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Feasibility and outcomes of a multi-function mobile health approach for the schizophrenia spectrum: App4Independence
Sean A Kidd1, Laura Feldcamp2, Amos Adler3
1University of Toronto, Department of Psychiatry, Toronto, Canada.
Abstract:
Relative to the large investments in mobile health (mHealth) strategies for mental illnesses such as anxiety and depression, the development of technology to facilitate illness self-management for people with schizophrenia spectrum illnesses is limited. This situation falls out of step with the opportunity mHealth represents for providing inexpensive and accessible self-care resources and the routine use of mobile technologies by people with schizophrenia. Accordingly, the focus of this study was upon the feasibility of a schizophrenia-focused mobile application: App4Independence (A4i). A4i is a multi-feature app that uses feed, scheduling, and text-based functions co-designed with service users to enhance illness self-management. This study was completed in a large urban Canadian centre and employed pre-post assessments over a 1-month period that examined medication adherence, personal recovery, and psychiatric symptomatology. App use metrics were assessed as was qualitative feedback through semi-structured interview. Findings are reported in line with the World Health Organization mHealth Evidence and Assessment (mERA) checklist. Among the 38 individuals with a primary psychosis who participated, there was no research attrition and classic retention on the app was 52.5%. Significant improvement was observed in some psychiatric symptom domains with small-medium effects. Significant change in recovery engagement and medication adherence were not observed after controlling for multiple comparisons. Those who interacted with the app more frequently were more depressed and had higher hostility and interpersonal sensitivity at baseline. Satisfaction with the app was high and qualitative feedback provided insights regarding feature enhancements. This research suggested that A4i is feasible in terms of outcome and process indicators and is a technology that is ready to move on to clinical trial and validation testing. This study contributes to the small but emergent body of work investigating digital health approaches in severe mental illness populations.
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