Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study

Nur Amirah Abdul Rashid, Wijaya Martanto, Zixu Yang, Xuancong Wang, Creighton Heaukulani, Nikola Vouk, Thisum Buddhika, Yuan Wei, Swapna Verma, Charmaine Tang, Robert J T Morris, Jimmy Lee, Nur Amirah Abdul Rashid, Wijaya Martanto, Zixu Yang, Xuancong Wang, Creighton Heaukulani, Nikola Vouk, Thisum Buddhika, Yuan Wei, Swapna Verma, Charmaine Tang, Robert J T Morris, Jimmy Lee

Abstract

Introduction: The course of schizophrenia illness is characterised by recurrent relapses which are associated with adverse clinical outcomes such as treatment-resistance, functional and cognitive decline. Early identification is essential and relapse prevention remains a primary treatment goal for long-term management of schizophrenia. With the ubiquity of devices such as smartphones, objective digital biomarkers can be harnessed and may offer alternative means for symptom monitoring and relapse prediction. The acceptability of digital sensors (smartphone and wrist-wearable device) and the association between the captured digital data with clinical and health outcomes in individuals with schizophrenia will be examined.

Methods and analysis: In this study, we aim to recruit 100 individuals with schizophrenia spectrum disorders who are recently discharged from the Institute of Mental Health (IMH), Singapore. Participants are followed up for 6 months, where digital, clinical, cognitive and functioning data are collected while health utilisation data are obtained at the 6 month and 1 year timepoint from study enrolment. Associations between digital, clinical and health outcomes data will be examined. A data-driven machine learning approach will be used to develop prediction algorithms to detect clinically significant outcomes. Study findings will inform the design, data collection procedures and protocol of future interventional randomised controlled trial, testing the effectiveness of digital phenotyping in clinical management of individuals with schizophrenia spectrum disorders.

Ethics and dissemination: Ethics approval has been granted by the National Healthcare Group (NHG) Domain Specific Review Board (DSRB Reference no.: 2019/00720). The results will be published in peer-reviewed journals and presented at conferences.

Trial registration number: NCT04230590.

Keywords: mental health; psychiatry; schizophrenia & psychotic disorders.

Conflict of interest statement

Competing interests: JL, ZY and NAAR received funding from the Ministry of Health Office of Healthcare Transformation during the course of the study. JL is further supported by the Ministry of Health National Medical Research Council. RJTM, WM, XW and NV have a patent on systems, devices and methods for self-contained personal monitoring of behaviour to improve mental health and other behaviourally related health conditions pending. Nothing in this patent will affect freedom of use in the application of the techniques described in the submitted paper. All other authors declare that they have no competing interests.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

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