Aim: Social cognition impairment is a hallmark of schizophrenia and contains multiple domains. The domain of social inference has been relatively understudied in schizophrenia and its risk states.
Methods: Social inference was assessed in 60 clinical high-risk (CHR) patients and 28 healthy control subjects, using the video social inference task. We hypothesized a deficit in social inference in CHR participants and examined predictive value for psychosis transition.
Results: Social inference was positively associated with increasing age. Social inference did not differ significantly between CHR patients and controls, or predict transition to psychosis.
Conclusions: Few studies have examined social inference of individuals at clinical high risk for psychosis, and findings have been inconclusive. Additional studies using a variety of measures of social inference in CHR participants are recommended.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/eip.12182 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Socioeconomic inequalities in depression and the role of job conditions in China.
Front Public Health
December 2024
Asian Demographic Research Institute, School of Sociology and Political Sciences, Shanghai University, Shanghai, China.
Background: The rising prevalence of depression in China, coupled with a tightening job market, highlights concern for the workforce's mental health. Although socioeconomic inequalities in depression have been well documented in high-income countries, the association between socioeconomic status (SES) and depression, along with its work-related mediators, has not been sufficiently studied in China.
Methods: The study participants are 6,536 non-agriculturally employed working adults from the 2020 China Family Panel Studies (CFPS).
Individual differences in autism-like traits are associated with reduced goal emulation in a computational model of observational learning.
Nat Ment Health
September 2024
Division of Humanities and Social Sciences, California Institute of Technology, USA.
One's ability to infer the goals and intentions of others is crucial for social interactions, and such social capabilities are broadly distributed across individuals. Autism-like traits (i.e.
View Article and Find Full Text PDFAre you tuned in to others' mind? A cross-modal evaluation of affective theory of mind in people with Parkinson's disease.
Acta Psychol (Amst)
December 2024
Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Affective Theory of Mind (ToM) is the ability to understand other peoples' emotional states and feelings. Several studies showed impaired affective ToM abilities in people with Parkinson's disease (PD). However, most studies tested this ability by using single-stimulus modality tasks (visual cues).
View Article and Find Full Text PDFEffectiveness of a social cognition remediation intervention for patients with schizophrenia: a randomized-controlled study.
Ann Gen Psychiatry
December 2024
University of Campania "Luigi Vanvitelli", Piazza Miraglia 2, 80138, Naples, Italy.
This randomized-controlled study evaluates the effectiveness of a newly developed social cognition rehabilitation intervention, the modified Social Cognition Individualized Activity Lab (mSoCIAL), in improving social cognition and clinical and functional outcomes of persons with schizophrenia recruited in two Italian sites: University of Campania "Luigi Vanvitelli" in Naples and ASST Fatebenefratelli-Sacco in Milan. mSoCIAL consists of a social cognitive training module focusing on different domains of social cognition and of a narrative enhancement module. We assessed changes in social cognition, clinical characteristics and functional variables in patients with schizophrenia who participated in 10 weekly sessions of mSoCIAL or received treatment as usual (TAU).
View Article and Find Full Text PDFDANI: fast diffusion aware network inference with preserving topological structure property.
Sci Rep
December 2024
Department of Computer Engineering, Sharif University of Technology, Azadi Avenue, Tehran, Iran.
Numerous algorithms have been proposed to infer the underlying structure of the social networks via observed information propagation. The previously proposed algorithms concentrate on inferring accurate links and neglect preserving the essential topological properties of the underlying social networks. In this paper, we propose a novel method called DANI to infer the underlying network while preserving its structural properties.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!