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Inter-relationships among psychopathology, premorbid adjustment, cognition and psychosocial functioning in first-episode psychosis: a network analysis approach

Published online by Cambridge University Press:  27 August 2019

W. C. Chang
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
C. S. M. Wong
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
P. C. F. Or
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
A. O. K. Chu
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
C. L. M. Hui
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
S. K. W. Chan
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
E. M. H. Lee
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
Y. N. Suen
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
E. Y. H. Chen
Affiliation:
Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
Corresponding
E-mail address:

Abstract

Background

Better understanding of interplay among symptoms, cognition and functioning in first-episode psychosis (FEP) is crucial to promoting functional recovery. Network analysis is a promising data-driven approach to elucidating complex interactions among psychopathological variables in psychosis, but has not been applied in FEP.

Method

This study employed network analysis to examine inter-relationships among a wide array of variables encompassing psychopathology, premorbid and onset characteristics, cognition, subjective quality-of-life and psychosocial functioning in 323 adult FEP patients in Hong Kong. Graphical Least Absolute Shrinkage and Selection Operator (LASSO) combined with extended Bayesian information criterion (BIC) model selection was used for network construction. Importance of individual nodes in a generated network was quantified by centrality analyses.

Results

Our results showed that amotivation played the most central role and had the strongest associations with other variables in the network, as indexed by node strength. Amotivation and diminished expression displayed differential relationships with other nodes, supporting the validity of two-factor negative symptom structure. Psychosocial functioning was most strongly connected with amotivation and was weakly linked to several other variables. Within cognitive domain, digit span demonstrated the highest centrality and was connected with most of the other cognitive variables. Exploratory analysis revealed no significant gender differences in network structure and global strength.

Conclusion

Our results suggest the pivotal role of amotivation in psychopathology network of FEP and indicate its critical association with psychosocial functioning. Further research is required to verify the clinical significance of diminished motivation on functional outcome in the early course of psychotic illness.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2019

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Inter-relationships among psychopathology, premorbid adjustment, cognition and psychosocial functioning in first-episode psychosis: a network analysis approach
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