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Xu S, Yang Z, Chakraborty D, Chua YHV, Tolomeo S, Winkler S, Birnbaum M, Tan BL, Lee J, Dauwels J. Identifying psychiatric manifestations in schizophrenia and depression from audio-visual behavioural indicators through a machine-learning approach. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:92. [PMID: 36344515 PMCID: PMC9640655 DOI: 10.1038/s41537-022-00287-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 09/08/2022] [Indexed: 11/09/2022]
Abstract
Schizophrenia (SCZ) and depression (MDD) are two chronic mental disorders that seriously affect the quality of life of millions of people worldwide. We aim to develop machine-learning methods with objective linguistic, speech, facial, and motor behavioral cues to reliably predict the severity of psychopathology or cognitive function, and distinguish diagnosis groups. We collected and analyzed the speech, facial expressions, and body movement recordings of 228 participants (103 SCZ, 50 MDD, and 75 healthy controls) from two separate studies. We created an ensemble machine-learning pipeline and achieved a balanced accuracy of 75.3% for classifying the total score of negative symptoms, 75.6% for the composite score of cognitive deficits, and 73.6% for the total score of general psychiatric symptoms in the mixed sample containing all three diagnostic groups. The proposed system is also able to differentiate between MDD and SCZ with a balanced accuracy of 84.7% and differentiate patients with SCZ or MDD from healthy controls with a balanced accuracy of 82.3%. These results suggest that machine-learning models leveraging audio-visual characteristics can help diagnose, assess, and monitor patients with schizophrenia and depression.
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Affiliation(s)
- Shihao Xu
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
| | - Zixu Yang
- Institute of Mental Health, Singapore, Singapore
| | - Debsubhra Chakraborty
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
| | - Yi Han Victoria Chua
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
- School of Social Science, Nanyang Technological University, Singapore, Singapore
| | - Serenella Tolomeo
- Department of Psychology, National University of Singapore, Singapore, Singapore
| | - Stefan Winkler
- School of Computing, National University of Singapore, Singapore, Singapore
| | | | | | - Jimmy Lee
- Institute of Mental Health, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Justin Dauwels
- Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, Netherlands.
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Tan X, Martin D, Lee J, Tor PC. The Impact of Electroconvulsive Therapy on Negative Symptoms in Schizophrenia and Their Association with Clinical Outcomes. Brain Sci 2022; 12:545. [PMID: 35624932 PMCID: PMC9139352 DOI: 10.3390/brainsci12050545] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/13/2022] [Accepted: 04/22/2022] [Indexed: 02/04/2023] Open
Abstract
OBJECTIVE The treatment efficacy of electroconvulsive therapy (ECT) for negative symptoms amongst patients with schizophrenia remains unclear. In this study, we aim to examine the effects of ECT on negative symptoms in schizophrenia and their association with other clinical outcomes, including cognition and function. METHODS This is a retrospective data analysis of patients with schizophrenia/schizoaffective disorder treated with ECT at the Institute of Mental Health (IMH), Singapore, between January 2016 and December 2019. Clinical outcomes were assessed by the Brief Psychiatric Rating Scale (BPRS), the Montreal Cognitive Assessment (MoCA), and Global Assessment of Function (GAF). Changes in scores were compared with repeated measures analysis of variance. Sequential structural modelling was utilized to examine the pathway relationships between changes in negative symptoms, global functioning, and cognition functioning after ECT. RESULTS A total of 340 patients were analysed. Hence, 196 (57.6%), 53 (15.5%), and 91 (26.7%) showed improvements, no change, and deterioration in negative symptoms, respectively. ECT-induced improvement of negative symptoms was significantly associated with improvement of global functioning (direct effect correlation coefficient (r): -0.496; se: 0.152; p = 0.001) and cognition function (indirect effect r: -0.077; se: 0.037; p = 0.035). Moreover, having capacity to consent, more severe baseline negative symptoms, lithium prescription, and an indirect effect of voluntary admission status via consent capacity predicted ECT associated negative symptoms improvement. CONCLUSION ECT is generally associated with improvements of negative symptoms in people with schizophrenia, which correlate with improvements of overall function. Possible novel clinical predictors of negative symptom improvement have been identified and will require further research and validation.
