Characterisation of alogia in people with schizophrenia using natural language processing. a comparative study with a group of people with bipolar disorder

Using Natural Language Processing (NLP)-derived metrics, we examined poverty of speech in a group of people diagnosed with schizophrenia compared to a group of people with bipolar disorder and a control group, intending to describe a pattern of alterations specific to schizophrenia and to help clarify the degree of association with deficit symptoms and cognitive deficits.Methods Ninety participants were recruited for the study, distributed equally in three groups: schizophrenia (SZ), bipolar disorder (BD), and healthy controls (HC). All participants described scenes depicting people interacting with each other in everyday social situations, and their cognitive functioning was assessed using the screen for cognitive impairment in Psychiatry (SCIP). Clinical status was assessed with the Brief Psychiatric Rating Scale (BPRS). Speech samples were explored with metrics that quantify speech production and complexity.Results People with schizophrenia exhibited lower verbal production and reduced sentence complexity compared to healthy controls, while the bipolar disorder group showed values largely overlapping with controls. Across the pooled patient sample (SZ + BD), negative symptom severity was associated with multiple linguistic measures, including mean length of utterance (r = −0.384, BF₁₀ = 14.03, 95% CI [−0.571, −0.138]), syntagms, discourse complexity, and lexical–morphological indices, whereas positive symptoms showed little or no association with language metrics. Better cognitive functioning was associated with greater linguistic richness across most measures.Conclusions The findings from this study suggest that poverty of speech, as captured by NLP-derived measures, is more prominent in schizophrenia than in bipolar disorder and healthy controls within the present sample. The observed associations with cognitive performance highlight the close relationship between language production and cognition, but do not establish a causal dependence. Rather than prompting a re-examination of alogia’s classification among negative symptoms, these results underscore the need for integrative models that account for the well-known covariation between negative symptoms and cognitive functioning.

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Journal
Cognitive Neuropsychiatry
Published
2026-07-27
DOI
https://doi.org/10.1080/13546805.2026.2703583
Primary Topic
Schizophrenia research and treatment
Type
article
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article

Characterisation of alogia in people with schizophrenia using natural language processing. a comparative study with a group of people with bipolar disorder

Francisca Alonso, Mónica Otero, Álvaro Cavieres, Jorge Portal et al.
Cognitive Neuropsychiatry
Schizophrenia research and treatment
article

Characterisation of alogia in people with schizophrenia using natural language processing. a comparative study with a group of people with bipolar disorder

Francisca Alonso, Mónica Otero, Álvaro Cavieres, Jorge Portal, Vanessa Acuña, Pablo Lopez-Silva, Amanda Cifuentes, Juan Satt
article en

Abstract

Using Natural Language Processing (NLP)-derived metrics, we examined poverty of speech in a group of people diagnosed with schizophrenia compared to a group of people with bipolar disorder and a control group, intending to describe a pattern of alterations specific to schizophrenia and to help clarify the degree of association with deficit symptoms and cognitive deficits.Methods Ninety participants were recruited for the study, distributed equally in three groups: schizophrenia (SZ), bipolar disorder (BD), and healthy controls (HC). All participants described scenes depicting people interacting with each other in everyday social situations, and their cognitive functioning was assessed using the screen for cognitive impairment in Psychiatry (SCIP). Clinical status was assessed with the Brief Psychiatric Rating Scale (BPRS). Speech samples were explored with metrics that quantify speech production and complexity.Results People with schizophrenia exhibited lower verbal production and reduced sentence complexity compared to healthy controls, while the bipolar disorder group showed values largely overlapping with controls. Across the pooled patient sample (SZ + BD), negative symptom severity was associated with multiple linguistic measures, including mean length of utterance (r = −0.384, BF₁₀ = 14.03, 95% CI [−0.571, −0.138]), syntagms, discourse complexity, and lexical–morphological indices, whereas positive symptoms showed little or no association with language metrics. Better cognitive functioning was associated with greater linguistic richness across most measures.Conclusions The findings from this study suggest that poverty of speech, as captured by NLP-derived measures, is more prominent in schizophrenia than in bipolar disorder and healthy controls within the present sample. The observed associations with cognitive performance highlight the close relationship between language production and cognition, but do not establish a causal dependence. Rather than prompting a re-examination of alogia’s classification among negative symptoms, these results underscore the need for integrative models that account for the well-known covariation between negative symptoms and cognitive functioning.

Cognitive Neuropsychiatry
Valparaiso University (US), San Sebastián University (CL), University of Oxford (GB), Universidad Técnica Federico Santa María (EC), Institute for Complex Systems (IT)
Quality Education
Openalex Percentile: Top 8%
Schizophrenia research and treatment
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