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Article: Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach

TitleCognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach
Authors
Keywordscognitive clusters
cognitive heterogeneity
cognitive impairment
first-episode psychosis
functional outcome
Issue Date27-Jul-2023
PublisherFrontiers Media
Citation
Frontiers in Psychiatry, 2023, v. 14 How to Cite?
AbstractIntroduction: Prior 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. Methods: Two-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. Results: Three 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. Discussion: Our 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.
Persistent Identifierhttp://hdl.handle.net/10722/331870
ISSN
2023 Impact Factor: 3.2
2023 SCImago Journal Rankings: 1.155
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorKam, CTK-
dc.contributor.authorFung, VSC-
dc.contributor.authorChang, WC-
dc.contributor.authorHui, CLM-
dc.contributor.authorChan, SKW-
dc.contributor.authorLee, EHM-
dc.contributor.authorLui, SSY-
dc.contributor.authorChen, EYH-
dc.date.accessioned2023-09-28T04:59:14Z-
dc.date.available2023-09-28T04:59:14Z-
dc.date.issued2023-07-27-
dc.identifier.citationFrontiers in Psychiatry, 2023, v. 14-
dc.identifier.issn1664-0640-
dc.identifier.urihttp://hdl.handle.net/10722/331870-
dc.description.abstractIntroduction: Prior 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. Methods: Two-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. Results: Three 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. Discussion: Our 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.-
dc.languageeng-
dc.publisherFrontiers Media-
dc.relation.ispartofFrontiers in Psychiatry-
dc.subjectcognitive clusters-
dc.subjectcognitive heterogeneity-
dc.subjectcognitive impairment-
dc.subjectfirst-episode psychosis-
dc.subjectfunctional outcome-
dc.titleCognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach-
dc.typeArticle-
dc.identifier.doi10.3389/fpsyt.2023.1203655-
dc.identifier.scopuseid_2-s2.0-85167705793-
dc.identifier.volume14-
dc.identifier.eissn1664-0640-
dc.identifier.isiWOS:001043989900001-
dc.identifier.issnl1664-0640-

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