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Affiliation(s)
- Xiaowei Tan
- Department of Mood Disorder and Anxiety, Institute of Mental Health, Singapore 539747, Singapore;
| | - Donel Martin
- School of Psychiatry, University of New South Wales, Randwick, NSW 2031, Australia;
- Black Dog Institute, Hospital Road, Randwick, NSW 2031, Australia
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore 539747, Singapore;
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Phern Chern Tor
- Department of Mood Disorder and Anxiety, Institute of Mental Health, Singapore 539747, Singapore;
- Neurostimulation Service, Institute of Mental Health, Singapore 539747, Singapore
- Duke-NUS Graduate Medical School, National University of Singapore, Singapore 169857, Singapore
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Long-term consequences of COVID-19 on cognitive functioning up to 6 months after discharge: role of depression and impact on quality of life. Eur Arch Psychiatry Clin Neurosci 2022; 272:773-782. [PMID: 34698871 PMCID: PMC8546751 DOI: 10.1007/s00406-021-01346-9] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 10/19/2021] [Indexed: 01/04/2023]
Abstract
Neurologic and psychiatric symptoms have been reported in the months following the infection with COVID-19. A low-grade inflammation has been associated both with depression and cognitive symptoms, suggesting a link between these disorders. The aim of the study is to investigate cognitive functioning 6 months following hospital discharge for COVID-19, the impact of depression, and the consequences on quality of life. Ninety-two COVID-19 survivors evaluated at 1-month follow-up, 122 evaluated at 3 months and 98 evaluated at 6 months performed neuropsychological and psychiatric evaluations and were compared with a healthy comparison group (HC) of 165 subjects and 165 patients with major depression (MDD). Cognitive performances were adjusted for age, sex, and education. Seventy-nine percent of COVID-19 survivors at 1 month and 75% at 3- and 6-month follow-up showed cognitive impairment in at least one cognitive function. No significant difference in cognitive performances was observed between 1-, 3-, and 6-months follow-up. COVID-19 patients performed worse than HC but better than MDD in psychomotor coordination and speed of information processing. No difference between COVID-19 survivors and MDD was observed for verbal fluency, and executive functions, which were lower than in HC. Finally, COVID-19 survivors performed the same as HC in working memory and verbal memory. The factor that most affected cognitive performance was depressive psychopathology which, in turn, interact with cognitive functions in determining quality of life. Our results confirm that COVID-19 sequelae include signs of cognitive impairment which persist up to 6 months after hospital discharge and affect quality of life.
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Xu L, Zhang M, Wang S, Wei Y, Cui H, Qian Z, Wang Y, Tang X, Hu Y, Tang Y, Zhang T, Wang J. Corrigendum: Relationship Between Cognitive and Clinical Insight at Different Durations of Untreated Attenuated Psychotic Symptoms in High-Risk Individuals. Front Psychiatry 2022; 13:839315. [PMID: 35211047 PMCID: PMC8861634 DOI: 10.3389/fpsyt.2022.839315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 01/14/2022] [Indexed: 11/13/2022] Open
Abstract
[This corrects the article DOI: 10.3389/fpsyt.2021.753130.].
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Affiliation(s)
- LiHua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Mei Zhang
- Department of Nursing and Midwifery, Jiangsu College of Nursing, Huai'an, China
| | - ShuQin Wang
- Department of Chinese Language Teaching, Shanghong Middle School, Shanghai, China
| | - YanYan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - HuiRu Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - ZhenYing Qian
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YingChan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - XiaoChen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YeGang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YingYing Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - TianHong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - JiJun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
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Xu L, Zhang M, Wang S, Wei Y, Cui H, Qian Z, Wang Y, Tang X, Hu Y, Tang Y, Zhang T, Wang J. Relationship Between Cognitive and Clinical Insight at Different Durations of Untreated Attenuated Psychotic Symptoms in High-Risk Individuals. Front Psychiatry 2021; 12:753130. [PMID: 34867540 PMCID: PMC8637962 DOI: 10.3389/fpsyt.2021.753130] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 10/15/2021] [Indexed: 11/26/2022] Open
Abstract
Background: This study examines whether cognitive insight is impaired in high-risk individuals with attenuated psychotic symptoms (APS) and explores the relationship between cognitive and clinical insight at different durations of untreated attenuated psychotic symptoms (DUAPS). Methods: The Structured Interview for Psychosis high-risk Syndrome (SIPS) was used to identify APS individuals. APS (n = 121) and healthy control (HC, n = 87) subjects were asked to complete the Beck Cognitive Insight Scale (BCIS). Clinical insight of APS individuals was evaluated using the Schedule for Assessment of Insight (SAI). APS individuals were classified into four subgroups based on DUAPS, including 0-3, 4-6, 7-12, and >12 months. Power analysis for significant correlation was conducted using the WebPower package in R. Results: Compared with HC subjects, APS individuals showed poorer cognitive insight, with lower scores on BCIS self-reflectiveness and composite index (BCIS self-reflectiveness minus BCIS self-certainty). Only when DUAPS was longer than 12 months did the significant positive correlation between cognitive and clinical insight obtain the power about 0.8, including the associations between self-reflectiveness and awareness of illness, self-reflectiveness and the total clinical insight, and composite index and awareness of illness. The positive associations of composite index with awareness of illness within 0-3 months DUAPS and with the total score of SAI when DUAPS > 12 months were significant but failed to obtain satisfactory power. Conclusions: APS individuals may have impaired cognitive insight, demonstrating lower self-reflectiveness. The correlation between cognitive and clinical insight is associated with the duration of untreated attenuated psychotic symptoms.
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Affiliation(s)
- LiHua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Mei Zhang
- Department of Nursing and Midwifery, Jiangsu College of Nursing, Huai'an, China
| | - ShuQin Wang
- Department of Chinese Language Teaching, Shanghong Middle School, Shanghai, China
| | - YanYan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - HuiRu Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - ZhenYing Qian
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YingChan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - XiaoChen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YeGang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - YingYing Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - TianHong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - JiJun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
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