SCC-IRG JST: Active sensing and personalized interventions for pandemic-induced social isolation

Social connections are essential for individuals' health and the growth of a community. Social isolation is an increasing concern in developed countries with aging populations. The American Academy of Social Work and Social Welfare calls social isolation ``a silent killer as dangerous to health as smoking.'' The onset of the COVID-19 pandemic greatly exacerbated the problems of social isolation, depriving older adults of their personal interactions with peers and often even with caregivers. This proposal aims to develop and evaluate techno-social solutions to increase the social interactions between older adults within a community, reducing the level of social isolation within a community, while maintaining the required social distancing --- issues of great importance in the US and Japan. This project represents a collaboration between academic researchers and community partners in the U.S. and Japan, who will provide a potential pathway for transitioning research results to practice. Although this project focuses on social isolation in older adults, knowledge developed through this project can be applied to other age groups and other domains in mental health and healthcare.

The aim is to develop a technology platform and tools to facilitate re-engagement of community members at high risk for social isolation. It will enable the delivery of tailored interventions to connect community members with peers and caregivers in the community at the individual level, as well as interventions to plan and coordinate services at the community level. The potential of this work will be demonstrated with two distinctly different communities of older adults at high risk for social isolation, one in the U.S. and one in Japan. This proposal addresses the following technical challenges: (1) Identification of new sensing modalities to complement sensors already used in the field. (2) Develop techniques and algorithms to analyze collected state information to predict with sufficient likelihood the onset of a problem early enough for caregivers to react to the problem. (3) Personalization of the proposed interventions, i.e., adapting interventions to a specific individual at runtime, with a focus on decision-making at the community level. (4) Develop a platform to integrate sensors with data storage and the analysis engine ensuring security of the system and protecting privacy of the individuals.

This project is a joint collaboration between the National Science Foundation and the Japan Science and Technology Agency.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.