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.
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.
Authors: Francesco Dal Santo; Eduardo Fonseca-Pedrero; María Paz García-Portilla; Leticia González-Blanco; Pilar A Sáiz; Silvana Galderisi; Giulia Maria Giordano; Julio Bobes Journal: Eur Psychiatry Date: 2022-06-10 Impact factor: 7.156
Authors: Hui-Xin Hu; Wilson Y S Lau; Eugenia P Y Ma; Karen S Y Hung; Si-Yu Chen; Kin-Shing Cheng; Eric F C Cheung; Simon S Y Lui; Raymond C K Chan Journal: Schizophr Bull Date: 2022-06-21 Impact factor: 7.348
Authors: S Galderisi; A Mucci; S Dollfus; M Nordentoft; P Falkai; S Kaiser; G M Giordano; A Vandevelde; M Ø Nielsen; L B Glenthøj; M Sabé; P Pezzella; I Bitter; W Gaebel Journal: Eur Psychiatry Date: 2021-02-18 Impact factor: 5.361
Authors: Hua Ye; Andrew Zalesky; Jinglei Lv; Samantha M Loi; Suheyla Cetin-Karayumak; Yogesh Rathi; Ye Tian; Christos Pantelis; Maria A Di Biase Journal: Schizophr Bull Date: 2021-07-08 Impact factor: 9.306