).
Conclusions:
- mHealth interventions for psychosis are complex, utilizing diverse modalities and outcome measures addressing various health determinants.
- A holistic evaluation approach is recommended, integrating both clinical and patient-centric outcomes for a comprehensive assessment.
- Standardizing outcome measures could improve comparability and understanding of mHealth effectiveness in psychosis care.
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