Facial emotion recognition in people with schizophrenia and a history of violence: a mediation analysis

Bulgari, Viola; Bava, Mattia; Gamba, Giulia; Bartoli, Francesco; Ornaghi, Annalisa; Candini, Valentina; Ferla, Maria Teresa; Cricelli, Marta; Bianconi, Giorgio; Cavalera, Cesare; Conte, Giovanni; Stefana, Alberto; Picchioni, Marco; Iozzino, Laura; Crocamo, Cristina; Carrà, Giuseppe

doi:10.1007/s00406-019-01027-8

Cited by 20 publications

(15 citation statements)

References 49 publications

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“…Such difficulties promote the onset of psychotic symptoms and, ultimately, lead to significant social dysfunction and reduced capacity to function. Bulgari et al ( 13 ) discovered that patients' lack of ability to accurately recognize facial expression is one reason for aggressive behavior often seen in the disease, and as a result, communication between patients with schizophrenia and society is inseparable from the process of recognizing facial emotions. The ability to deal with facial emotions is the central component and deciding factor affecting patients' social cognition, and it is also an important factor affecting social function.…”

Section: Introductionmentioning

confidence: 99%

Facial Emotion Recognition in Schizophrenia

Gao

Zhao

et al. 2021

Front. Psychiatry

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Deficits in facial emotion recognition are one of the most common cognitive impairments, and they have been extensively studied in various psychiatric disorders, especially in schizophrenia. However, there is still a lack of conclusive evidence about the factors associated with schizophrenia and impairment at each stage of the disease, which poses a challenge to the clinical management of patients. Based on this, we summarize facial emotion cognition among patients with schizophrenia, introduce the internationally recognized Bruce–Young face recognition model, and review the behavioral and event-related potential studies on the recognition of emotions at each stage of the face recognition process, including suggestions for the future direction of clinical research to explore the underlying mechanisms of schizophrenia.

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Section: Introductionmentioning

confidence: 99%

Facial Emotion Recognition in Schizophrenia

Gao

Zhao

et al. 2021

Front. Psychiatry

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“…Understanding mental states and recognizing emotions appear to be related to impairments in everyday social functioning, while attributions fail to predict these types of disability. In particular, previous studies have shown deficits in facial affect recognition in patients with aggressive behaviour and impaired recognition of fear and anger, alongside misjudgement of neutral expressions as indicative of fear or anger, are characteristic of patients displaying violent behaviour [ 8 ]. However, attribution style predicts the presence of paranoid ideation [ 9 ], which, particularly when severe delusions are present, is associated with unprovoked attacks on others [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Neurocognition and social cognition in patients with schizophrenia spectrum disorders with and without a history of violence: results of a multinational European study

et al. 2021

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Objective Neurocognitive impairment has been extensively studied in people with schizophrenia spectrum disorders and seems to be one of the major determinants of functional outcome in this clinical population. Data exploring the link between neuropsychological deficits and the risk of violence in schizophrenia has been more inconsistent. In this study, we analyse the differential predictive potential of neurocognition and social cognition to discriminate patients with schizophrenia spectrum disorders with and without a history of severe violence. Methods Overall, 398 (221 cases and 177 controls) patients were recruited in forensic and general psychiatric settings across five European countries and assessed using a standardized battery. Results Education and processing speed were the strongest discriminators between forensic and non-forensic patients, followed by emotion recognition. In particular, increased accuracy for anger recognition was the most distinctive feature of the forensic group. Conclusions These results may have important clinical implications, suggesting potential enhancements of the assessment and treatment of patients with schizophrenia spectrum disorders with a history of violence, who may benefit from consideration of socio-cognitive skills commonly neglected in ordinary clinical practice.

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“…(3) aged 18-50 years; (4) psychiatric medication treatment for no more than 6 months; (5) total scores on the Positive and Negative Syndrome Scale (PANSS) over 50 points (25); (6) vision or corrected vision to 1.0 or above; (7) formal education no less than 6 years; (8) no history of electroconvulsive therapy (ECT) within 2 years; (9) no history of alcohol or drug abuse within the past 5 years; and (10) written informed consent from the patient or their legal guardian. Exclusion criteria: (1) meeting the diagnostic criteria for other psychiatric disorders in the DSM-IV; (2) history of organic brain disease such as epilepsy, traumatic brain injury, severe encephalitis, and brain tumor; and (3) contraindications for MRI.…”

Section: Subjectsmentioning

confidence: 99%

“…Previous studies have reported impaired FER in both patients with first-episode schizophrenia (FSZ) and chronic schizophrenia ( 6 , 7 ). Additionally, Bulgari et al found that facial emotion recognition in schizophrenia patients with violent behavior is different from that of non-violent patients, suggesting that face emotion recognition may be associated with violent behavior ( 8 ). These findings provide an evidence that FER deficiency in schizophrenia may suggest an inextricably linked social communication impairment.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Facial Emotion Recognition Ability in Patients With First-Episode Schizophrenia Using Amplitude of Low-Frequency Fluctuation-Based Support Vector Regression Model

et al. 2022

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ObjectiveThere were few studies that had attempted to predict facial emotion recognition (FER) ability at the individual level in schizophrenia patients. In this study, we developed a model for the prediction of FER ability in Chinese Han patients with the first-episode schizophrenia (FSZ).Materials and MethodsA total of 28 patients with FSZ and 33 healthy controls (HCs) were recruited. All subjects underwent resting-state fMRI (rs-fMRI). The amplitude of low-frequency fluctuation (ALFF) method was selected to analyze voxel-level spontaneous neuronal activity. The visual search experiments were selected to evaluate the FER, while the support vector regression (SVR) model was selected to develop a model based on individual rs-fMRI brain scan.ResultsGroup difference in FER ability showed statistical significance (P < 0.05). In FSZ patients, increased mALFF value were observed in the limbic lobe and frontal lobe, while decreased mALFF value were observed in the frontal lobe, parietal lobe, and occipital lobe (P < 0.05, AlphaSim correction). SVR analysis showed that abnormal spontaneous activity in multiple brain regions, especially in the right posterior cingulate, right precuneus, and left calcarine could effectively predict fearful FER accuracy (r = 0.64, P = 0.011) in patients.ConclusionOur study provides an evidence that abnormal spontaneous activity in specific brain regions may serve as a predictive biomarker for fearful FER ability in schizophrenia.

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Facial emotion recognition in people with schizophrenia and a history of violence: a mediation analysis

Cited by 20 publications

References 49 publications

Facial Emotion Recognition in Schizophrenia

Facial Emotion Recognition in Schizophrenia

Neurocognition and social cognition in patients with schizophrenia spectrum disorders with and without a history of violence: results of a multinational European study

Prediction of Facial Emotion Recognition Ability in Patients With First-Episode Schizophrenia Using Amplitude of Low-Frequency Fluctuation-Based Support Vector Regression Model

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