A network analysis of facial and vocal emotion recognition deficits in schizophrenia
IntroductionFacial and vocal emotion recognition deficits are common in individuals with schizophrenia.MethodsIn this observational, single-center study, 106 patients with schizophrenia (SCZ) and 118 age- and sex-matched healthy controls underwent cognitive and emotional function assessments. The Te...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1598026/full |
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| author | Wenxuan Zhao Qi Zhang Long Gao Ning Fan Yajun Yun Jiaqi Song Yunhe Ji Yongqian Wang Meng Zhang Fude Yang Shuping Tan |
| author_facet | Wenxuan Zhao Qi Zhang Long Gao Ning Fan Yajun Yun Jiaqi Song Yunhe Ji Yongqian Wang Meng Zhang Fude Yang Shuping Tan |
| author_sort | Wenxuan Zhao |
| collection | DOAJ |
| description | IntroductionFacial and vocal emotion recognition deficits are common in individuals with schizophrenia.MethodsIn this observational, single-center study, 106 patients with schizophrenia (SCZ) and 118 age- and sex-matched healthy controls underwent cognitive and emotional function assessments. The Temporal Experience of Pleasure Scale (TEPS), Personal and Social Performance Scale, Positive and Negative Symptom Scale, and Brief Negative Symptom Scale were used to evaluate psychotic symptoms in the SCZ group. Participants were assessed using the MATRICS Consensus Cognitive Battery (MCCB), the Positive and Negative Syndrome Scale, and emotion recognition tests involving 42 facial and 42 vocal emotional tasks.ResultsThe SCZ group had significant impairments in facial and vocal emotion recognition, with lower accuracy across all emotional categories. Mean scores in the SCZ group were significantly lower than those in the control group (facial, 23.55 ± 7.10 vs. 31.86 ± 5.16; vocal, 18.64 ± 9.48 vs. 29.42 ± 5.01, respectively; p<0.001). Emotion recognition deficits and demographic or clinical characteristics were not significantly correlated. Network analysis revealed strong intercorrelations among different cognitive domains, linking MCCB performance to emotion recognition abilities (r>0.9; p<0.001). Integration of tests of cognitive function (MCCB, area under the curve [AUC]=91.90%, p<0.01), emotion recognition abilities (facial, AUC=82.56%; vocal, AUC=82.82%; p<0.01), and TEPS (AUC=91.13%, p<0.01) proved useful for distinguishing patients with schizophrenia from healthy individuals.DiscussionThese findings underscore the importance of emotion recognition impairments in schizophrenia and their strong association with cognitive deficits. Future interventions should focus on targeted cognitive and affective training strategies. Incorporating multimodal assessments into clinical evaluations may enhance diagnostic accuracy. |
| format | Article |
| id | doaj-art-366d8928ae3a4e2f8b330b55808df830 |
| institution | Kabale University |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-366d8928ae3a4e2f8b330b55808df8302025-08-20T03:53:50ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-05-011610.3389/fpsyt.2025.15980261598026A network analysis of facial and vocal emotion recognition deficits in schizophreniaWenxuan Zhao0Qi Zhang1Long Gao2Ning Fan3Yajun Yun4Jiaqi Song5Yunhe Ji6Yongqian Wang7Meng Zhang8Fude Yang9Shuping Tan10Peking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaWuxi Mental Health Center, Wuxi, ChinaChangping Labroray, Beijing, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaYantai Psychological Rehabilitation Hospital, Yantai, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaPeking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, ChinaIntroductionFacial and vocal emotion recognition deficits are common in individuals with schizophrenia.MethodsIn this observational, single-center study, 106 patients with schizophrenia (SCZ) and 118 age- and sex-matched healthy controls underwent cognitive and emotional function assessments. The Temporal Experience of Pleasure Scale (TEPS), Personal and Social Performance Scale, Positive and Negative Symptom Scale, and Brief Negative Symptom Scale were used to evaluate psychotic symptoms in the SCZ group. Participants were assessed using the MATRICS Consensus Cognitive Battery (MCCB), the Positive and Negative Syndrome Scale, and emotion recognition tests involving 42 facial and 42 vocal emotional tasks.ResultsThe SCZ group had significant impairments in facial and vocal emotion recognition, with lower accuracy across all emotional categories. Mean scores in the SCZ group were significantly lower than those in the control group (facial, 23.55 ± 7.10 vs. 31.86 ± 5.16; vocal, 18.64 ± 9.48 vs. 29.42 ± 5.01, respectively; p<0.001). Emotion recognition deficits and demographic or clinical characteristics were not significantly correlated. Network analysis revealed strong intercorrelations among different cognitive domains, linking MCCB performance to emotion recognition abilities (r>0.9; p<0.001). Integration of tests of cognitive function (MCCB, area under the curve [AUC]=91.90%, p<0.01), emotion recognition abilities (facial, AUC=82.56%; vocal, AUC=82.82%; p<0.01), and TEPS (AUC=91.13%, p<0.01) proved useful for distinguishing patients with schizophrenia from healthy individuals.DiscussionThese findings underscore the importance of emotion recognition impairments in schizophrenia and their strong association with cognitive deficits. Future interventions should focus on targeted cognitive and affective training strategies. Incorporating multimodal assessments into clinical evaluations may enhance diagnostic accuracy.https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1598026/fullschizophreniaemotion recognitionneuropsychological testsprincipal component analysisnetwork analysis |
| spellingShingle | Wenxuan Zhao Qi Zhang Long Gao Ning Fan Yajun Yun Jiaqi Song Yunhe Ji Yongqian Wang Meng Zhang Fude Yang Shuping Tan A network analysis of facial and vocal emotion recognition deficits in schizophrenia Frontiers in Psychiatry schizophrenia emotion recognition neuropsychological tests principal component analysis network analysis |
| title | A network analysis of facial and vocal emotion recognition deficits in schizophrenia |
| title_full | A network analysis of facial and vocal emotion recognition deficits in schizophrenia |
| title_fullStr | A network analysis of facial and vocal emotion recognition deficits in schizophrenia |
| title_full_unstemmed | A network analysis of facial and vocal emotion recognition deficits in schizophrenia |
| title_short | A network analysis of facial and vocal emotion recognition deficits in schizophrenia |
| title_sort | network analysis of facial and vocal emotion recognition deficits in schizophrenia |
| topic | schizophrenia emotion recognition neuropsychological tests principal component analysis network analysis |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1598026/full |
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