JMIR Publications

ABSTRACT

Background:

Mobile health (mHealth) interventions have gained popularity in augmenting psychiatric care for adults with psychosis. Interest has grown in leveraging mHealth to empower individuals living with severe mental illness and extend continuity of care beyond hospital to community. However, reported outcomes have been mixed, likely attributed in part to the intervention and adopted outcomes, which affected between-study comparisons.

Objective:

To critically review outcome measures used to evaluate mHealth interventions for adults with psychosis, in relation to mHealth intervention characteristics.

Methods:

A systematic mapping review was conducted. We searched PubMed, CINAHL, Embase, PsycINFO and Cochrane Libraries from 1973 to present. Selection criteria included randomized controlled studies of mHealth interventions in adults diagnosed with schizophrenia spectrum disorders. Reviewers worked in pairs to screen and extract data from included studies independently using a standardized form; disagreements were resolved by consensus with an independent reviewer. We report our findings in line with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines.

Results:

1703 citations were screened; 29 publications reporting on 23 studies were included in this review. mHealth interventions for psychosis span a wide range with psychological therapy being the most-deployed intervention (12/23, 52%) followed by psychoeducation (8/23, 35%) and active self-monitoring (8/23, 35%). Several mHealth interventions for psychosis targeted multiple pillars of biopsychosocial wellbeing (10/23, 43%); the bulk of interventions (16/23, 70%) incorporated features promoting users’ self-management. The majority of mHealth interventions were delivered through applications (14/23, 61%) as the main medium and smartphones (17/23, 74%) as the main channel of delivery. Interventions were primarily administered in the outpatient and community settings (16/23, 70%); many were also blended with in-person sessions (11/23, 48%) or guided remotely (6/23, 26%) by persons including healthcare providers or trained peer supporters. Severity of psychosis-related symptoms (21/23, 91%) was the most prevalent outcome; of which, positive symptoms (13/23, 57%), mood and anxiety (10/23, 43%) and overall psychopathology severity (9/23, 39%) were most commonly measured. Patient-centric outcomes including well-being (17/23, 74%) – particularly quality of life (10/23, 43%) – and user experience (15/23, 65%) including feasibility (7/23, 30%), acceptability (7/23, 30%), and engagement (7/23, 26%). Notably, outcome choices remained diverse despite stratification by type of mHealth intervention.

Conclusions:

mHealth interventions for psychosis encompass a wide range of modalities and employed outcome measures that probe various social and behavioral determinants of health. These should be considered complex interventions in the digital mental health scene and a holistic evaluation approach combining clinical and patient-centric outcomes is recommended.