Digital phenotyping of social functioning and employment in people with schizophrenia: Pilot data from an international sample

作者：Erlend Lane, Lucy Gray, David Kimhy, Dilip V. Jeste, John Torous · 发表于：Psychiatry and Clinical Neurosciences · 年份：2025 · DOI：10.1111/pcn.13786 · 被引用次数：5 · 研究领域：Digital Mental Health Interventions、Schizophrenia research and treatment、Sleep and related disorders

Aim Individuals living with schizophrenia experience significant impairments in social functioning. As a major clinical outcome, social functioning requires appropriate measurement tools that can capture its dynamic nature. Digital phenotyping, using smartphone technology to collect high volume ecologically valid data, can potentially capture these facets. We investigated the viability of digital data, such as GPS, Accelerometer, and screen activation as a proxy for common social functioning measurements. Methods We used an ordinary least squares linear regression approach to compare the performance of digital signals with the performance of past social functioning scale (SFS) scores for predicting current SFS scores and subdomain values in 62 individuals with schizophrenia using smartphone and clinical assessments over the course of a year. The outcome of interest was the current SFS, for which we compared the capacity of the digital data (active and passive), and prior SFS scores to predict SFS scores. Results Overall, the sub‐scale models in order of performance (measured by RMSE score) were: (i) employment, (ii) social engagement, (iii) interpersonal behavior, (iv) recreation, (v) prosocial activities, (vii) performance, and (vii) competence. Digital data were particularly capable of predicting subdomain scores for employment ( R 2 = 0.746, Mean Squared Error (MSE) = 1.663) and social engagement ( R 2 = 0.710, MSE = 2.318). Conclusions Digital phenotyping may have the cap...