Integrating smartwatches in community mental health services for severe mental illness for detecting relapse and informing future intervention: A case series.

OBJECTIVE: This case series explored the integration of smartwatches in a community mental health service to support severe mental illness (SMI) management and intervention. We examined whether biometric data provided by smartwatches could help to predict relapse and inform treatment decisions. METHOD: Four Australian SMI outpatients of mixed diagnoses (age range = 19-24) were selected from a prior study. Clinicians accessed patients' biometric data (activity, sleep, heart rate, and electrodermal activity) through smartwatches. RESULTS: Changes in circadian rhythm and electrodermal activity preceded hospitalization in two cases. Additionally, smartwatch data was effectively used to guide targeted interventions, improving patient treatment outcomes. CONCLUSION: Integrating smartwatches in community mental health services offers promise as adjunct tools for SMI management. However, ethical considerations on data privacy and technology reliance require further evaluation. Additionally, as this is a small case series, randomized controlled trials with larger sample sizes are required to provide evidence for generalisability of results.

Integrating a Mobile Health Device Into a Community Youth Mental Health Team to Manage Severe Mental Illness: Protocol for a Randomized Controlled Trial.

BACKGROUND: Symptoms of mental illness are often triggered by stress, and individuals with mental illness are sensitive to these effects. The development of mobile health (mHealth) devices allows continuous recording of biometrics associated with activity, sleep, and arousal. Deviations in these measures could indicate a stressed state requiring early intervention. This paper describes a protocol for integrating an mHealth device into a community mental health team to enhance management of severe mental illness in young adults. OBJECTIVE: The aim of this study is to examine (1) whether an mHealth device integrated into a community mental health team can improve outcomes for young adults with severe mental illness and (2) whether the device detects periods of mental health versus deterioration. METHODS: This study examines whether physiological information from an mHealth device prevents mental deterioration when shared with the participant and clinical team versus with the participant alone. A randomized controlled trial (RCT) will allocate 126 young adults from community mental health services for 6 months to standard case management combined with an integrated mHealth device (ie, physiological information is viewed by both participant and case manager: unWIRED intervention) or an unintegrated mHealth device (ie, participant alone self-monitors: control). Participants will wear the Empatica Embrace2 device, which continuously records electrodermal activity and actigraphy (ie, rest and activity). The study also examines whether the Embrace2 can detect periods of mental health versus deterioration. A variety of measurements will be taken, including physiological data from the Embrace2; participant and case manager self-report regarding symptoms, functioning, and quality of life; chart reviews; and ecological momentary assessments of stress in real time. Changes in each participant's Clinical Global Impression Scale scores will be assessed by blinded raters as the primary outcome. In addition, participants and case managers will provide qualitative data regarding their experience with the integrated mHealth device, which will be thematically analyzed. RESULTS: The study has received ethical approval from the Western Sydney Local Health District Human Research Ethics Committee. It is due to start in October 2020 and conclude in October 2022. CONCLUSIONS: The RCT will provide insight as to whether an integrated mHealth device enables case managers and participants to pre-emptively manage early warning signs and prevent relapse. We anticipate that unWIRED will enhance early intervention by improving detection of stress and allowing case managers and patients to better engage and respond to symptoms. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000642987; https://www.anzctr.org.au/ACTRN12620000642987.aspx. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/19510.

Using a mobile health device to manage severe mental illness in the community: What is the potential and what are the challenges?

There has been a revolution in the use of mobile health devices for monitoring physical health. There is more recent interest in whether these devices can also be used for monitoring symptoms of mental illness. This paper considers how stress increases risk of mental deterioration and individuals with mental illness are sensitive to the effects of stress. It discusses how an inexpensive mobile health device could be used for detecting physiological signs of stress: deviations in biometrics such as sleep, activity and arousal may reflect a stress response and increased risk of relapse. These biometrics can allow patients to self-monitor and clinicians to detect early warning signs. This paper reviews the measurement of electrodermal activity, actigraphy and heart rate to predict mental deterioration. It considers the advantages of continuous measurement and reviews studies using mobile health devices to monitor stress and psychosis. It describes the potential for using a mobile health device to manage and monitor severe mental illness in young adults. Finally, this paper considers challenges associated with this approach, particularly with regard to correctly interpreting the physiological data and integrating the mobile health device into clinical practice. This paper concludes a mobile health device has the potential to enhance care by improving detection of early warning signs and increasing the connection between clinicians and their patients.