To date no data still exist on the comprehension of figurative language in the early phases of psychosis. The aim of this study is to investigate for the first time the comprehension of metaphors and idioms at the onset of the illness. Two-hundred-twenty eight (228) first episode psychosis (FEP) patients (168 NAP, non-affective psychosis; 60 AP, affective psychosis) and 70 healthy controls (HC) were assessed. Groups were contrasted on: a) type of stimulus (metaphors vs idioms) and b) type of response (OPEN = spontaneous explanations vs CLOSED = multiple choice answer). Moreover, a machine learning (ML) approach was adopted to classifying participants. Both NAP and AP had a poorer performance on OPEN metaphors and idioms compared to HC, with worse results on spontaneous interpretation of idioms than metaphors. No differences were observed between NAP and AP in CLOSED tasks. The ML approach points at CLOSED idioms as the best discriminating variable, more relevant than the set of pre-frontal and IQ scores. Deficits in non-figurative language may represent a core feature of psychosis. The possibility to identify linguistic features discriminating FEP may support the early recognition of patients at risk to develop psychosis, guiding provision of personalized and timely interventions.

Non literal language comprehension in a large sample of first episode psychosis patients in adulthood

Finos, Livio
Formal Analysis
;
Veronese, Angela;Ruggeri, Mirella;
2017

Abstract

To date no data still exist on the comprehension of figurative language in the early phases of psychosis. The aim of this study is to investigate for the first time the comprehension of metaphors and idioms at the onset of the illness. Two-hundred-twenty eight (228) first episode psychosis (FEP) patients (168 NAP, non-affective psychosis; 60 AP, affective psychosis) and 70 healthy controls (HC) were assessed. Groups were contrasted on: a) type of stimulus (metaphors vs idioms) and b) type of response (OPEN = spontaneous explanations vs CLOSED = multiple choice answer). Moreover, a machine learning (ML) approach was adopted to classifying participants. Both NAP and AP had a poorer performance on OPEN metaphors and idioms compared to HC, with worse results on spontaneous interpretation of idioms than metaphors. No differences were observed between NAP and AP in CLOSED tasks. The ML approach points at CLOSED idioms as the best discriminating variable, more relevant than the set of pre-frontal and IQ scores. Deficits in non-figurative language may represent a core feature of psychosis. The possibility to identify linguistic features discriminating FEP may support the early recognition of patients at risk to develop psychosis, guiding provision of personalized and timely interventions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3249161
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