JMIR Publications

ABSTRACT

Background:

Worldwide, in 2021, 929 million people use smart wearables and 31 million use Fitbit devices. While there is growing research on using smart wearables to benefit physical health, more research is required on the application and feasibility of using these devices for mental health and wellbeing. In studies focusing on emotion recognition, inference is often dependent on external cues, which may not always be representative of genuine inner emotion.

Objective:

The aim of this study was to identify the facilitators and barriers of utilizing consumer-grade activity trackers for applications in remote mental health monitoring of older aged persons.

Methods:

Participants, aged ≥65, were recruited using criterion sampling. Participants were provided an activity tracker (Fitbit Alta HR) and completed weekly online questionnaires (Geriatric Depression Scale), and self-report mood questionnaires. We conducted semi-structured pre-post qualitative interviews with participants to gain insight on the facilitators and barriers of the procedure. Interview transcripts were analyzed using a hybrid inductive-deductive thematic analysis.

Results:

Twelve participants enrolled in the study, with 9 returning for the post-procedure interviews. Participants were positive about the procedure with 77.78% (7/9) participants finding it feasible, having experienced no inconvenience through the 4-week procedure period. 66.67% (6/9) participants were interested in the full implementation of our prototype, stating that they would feel more at ease knowing that their mental wellbeing was being monitored by their carers remotely.

Conclusions:

Fitbit-like devices are an unobtrusive tool to collect user data without being disruptive or inconvenient to the user. Future research should integrate physiological user inputs to differentiate and predict depressive tendencies in users.