Mughal Fiza, Raffe William, Stubbs Peter, Kneebone Ian, Garcia Jaime
Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia.
Discipline of Physiotherapy, University of Technology Sydney, Sydney, Australia.
JMIR Form Res. 2022 Nov 29;6(11):e33952. doi: 10.2196/33952.
In 2022, an estimated 1.105 billion people used smart wearables and 31 million used Fitbit devices worldwide. Although 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 well-being. In studies focusing on emotion recognition, emotions are often inferred and dependent on external cues, which may not be representative of true emotional states.
The aim of this study was to evaluate the feasibility and acceptability of using consumer-grade activity trackers for apps in the remote mental health monitoring of older aged people.
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, semistructured qualitative interviews were conducted to provide insight into the acceptance and feasibility of performing the protocol over a 4-week period. Interview transcripts were analyzed using a hybrid inductive-deductive thematic analysis.
In total, 12 participants enrolled in the study, and 9 returned for interviews after the study period. Participants had positive attitudes toward being remotely monitored, with 78% (7/9) of participants experiencing no inconvenience throughout the study period. Moreover, 67% (6/9) were interested in trialing our prototype when it is implemented. Participants stated they would feel more comfortable if mental well-being was being monitored by carers remotely.
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.
2022年，全球估计有11.05亿人使用智能可穿戴设备，3100万人使用Fitbit设备。尽管越来越多的证据表明使用智能可穿戴设备有益于身体健康，但对于将这些设备用于心理健康和幸福方面的可行性，仍需要更多研究。在专注于情绪识别的研究中，情绪往往是推断出来的，且依赖于外部线索，这可能并不代表真实的情绪状态。
本研究的目的是评估在老年人远程心理健康监测中使用消费级活动追踪器应用程序的可行性和可接受性。
采用标准抽样招募老年人。为参与者提供一个活动追踪器（Fitbit Alta HR），并让他们在4周内每周完成在线问卷，包括老年抑郁量表。在研究期前后，进行半结构化定性访谈，以深入了解在4周内执行该方案的可接受性和可行性。使用混合归纳-演绎主题分析法对访谈记录进行分析。
共有12名参与者登记参加本研究，9名在研究期后返回接受访谈。参与者对远程监测持积极态度，78%（7/9）的参与者在整个研究期内没有感到不便。此外，67%（6/9）的参与者在我们的原型实施后有兴趣试用。参与者表示，如果由护理人员远程监测心理健康，他们会感觉更自在。
类似Fitbit的设备是收集用户生理数据的一种不引人注意且方便的工具。未来的研究应整合用户的生理输入，以区分和预测用户的抑郁倾向。
