Cargando…

Depression prediction based on LassoNet-RNN model: A longitudinal study

Depression has become a widespread health concern today. Understanding the influencing factors can promote human mental health as well as provide a basis for exploring preventive measures. Combining LassoNet with recurrent neural network (RNN), this study constructed a screening model ,LassoNet-RNN,...

Descripción completa

Detalles Bibliográficos
Autores principales: Han, Jiatong, Li, Hao, Lin, Han, Wu, Pingping, Wang, Shidan, Tu, Juan, Lu, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570602/
https://www.ncbi.nlm.nih.gov/pubmed/37842633
http://dx.doi.org/10.1016/j.heliyon.2023.e20684
_version_ 1785119805182836736
author Han, Jiatong
Li, Hao
Lin, Han
Wu, Pingping
Wang, Shidan
Tu, Juan
Lu, Jing
author_facet Han, Jiatong
Li, Hao
Lin, Han
Wu, Pingping
Wang, Shidan
Tu, Juan
Lu, Jing
author_sort Han, Jiatong
collection PubMed
description Depression has become a widespread health concern today. Understanding the influencing factors can promote human mental health as well as provide a basis for exploring preventive measures. Combining LassoNet with recurrent neural network (RNN), this study constructed a screening model ,LassoNet-RNN, for identifying influencing factors of individual depression. Based on multi-wave surveys of China Health and Retirement Longitudinal Study (CHARLS) dataset (11,661 observations), we analyzed the multivariate time series data and recognized 27 characteristic variables selected from four perspectives: demographics, health-related risk factors, household economic status, and living environment. Additionally, the importance rankings of the characteristic variables were obtained. These results offered insightful recommendations for theoretical developments and practical decision making in public health.
format Online
Article
Text
id pubmed-10570602
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-105706022023-10-14 Depression prediction based on LassoNet-RNN model: A longitudinal study Han, Jiatong Li, Hao Lin, Han Wu, Pingping Wang, Shidan Tu, Juan Lu, Jing Heliyon Research Article Depression has become a widespread health concern today. Understanding the influencing factors can promote human mental health as well as provide a basis for exploring preventive measures. Combining LassoNet with recurrent neural network (RNN), this study constructed a screening model ,LassoNet-RNN, for identifying influencing factors of individual depression. Based on multi-wave surveys of China Health and Retirement Longitudinal Study (CHARLS) dataset (11,661 observations), we analyzed the multivariate time series data and recognized 27 characteristic variables selected from four perspectives: demographics, health-related risk factors, household economic status, and living environment. Additionally, the importance rankings of the characteristic variables were obtained. These results offered insightful recommendations for theoretical developments and practical decision making in public health. Elsevier 2023-10-05 /pmc/articles/PMC10570602/ /pubmed/37842633 http://dx.doi.org/10.1016/j.heliyon.2023.e20684 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Han, Jiatong
Li, Hao
Lin, Han
Wu, Pingping
Wang, Shidan
Tu, Juan
Lu, Jing
Depression prediction based on LassoNet-RNN model: A longitudinal study
title Depression prediction based on LassoNet-RNN model: A longitudinal study
title_full Depression prediction based on LassoNet-RNN model: A longitudinal study
title_fullStr Depression prediction based on LassoNet-RNN model: A longitudinal study
title_full_unstemmed Depression prediction based on LassoNet-RNN model: A longitudinal study
title_short Depression prediction based on LassoNet-RNN model: A longitudinal study
title_sort depression prediction based on lassonet-rnn model: a longitudinal study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570602/
https://www.ncbi.nlm.nih.gov/pubmed/37842633
http://dx.doi.org/10.1016/j.heliyon.2023.e20684
work_keys_str_mv AT hanjiatong depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy
AT lihao depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy
AT linhan depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy
AT wupingping depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy
AT wangshidan depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy
AT tujuan depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy
AT lujing depressionpredictionbasedonlassonetrnnmodelalongitudinalstudy