Intensive Longitudinal Social Sensing in Patients With Psychosis Spectrum Disorders: An Exploratory Pilot Study

Moritz von Heyden; Paul Grube; Markus Sack; Johannes Wiesner; Oliver Frank; Kathrin Becker; Stefan Heintz; Iris Reinhard; Sarah Hohmann; Dusan Hirjak; Andreas Meyer-Lindenberg; Urs Braun

doi:10.1093/schbul/sbae032

Intensive Longitudinal Social Sensing in Patients With Psychosis Spectrum Disorders: An Exploratory Pilot Study

Schizophr Bull. 2024 Mar 24:sbae032. doi: 10.1093/schbul/sbae032. Online ahead of print.

Authors

Moritz von Heyden^{1

2}, Paul Grube^{1

2}, Markus Sack³, Johannes Wiesner^{1

2}, Oliver Frank^{1

2}, Kathrin Becker⁴, Stefan Heintz⁴, Iris Reinhard⁵, Sarah Hohmann^{4

6}, Dusan Hirjak¹, Andreas Meyer-Lindenberg^{1

7}, Urs Braun^{1

2

7}

Affiliations

¹ Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
² Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, University Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
³ Department of Neuroimaging, Central Institute of Mental Health, University Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
⁴ Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, University Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
⁵ Department of Biostatistics, Central Institute of Mental Health, University Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
⁶ Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
⁷ German Center for Mental Health, Partner site Mannheim-Heidelberg-Ulm.

PMID: 38522431
DOI: 10.1093/schbul/sbae032

Abstract

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.

Keywords: RFID sensors; negative symptoms; psychosis spectrum disorders; schizophrenia; social; social interaction.

Abstract

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