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Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study
BACKGROUND AND HYPOTHESIS: Current 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 DESIGN: We utilized data of 1119 patients from the Gene...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10686366/ https://www.ncbi.nlm.nih.gov/pubmed/37104875 http://dx.doi.org/10.1093/schbul/sbad046 |
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author | Tiles-Sar, Natalia Habtewold, Tesfa Dejenie Liemburg, Edith J van der Meer, Lisette Bruggeman, Richard Alizadeh, Behrooz Z |
author_facet | Tiles-Sar, Natalia Habtewold, Tesfa Dejenie Liemburg, Edith J van der Meer, Lisette Bruggeman, Richard Alizadeh, Behrooz Z |
author_sort | Tiles-Sar, Natalia |
collection | PubMed |
description | BACKGROUND AND HYPOTHESIS: Current 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 DESIGN: We 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 RESULTS: We found all trajectories were significantly associated with SF (P < .01), explaining up to 16% of SF variation (R(2) 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. CONCLUSIONS: We found a core set of lifelong predictors of SF. Yet, the performance of our prediction models was moderate. |
format | Online Article Text |
id | pubmed-10686366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106863662023-11-30 Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study Tiles-Sar, Natalia Habtewold, Tesfa Dejenie Liemburg, Edith J van der Meer, Lisette Bruggeman, Richard Alizadeh, Behrooz Z Schizophr Bull Regular Articles BACKGROUND AND HYPOTHESIS: Current 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 DESIGN: We 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 RESULTS: We found all trajectories were significantly associated with SF (P < .01), explaining up to 16% of SF variation (R(2) 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. CONCLUSIONS: We found a core set of lifelong predictors of SF. Yet, the performance of our prediction models was moderate. Oxford University Press 2023-04-27 /pmc/articles/PMC10686366/ /pubmed/37104875 http://dx.doi.org/10.1093/schbul/sbad046 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Regular Articles Tiles-Sar, Natalia Habtewold, Tesfa Dejenie Liemburg, Edith J van der Meer, Lisette Bruggeman, Richard Alizadeh, Behrooz Z Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
title | Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
title_full | Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
title_fullStr | Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
title_full_unstemmed | Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
title_short | Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study |
title_sort | understanding lifelong factors and prediction models of social functioning after psychosis onset using the large-scale group cohort study |
topic | Regular Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10686366/ https://www.ncbi.nlm.nih.gov/pubmed/37104875 http://dx.doi.org/10.1093/schbul/sbad046 |
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