1
|
The complexity of theory of mind deficit in schizophrenia: A cross-sectional analysis of baseline data from a longitudinal schizophrenia study. Acta Psychol (Amst) 2023; 233:103842. [PMID: 36701860 DOI: 10.1016/j.actpsy.2023.103842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 12/26/2022] [Accepted: 01/19/2023] [Indexed: 01/25/2023] Open
Abstract
A large number of trials have supported the functional significance of Theory of Mind (ToM) impairment in schizophrenia. However, the nature and the extent of the impairment are still unclear. Reviews on the topic suggest that, in many cases, studies use only one tool to assess the levels of difficulty in the field, limiting the validity of the measurement to one aspect of ToM. On the other hand, the divergence of the used assessment tools makes it hard to compare the result of these studies. Thus, we decided to use additional assessment tools to evaluate the extent of ToM in order to describe several aspects of the phenomenon. A hierarchical cluster analysis of variables was used on a sample of 68 participants with schizophrenia or schizoaffective disorder, to determine the similarity between variances of the assessed ToM subcomponents. Further cross-sectional correlational analysis was then performed to investigate the association between the identified clusters and other used measures (e.g.: neurocognition). The statistical analysis supported a five-cluster model. Identified clusters illustrate the difference between Hypo and HyperToM as well as the degree of ToM task complexity, allowing for a more accurate description of the nature of ToM deficit in schizophrenia.
Collapse
|
2
|
Oliver LD, Haltigan JD, Gold JM, Foussias G, DeRosse P, Buchanan RW, Malhotra AK, Voineskos AN. Lower- and Higher-Level Social Cognitive Factors Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls: Relationship With Neurocognition and Functional Outcome. Schizophr Bull 2019; 45:629-638. [PMID: 30107517 PMCID: PMC6483578 DOI: 10.1093/schbul/sby114] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Schizophrenia spectrum disorders (SSDs) often feature social cognitive deficits. However, little work has focused on the factor structure of social cognition, and results have been inconsistent in schizophrenia. This study aimed to elucidate the factor structure of social cognition across people with SSDs and healthy controls. It was hypothesized that a 2-factor model, including lower-level "simulation" and higher-level "mentalizing" factors, would demonstrate the best fit across participants. METHODS Participants with SSDs (N = 164) and healthy controls (N = 102) completed social cognitive tasks ranging from emotion recognition to complex mental state inference, as well as clinical and functional outcome, and neurocognitive measures. Structural equation modeling was used to test social cognitive models, models of social cognition and neurocognition, measurement invariance between cases and controls, and relationships with outcome measures. RESULTS A 2-factor (simulation and mentalizing) model fit the social cognitive data best across participants and showed adequate measurement invariance in both SSD and control groups. Patients showed lower simulation and mentalizing scores than controls, but only mentalizing was significantly associated with negative symptoms and functional outcome. Social cognition also mediated the relationship between neurocognition and both negative symptoms and functional outcome. CONCLUSIONS These results uniquely indicate that distinct lower- and higher-level aspects of social cognition exist across SSDs and healthy controls. Further, mentalizing may be particularly linked to negative symptoms and functional outcome. This informs future studies of the neural circuitry underlying social cognition and the development of targeted treatment options for improving functional outcome.
Collapse
Affiliation(s)
- Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - John D Haltigan
- Clinical Research Division, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD
| | - George Foussias
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada,Clinical Research Division, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Pamela DeRosse
- Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, NY,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD
| | - Anil K Malhotra
- Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, NY,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada,Clinical Research Division, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada,To whom correspondence should be addressed; Centre for Addiction and Mental Health, 250 College Street, Toronto, ON M5T 1R8, Canada; tel: 416-535-8501 (ext. 33977), fax: 416-260-4162, e-mail:
| | | |
Collapse
|
3
|
Abstract
Cognitive impairments in substance use disorders have been extensively researched, especially since the advent of cognitive and computational neuroscience and neuroimaging methods in the last 20 years. Conceptually, altered cognitive function can be viewed as a hallmark feature of substance use disorders, with documented alterations in the well-known "executive" domains of attention, inhibition/regulation, working memory, and decision-making. Poor cognitive (sometimes referred to as "top-down") regulation of downstream motivational processes-whether appetitive (reward, incentive salience) or aversive (stress, negative affect)-is recognized as a fundamental impairment in addiction and a potentially important target for intervention. As addressed in this special issue, cognitive impairment is a transdiagnostic domain; thus, advances in the characterization and treatment of cognitive dysfunction in substance use disorders could have benefit across multiple psychiatric disorders. Toward this general goal, we summarize current findings in the abovementioned cognitive domains of substance use disorders, while suggesting a potentially useful expansion to include processes that both precede (precognition) and supersede (social cognition) what is usually thought of as strictly cognition. These additional two areas have received relatively less attention but phenomenologically and otherwise are important features of substance use disorders. The review concludes with suggestions for research and potential therapeutic targeting of both the familiar and this more comprehensive version of cognitive domains related to substance use disorders.
