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Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study

Identifying the possible factors of psychiatric symptoms among children can reduce the risk of adverse psychosocial outcomes in adulthood. We designed a classification tool to examine the association between modifiable risk factors and psychiatric symptoms, defined based on the Persian version of th...

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Autores principales: Marateb, Hamid Reza, Tasdighi, Zahra, Mohebian, Mohammad Reza, Naghavi, Azam, Hess, Moritz, Motlagh, Mohammad Esmaiel, Heshmat, Ramin, Mansourian, Marjan, Mañanas, Miguel Angel, Binder, Harald, Kelishadi, Roya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8333323/
https://www.ncbi.nlm.nih.gov/pubmed/34344950
http://dx.doi.org/10.1038/s41598-021-95208-y
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author Marateb, Hamid Reza
Tasdighi, Zahra
Mohebian, Mohammad Reza
Naghavi, Azam
Hess, Moritz
Motlagh, Mohammad Esmaiel
Heshmat, Ramin
Mansourian, Marjan
Mañanas, Miguel Angel
Binder, Harald
Kelishadi, Roya
author_facet Marateb, Hamid Reza
Tasdighi, Zahra
Mohebian, Mohammad Reza
Naghavi, Azam
Hess, Moritz
Motlagh, Mohammad Esmaiel
Heshmat, Ramin
Mansourian, Marjan
Mañanas, Miguel Angel
Binder, Harald
Kelishadi, Roya
author_sort Marateb, Hamid Reza
collection PubMed
description Identifying the possible factors of psychiatric symptoms among children can reduce the risk of adverse psychosocial outcomes in adulthood. We designed a classification tool to examine the association between modifiable risk factors and psychiatric symptoms, defined based on the Persian version of the WHO-GSHS questionnaire in a developing country. Ten thousand three hundred fifty students, aged 6–18 years from all Iran provinces, participated in this study. We used feature discretization and encoding, stability selection, and regularized group method of data handling (GMDH) to classify the a priori specific factors (e.g., demographic, sleeping-time, life satisfaction, and birth-weight) to psychiatric symptoms. Self-rated health was the most critical feature. The selected modifiable factors were eating breakfast, screentime, salty snack for depression symptom, physical activity, salty snack for worriedness symptom, (abdominal) obesity, sweetened beverage, and sleep-hour for mild-to-moderate emotional symptoms. The area under the ROC curve of the GMDH was 0.75 (CI 95% 0.73–0.76) for the analyzed psychiatric symptoms using threefold cross-validation. It significantly outperformed the state-of-the-art (adjusted p < 0.05; McNemar's test). In this study, the association of psychiatric risk factors and the importance of modifiable nutrition and lifestyle factors were emphasized. However, as a cross-sectional study, no causality can be inferred.
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spelling pubmed-83333232021-08-05 Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study Marateb, Hamid Reza Tasdighi, Zahra Mohebian, Mohammad Reza Naghavi, Azam Hess, Moritz Motlagh, Mohammad Esmaiel Heshmat, Ramin Mansourian, Marjan Mañanas, Miguel Angel Binder, Harald Kelishadi, Roya Sci Rep Article Identifying the possible factors of psychiatric symptoms among children can reduce the risk of adverse psychosocial outcomes in adulthood. We designed a classification tool to examine the association between modifiable risk factors and psychiatric symptoms, defined based on the Persian version of the WHO-GSHS questionnaire in a developing country. Ten thousand three hundred fifty students, aged 6–18 years from all Iran provinces, participated in this study. We used feature discretization and encoding, stability selection, and regularized group method of data handling (GMDH) to classify the a priori specific factors (e.g., demographic, sleeping-time, life satisfaction, and birth-weight) to psychiatric symptoms. Self-rated health was the most critical feature. The selected modifiable factors were eating breakfast, screentime, salty snack for depression symptom, physical activity, salty snack for worriedness symptom, (abdominal) obesity, sweetened beverage, and sleep-hour for mild-to-moderate emotional symptoms. The area under the ROC curve of the GMDH was 0.75 (CI 95% 0.73–0.76) for the analyzed psychiatric symptoms using threefold cross-validation. It significantly outperformed the state-of-the-art (adjusted p < 0.05; McNemar's test). In this study, the association of psychiatric risk factors and the importance of modifiable nutrition and lifestyle factors were emphasized. However, as a cross-sectional study, no causality can be inferred. Nature Publishing Group UK 2021-08-03 /pmc/articles/PMC8333323/ /pubmed/34344950 http://dx.doi.org/10.1038/s41598-021-95208-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Marateb, Hamid Reza
Tasdighi, Zahra
Mohebian, Mohammad Reza
Naghavi, Azam
Hess, Moritz
Motlagh, Mohammad Esmaiel
Heshmat, Ramin
Mansourian, Marjan
Mañanas, Miguel Angel
Binder, Harald
Kelishadi, Roya
Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study
title Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study
title_full Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study
title_fullStr Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study
title_full_unstemmed Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study
title_short Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study
title_sort classification of psychiatric symptoms using deep interaction networks: the caspian-iv study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8333323/
https://www.ncbi.nlm.nih.gov/pubmed/34344950
http://dx.doi.org/10.1038/s41598-021-95208-y
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