Objective monitoring of loneliness levels using smart devices: A multi-device approach for mental health applications.

Loneliness is linked to wide ranging physical and mental health problems, including increased rates of mortality. Understanding how loneliness manifests is important for targeted public health treatment and intervention. With advances in mobile sending and wearable technologies, it is possible to collect data on human phenomena in a continuous and uninterrupted way. In doing so, such approaches can be used to monitor physiological and behavioral aspects relevant to an individual's loneliness. In this study, we proposed a method for continuous detection of loneliness using fully objective data from smart devices and passive mobile sensing. We also investigated whether physiological and behavioral features differed in their importance in predicting loneliness across individuals. Finally, we examined how informative data from each device is for loneliness detection tasks. We assessed subjective feelings of loneliness while monitoring behavioral and physiological patterns in 30 college students over a 2-month period. We used smartphones to monitor behavioral patterns (e.g., location changes, type of notifications, in-coming and out-going calls/text messages) and smart watches and rings to monitor physiology and sleep patterns (e.g., heart-rate, heart-rate variability, sleep duration). Participants reported their loneliness feeling multiple times a day through a questionnaire app on their phone. Using the data collected from their devices, we trained a random forest machine learning based model to detect loneliness levels. We found support for loneliness prediction using a multi-device and fully-objective approach. Furthermore, behavioral data collected by smartphones generally were the most important features across all participants. The study provides promising results for using objective data to monitor mental health indicators, which could provide a continuous and uninterrupted source of information in mental healthcare applications.

Perspectives of Japanese elders and their healthcare providers on use of wearable technology to monitor their health at home: A qualitative exploration.

BACKGROUND: With 24 million Japanese elderly aging at home, the challenges of managing chronic conditions are significant. As many Japanese elders manage multiple chronic conditions, investigating the usefulness of wearable health devices for this population is warranted. AIM: The purpose of this qualitative study, using grounded theory, was to explore the perspectives of Japanese elders, their caretakers, and their healthcare providers on the use of technology and wearable devices to monitor health conditions and keep Japanese elders safe at home. METHODS: In conducting this study, a community advisory board was first established to guide the research design; six focus groups and two one-on-one interviews were conducted, with a total of 21 participants. RESULTS: Four major themes emerged from the analysis: 1) Current Status of Health Issues Experienced by Japanese Elders and Ways of Being Monitored; 2) Current Use of Monitoring Technology and Curiosity about Use of the Latest Digital Technology to Keep Elderly Healthy at Home; 3) Perceived Advantages of Wearing Sensor Technology; and 4) Perceived Disadvantages of Wearing Technology. Many of the elderly participants were interested in using monitoring devices at home, particularly if not complicated. Healthcare workers found monitoring technologies particularly useful during the isolation of the COVID-19 pandemic. Elderly participants felt cost and technical issues could be barriers to using monitoring devices. CONCLUSION: While there are challenges to utilizing monitoring devices, the potential to aid the aging population of Japan justifies further investigation into the effectiveness of these devices. This study was not registered with a research trial registry.