Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study
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| Titel: | Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
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| Autoren: | Natalia Tiles-Sar, Tesfa Dejenie Habtewold, Edith J Liemburg, Lisette van der Meer, Richard Bruggeman, Behrooz Z Alizadeh, Therese van Amelsvoort, Agna A Bartels-Velthuis, Lieuwe de Haan, Frederike Schirmbeck, Claudia J P Simons, Jim van Os |
| Weitere Verfasser: | Hart- en Vaatziekten Team A, Genetica, Hersenen-Medisch 1, Brain |
| Quelle: | Schizophr Bull |
| Verlagsinformationen: | Oxford University Press (OUP), 2023. |
| Publikationsjahr: | 2023 |
| Schlagwörter: | Outcome Assessment, association, mixed-effect model/trajectories, Social Interaction, 3. Good health, schizophrenia, Health Care, Cohort Studies, Psychiatry and Mental health, Psychotic Disorders, Outcome Assessment, Health Care, follow-up, Psychotic Disorders/complications, Humans, Social Adjustment, Regular Articles |
| Beschreibung: | Background and hypothesisCurrent rates of poor social functioning (SF) in people with psychosis history reach 80% worldwide. We aimed to identify a core set of lifelong predictors and build prediction models of SF after psychosis onset.Study designWe utilized data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) longitudinal Dutch cohort. First, we applied group-based trajectory modeling to identify premorbid adjustment trajectories. We further investigated the association between the premorbid adjustment trajectories, six-year-long cognitive deficits, positive, and negative symptoms trajectories, and SF at 3-year and 6-year follow-ups. Next, we checked associations between demographics, clinical, and environmental factors measured at the baseline and SF at follow-up. Finally, we built and internally validated 2 predictive models of SF.Study resultsWe found all trajectories were significantly associated with SF (P < .01), explaining up to 16% of SF variation (R2 0.15 for 3- and 0.16 for 6-year follow-up). Demographics (sex, ethnicity, age, education), clinical parameters (genetic predisposition, illness duration, psychotic episodes, cannabis use), and environment (childhood trauma, number of moves, marriage, employment, urbanicity, unmet needs of social support) were also significantly associated with SF. After validation, final prediction models explained a variance up to 27% (95% CI: 0.23, 0.30) at 3-year and 26% (95% CI: 0.22, 0.31) at 6-year follow-up.ConclusionsWe found a core set of lifelong predictors of SF. Yet, the performance of our prediction models was moderate. |
| Publikationsart: | Article Other literature type |
| Dateibeschreibung: | application/pdf |
| Sprache: | English |
| ISSN: | 1745-1701 0586-7614 |
| DOI: | 10.1093/schbul/sbad046 |
| Zugangs-URL: | https://pubmed.ncbi.nlm.nih.gov/37104875 https://research.rug.nl/en/publications/3d0bccd0-11be-4842-9900-3c707b64b759 https://doi.org/10.1093/schbul/sbad046 https://hdl.handle.net/11370/3d0bccd0-11be-4842-9900-3c707b64b759 https://cris.maastrichtuniversity.nl/en/publications/00560b34-a5f4-4516-bc65-f1585110feeb https://doi.org/10.1093/schbul/sbad046 https://dspace.library.uu.nl/handle/1874/451165 https://pure.amsterdamumc.nl/en/publications/85c52243-7c0f-4611-bc60-f4eb34a288ac https://doi.org/10.1093/schbul/sbad046 |
| Rights: | CC BY URL: http://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Dokumentencode: | edsair.doi.dedup.....b51d0cdce5749464d5a3746b9cce11b6 |
| Datenbank: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstract: | Background and hypothesisCurrent rates of poor social functioning (SF) in people with psychosis history reach 80% worldwide. We aimed to identify a core set of lifelong predictors and build prediction models of SF after psychosis onset.Study designWe utilized data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) longitudinal Dutch cohort. First, we applied group-based trajectory modeling to identify premorbid adjustment trajectories. We further investigated the association between the premorbid adjustment trajectories, six-year-long cognitive deficits, positive, and negative symptoms trajectories, and SF at 3-year and 6-year follow-ups. Next, we checked associations between demographics, clinical, and environmental factors measured at the baseline and SF at follow-up. Finally, we built and internally validated 2 predictive models of SF.Study resultsWe found all trajectories were significantly associated with SF (P < .01), explaining up to 16% of SF variation (R2 0.15 for 3- and 0.16 for 6-year follow-up). Demographics (sex, ethnicity, age, education), clinical parameters (genetic predisposition, illness duration, psychotic episodes, cannabis use), and environment (childhood trauma, number of moves, marriage, employment, urbanicity, unmet needs of social support) were also significantly associated with SF. After validation, final prediction models explained a variance up to 27% (95% CI: 0.23, 0.30) at 3-year and 26% (95% CI: 0.22, 0.31) at 6-year follow-up.ConclusionsWe found a core set of lifelong predictors of SF. Yet, the performance of our prediction models was moderate. |
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| ISSN: | 17451701 05867614 |
| DOI: | 10.1093/schbul/sbad046 |