Impaired social functioning is a symptom of mental illness (e.g., depression, schizophrenia) and a wide range of other conditions (e.g., cognitive decline in the elderly, dementia). Today, assessing social functioning relies on subjective evaluations and self assessments. We propose a different approach and collect detailed social functioning measures and objective mobile sensing data from N=55 outpatients living with schizophrenia to study new methods of passively accessing social functioning. We identify a number of behavioral patterns from sensing data, and discuss important correlations between social function sub-scales and mobile sensing features. We show we can accurately predict the social functioning of outpatients in our study including the following sub-scales: prosocial activities (MAE = 7.79, r = 0.53), which indicates engagement in common social activities; interpersonal behavior (MAE = 3.39, r = 0.57), which represents the number of friends and quality of communications; and employment/occupation (MAE = 2.17, r = 0.62), which relates to engagement in productive employment or a structured program of daily activity. Our work on automatically inferring social functioning opens the way to new forms of assessment and intervention across a number of areas including mental health and aging in place.

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https://hci.top/en/papers/chi/31799/2020

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DOI: https://doi.org/10.1145/3313831.3376855
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Source
CHI
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Year
2020
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No award tagged
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Authors
17 authors
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Subtopics
Mental Health Apps & Online Support Communities, Telemedicine & Remote Patient Monitoring
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Professions
Psychiatrists & Psychotherapists, Elderly Care Workers, Family Caregivers
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Content Status
Abstract only
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Related Papers
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