Collapse
|
4
|
Zhang T, Cui H, Wei Y, Tang Y, Xu L, Tang X, Zhu Y, Jiang L, Zhang B, Qian Z, Chow A, Liu X, Li C, Xiao Z, Wang J. Progressive decline of cognition during the conversion from prodrome to psychosis with a characteristic pattern of the theory of mind compensated by neurocognition. Schizophr Res 2018; 195:554-559. [PMID: 28823722 DOI: 10.1016/j.schres.2017.08.020] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2017] [Revised: 08/15/2017] [Accepted: 08/15/2017] [Indexed: 10/19/2022]
Abstract
The association between neurocognition and the theory of mind (ToM) abilities during the progression of psychosis is unclear. This study included 83 individuals with attenuated psychosis syndrome (APS), from which 26 converted to psychosis (converters) after a follow up period of 18months. Comprehensive cognitive tests (including MATRICS Consensus Cognitive Battery, Faux-Pas Task, and Reading-Mind-in-Eyes Tasks) were administered at baseline. A structural equation modeling (SEM) analysis was conducted to estimate the effects of neurocognition on the ToM functioning in both APS and healthy controls (HC) datasets. At baseline, the converters and non-converters groups differed significantly on several domains of cognitive performance. The SEM analysis demonstrated that the path from neurocognition to ToM was statistically significant in the APS dataset (p<0.001). However, in the HC dataset, the result of the same analysis was not significant (p=0.117). Positive correlations between neurocognition and ToM were observed, and the most obvious correlations were found in the converters group compared with the non-converters group (p=0.064) and compared with the HC group (p=0.002). The correlation between ToM abilities and neurocognition may be increased during the progression of the condition, especially for individuals who convert to psychosis after a short period.
Collapse
Affiliation(s)
- TianHong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, PR China.
| | - HuiRu Cui
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - YanYan Wei
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - YingYing Tang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, PR China
| | - LiHua Xu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - XiaoChen Tang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - YiKang Zhu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - LiJuan Jiang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Bin Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - ZhenYing Qian
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Annabelle Chow
- James Cook University, Clinical Psychology, 387380 Singapore, Singapore
| | - XiaoHua Liu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - ChunBo Li
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - ZePing Xiao
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - JiJun Wang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai, PR China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, PR China.
| |
Collapse
|
5
|
Minichino A, Francesconi M, Carrión RE, Bevilacqua A, Parisi M, Rullo S, Ando' A, Biondi M, Delle Chiaie R, Cadenhead K. Prediction of functional outcome in young patients with a recent-onset psychiatric disorder: Beyond the traditional diagnostic classification system. Schizophr Res 2017; 185:114-121. [PMID: 28041918 DOI: 10.1016/j.schres.2016.12.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Revised: 12/13/2016] [Accepted: 12/17/2016] [Indexed: 01/04/2023]
Abstract
A critical research goal is to identify modifiable risk factors leading to functional disabilities in young psychiatric patients. The authors developed a multidimensional trans-diagnostic predictive model of functional outcome in patients with the recent-onset of a psychiatric illness. Baseline clinical, psychosis-risk status, cognitive, neurological-soft-signs measures, and dopamine-related-gene polymorphisms (DRD1-rs4532, COMT-rs165599, and DRD4-rs1800955) were collected in 138 young non-psychotic outpatients. 116 individuals underwent follow-up (mean=2.2years, SD=0.9) examination. A binary logistic model was used to predict low-functioning status at follow-up as defined by a score lower than 65 in the social occupational functioning assessment scale. A total of 54% of patients experiences low functioning at follow-up. Attention, Avolition, and Motor-Coordination subscale were significant predictors of low-functioning with an accuracy of 79.7%. A non-significant trend was found for a dopamine-related-gene polymorphism (DRD1-rs4532). The model was independent of psychotic-risk status, DSM-diagnosis, and psychotic conversion. A trans-diagnostic approach taking into account specific neurocognitive, clinical, and neurological information has the potential to identify those individuals with low-functioning independent of DSM diagnosis or the level of psychosis-risk. Specific early interventions targeting modifiable risk factors and emphasize functional recovery in young psychiatric samples, independent of DSM-diagnosis and psychosis-risk, are essential.
Collapse
Affiliation(s)
- Amedeo Minichino
- Department of Neurology and Psychiatry, Sapienza University of Rome, Italy; Department of Psychiatry, UCSD, La Jolla, CA, United States.
| | - Marta Francesconi
- Department of Neurology and Psychiatry, Sapienza University of Rome, Italy; Department of Psychiatry, UCSD, La Jolla, CA, United States
| | - Ricardo E Carrión
- Division of Psychiatry, Zucker Hillside Hospital, Long Island, NY, United States
| | - Arturo Bevilacqua
- Research Center in Neurobiology, Daniel Bovet (CRiN), Rome, Italy; Department of Psychology, Section of Neuroscience, Sapienza University of Rome, Italy
| | | | | | - Agata Ando'
- Department of Psychology, University of Turin
| | - Massimo Biondi
- Department of Neurology and Psychiatry, Sapienza University of Rome, Italy
| | | | | |
Collapse
|