Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach
IntroductionPrior research examining cognitive heterogeneity in psychotic disorders primarily focused on chronic schizophrenia, with limited data on first-episode psychosis (FEP). We aimed to identify distinct cognitive subgroups in adult FEP patients using data-driven cluster-analytic approach, and...
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1203655/full |
| _version_ | 1797771272382316544 |
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| author | Candice Tze Kwan Kam Vivian Shi Cheng Fung Wing Chung Chang Wing Chung Chang Christy Lai Ming Hui Sherry Kit Wa Chan Sherry Kit Wa Chan Edwin Ho Ming Lee Simon Sai Yu Lui Eric Yu Hai Chen Eric Yu Hai Chen |
| author_facet | Candice Tze Kwan Kam Vivian Shi Cheng Fung Wing Chung Chang Wing Chung Chang Christy Lai Ming Hui Sherry Kit Wa Chan Sherry Kit Wa Chan Edwin Ho Ming Lee Simon Sai Yu Lui Eric Yu Hai Chen Eric Yu Hai Chen |
| author_sort | Candice Tze Kwan Kam |
| collection | DOAJ |
| description | IntroductionPrior research examining cognitive heterogeneity in psychotic disorders primarily focused on chronic schizophrenia, with limited data on first-episode psychosis (FEP). We aimed to identify distinct cognitive subgroups in adult FEP patients using data-driven cluster-analytic approach, and examine relationships between cognitive subgroups and a comprehensive array of illness-related variables.MethodsTwo-hundred-eighty-nine Chinese patients aged 26–55 years presenting with FEP to an early intervention program in Hong Kong were recruited. Assessments encompassing premorbid adjustment, illness-onset profile, symptom severity, psychosocial functioning, subjective quality-of-life, and a battery of cognitive tests were conducted. Hierarchical cluster-analysis was employed, optimized with k-means clustering and internally-validated by discriminant-functional analysis. Cognitive subgroup comparisons in illness-related variables, followed by multivariable multinominal-regression analyzes were performed to identify factors independently predictive of cluster membership.ResultsThree clusters were identified including patients with globally-impaired (n = 101, 34.9%), intermediately-impaired (n = 112, 38.8%) and relatively-intact (n = 76, 26.3%) cognition (GIC, IIC and RIC subgroups) compared to demographically-matched healthy-controls’ performance (n = 50). GIC-subgroup was older, had lower educational attainment, greater positive, negative and disorganization symptom severity, poorer insight and quality-of-life than IIC- and RIC-subgroups, and higher antipsychotic-dose than RIC-subgroup. IIC-subgroup had lower education levels and more severe negative symptoms than RIC-subgroup, which had better psychosocial functioning than two cognitively-impaired subgroups. Educational attainment and disorganization symptoms were found to independently predict cluster membership.DiscussionOur results affirmed cognitive heterogeneity in FEP and identified three subgroups, which were differentially associated with demographic and illness-related variables. Further research should clarify longitudinal relationships of cognitive subgroups with clinical and functional outcomes in FEP. |
| first_indexed | 2024-03-12T21:35:07Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-03-12T21:35:07Z |
| publishDate | 2023-07-01 |
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| series | Frontiers in Psychiatry |
| spelling | doaj.art-0b824aca7b0349778a0c0df30cdedada2023-07-27T08:39:15ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-07-011410.3389/fpsyt.2023.12036551203655Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approachCandice Tze Kwan Kam0Vivian Shi Cheng Fung1Wing Chung Chang2Wing Chung Chang3Christy Lai Ming Hui4Sherry Kit Wa Chan5Sherry Kit Wa Chan6Edwin Ho Ming Lee7Simon Sai Yu Lui8Eric Yu Hai Chen9Eric Yu Hai Chen10Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaState Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaState Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaDepartment of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, ChinaState Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, ChinaIntroductionPrior research examining cognitive heterogeneity in psychotic disorders primarily focused on chronic schizophrenia, with limited data on first-episode psychosis (FEP). We aimed to identify distinct cognitive subgroups in adult FEP patients using data-driven cluster-analytic approach, and examine relationships between cognitive subgroups and a comprehensive array of illness-related variables.MethodsTwo-hundred-eighty-nine Chinese patients aged 26–55 years presenting with FEP to an early intervention program in Hong Kong were recruited. Assessments encompassing premorbid adjustment, illness-onset profile, symptom severity, psychosocial functioning, subjective quality-of-life, and a battery of cognitive tests were conducted. Hierarchical cluster-analysis was employed, optimized with k-means clustering and internally-validated by discriminant-functional analysis. Cognitive subgroup comparisons in illness-related variables, followed by multivariable multinominal-regression analyzes were performed to identify factors independently predictive of cluster membership.ResultsThree clusters were identified including patients with globally-impaired (n = 101, 34.9%), intermediately-impaired (n = 112, 38.8%) and relatively-intact (n = 76, 26.3%) cognition (GIC, IIC and RIC subgroups) compared to demographically-matched healthy-controls’ performance (n = 50). GIC-subgroup was older, had lower educational attainment, greater positive, negative and disorganization symptom severity, poorer insight and quality-of-life than IIC- and RIC-subgroups, and higher antipsychotic-dose than RIC-subgroup. IIC-subgroup had lower education levels and more severe negative symptoms than RIC-subgroup, which had better psychosocial functioning than two cognitively-impaired subgroups. Educational attainment and disorganization symptoms were found to independently predict cluster membership.DiscussionOur results affirmed cognitive heterogeneity in FEP and identified three subgroups, which were differentially associated with demographic and illness-related variables. Further research should clarify longitudinal relationships of cognitive subgroups with clinical and functional outcomes in FEP.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1203655/fullcognitive heterogeneitycognitive clusterscognitive impairmentfirst-episode psychosisfunctional outcome |
| spellingShingle | Candice Tze Kwan Kam Vivian Shi Cheng Fung Wing Chung Chang Wing Chung Chang Christy Lai Ming Hui Sherry Kit Wa Chan Sherry Kit Wa Chan Edwin Ho Ming Lee Simon Sai Yu Lui Eric Yu Hai Chen Eric Yu Hai Chen Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach Frontiers in Psychiatry cognitive heterogeneity cognitive clusters cognitive impairment first-episode psychosis functional outcome |
| title | Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach |
| title_full | Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach |
| title_fullStr | Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach |
| title_full_unstemmed | Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach |
| title_short | Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach |
| title_sort | cognitive subgroups and the relationships with symptoms psychosocial functioning and quality of life in first episode non affective psychosis a cluster analysis approach |
| topic | cognitive heterogeneity cognitive clusters cognitive impairment first-episode psychosis functional outcome |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1203655/full |
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