A machine-learning approach to investigating the complexity of theory of mind in individuals with schizophrenia

Abstract

Individuals with schizophrenia have difficulty attributing mental states to themselves and to others - Theory of Mind (ToM). ToM is a complex, multifaceted theoretical construct comprising first and second order, first and third person, egocentric and allocentric perspective, and cognitive and affective ToM. Most studies addressing ToM deficit in people with schizophrenia consider it an "all-or-nothing" ability and use a classical statistical methodology to test a null hypothesis. With the present study, we investigated ToM in individuals with schizophrenia, considering its complex nature and degrees of impairment. To do this, we used a machine-learning approach to detect patterns in heterogeneous and multivariate data. Our findings highlight the complex nature of ToM deficit in individuals with schizophrenia and reveal the relationship between various different aspects of ToM.