Fitbits for monitoring depressive symptoms in older aged persons: Qualitative outcomes of a feasibility study (Preprint)

JMIR Publications
Publication Type:
Journal Article
JMIR Formative Research, 2022, 6, (11), pp. e33952-e33952
Issue Date:
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BACKGROUND: In 2022, an estimated 1.105 billion people used smart wearables and 31 million used Fitbit devices, worldwide. While there is growing evidence for the use of smart wearables to benefit physical health, more research is required on the feasibility of using these devices for mental health and wellbeing. In studies focusing on emotion recognition, emotions are often inferred and dependent on external cues, which may not be representative of true emotional states. OBJECTIVE: The aim of this study was to evaluate the feasibility and acceptability of utilizing consumer-grade activity trackers for applications in remote mental health monitoring of older aged people. METHODS: Older adults were recruited using criterion sampling. Participants were provided an activity tracker (Fitbit Alta HR) and completed weekly online questionnaires, including the Geriatric Depression Scale, for 4 weeks. Before and after the study period semi-structured qualitative interviews were conducted to provide insight on the acceptance and feasibility of performing the protocol over a 4-week period. Interview transcripts were analyzed using a hybrid inductive-deductive thematic analysis. RESULTS: Twelve participants enrolled in the study, and 9 returned for interviews after the study period. Participants had positive attitudes towards being remotely monitored with 78% (7/9) participants experiencing no inconvenience throughout the study period. Sixty-seven percent (6/9) of were interested in trialing our prototype when it is implemented. Participants stated they would feel more comfortable that mental wellbeing was being monitored by carers remotely. CONCLUSIONS: Fitbit-like devices were an unobtrusive and convenient tool to collect physiological user data. Future research should integrate physiological user inputs to differentiate and predict depressive tendencies in users. CLINICALTRIAL:
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