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Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping Review
Malik Muhammad Qirtas1, Evi Zafeiridi1, Dirk Pesch1
1School of Computer Science & Information Technology, University College Cork, Cork, Ireland.
JMIR Mhealth and Uhealth
|April 12, 2022
Summary
Passive sensing using smartphones and wearables shows promise for detecting loneliness and social isolation. However, more research is needed to address population differences and privacy concerns for reliable detection.
Area of Science:
- Digital Health
- Human-Computer Interaction
- Gerontology
Background:
- Loneliness and social isolation are linked to adverse health outcomes, including depression and mortality.
- Mobile sensing technologies offer real-time data acquisition on individual behaviors and routines.
- These technologies present new avenues for early detection of social and health issues like loneliness.
Purpose of the Study:
- To review and synthesize studies using passive sensing for loneliness and social isolation detection.
- To examine target populations, privacy, and validation methods in these studies.
- To identify gaps and future research directions in passive sensing for social isolation.
Main Methods:
- A scoping review following PRISMA-ScR guidelines.
- Searched six major academic databases for relevant studies.
- Screened studies based on passive sensing methods, populations, and reliability.
Main Results:
- 29 studies were included out of 40,071 initially identified.
- Smartphone and wearable technology were used in 69% of the studies.
- 72% of studies employed a validated reference standard for accuracy assessment.
Conclusions:
- Passive sensing shows potential but faces challenges like population heterogeneity.
- Privacy and ethical considerations require more attention despite extensive data collection.
- Further research with robust designs and ethical evaluations is necessary for reliable detection.
