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Intensive Longitudinal Social Sensing in Patients With Psychosis Spectrum Disorders: An Exploratory Pilot Study.
Schizophrenia Bulletin 2024 March 25
BACKGROUND: Psychosis spectrum disorders are characterized by significant alterations in social functioning, which is a major factor for patient recovery. Despite its importance, objectively quantifying the complex day-to-day social behavior in real-life settings has rarely been attempted. Here, we conducted a pilot study with wearable sensors that passively and continuously register interactions with other participants. We hypothesized that the amount and pattern of social interaction was associated with the severity of psychotic symptoms.
STUDY DESIGN: We recruited 7 patients with psychosis spectrum disorders and 18 team members from a Soteria-style ward. Each participant wore a radio frequency identification badge, sending and receiving signals from nearby badges, allowing passive quantification of social interactions. In addition, symptom severity was assessed weekly by the Positive and Negative Syndrome Scale (PANSS).
STUDY RESULTS: During an 11-week period, we identified 17 970 interactions among patients and staff. On average, patients spent 2.6 h per day interacting, capturing relevant aspects of daily social life. Relative daily interaction time, average interaction duration, and clustering coefficient, a measure of local network integration, were significantly associated with lower PANSS scores. Self-reported interaction time did not correlate with measured interaction time or with PANSS, indicating the importance of objective markers.
CONCLUSIONS: This pilot study demonstrates the feasibility of passively recording social interaction of patients and staff at high resolution and for a long observation period in a real-life setting in a psychiatric department. We show links between quantified social interaction and psychopathology that may facilitate development and personalization of targeted treatments.
STUDY DESIGN: We recruited 7 patients with psychosis spectrum disorders and 18 team members from a Soteria-style ward. Each participant wore a radio frequency identification badge, sending and receiving signals from nearby badges, allowing passive quantification of social interactions. In addition, symptom severity was assessed weekly by the Positive and Negative Syndrome Scale (PANSS).
STUDY RESULTS: During an 11-week period, we identified 17 970 interactions among patients and staff. On average, patients spent 2.6 h per day interacting, capturing relevant aspects of daily social life. Relative daily interaction time, average interaction duration, and clustering coefficient, a measure of local network integration, were significantly associated with lower PANSS scores. Self-reported interaction time did not correlate with measured interaction time or with PANSS, indicating the importance of objective markers.
CONCLUSIONS: This pilot study demonstrates the feasibility of passively recording social interaction of patients and staff at high resolution and for a long observation period in a real-life setting in a psychiatric department. We show links between quantified social interaction and psychopathology that may facilitate development and personalization of targeted treatments.
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