Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods

Sexually active young people face an increasing public health burden of unintended pregnancies and sexually transmitted diseases due to improper contraception. However, environmental and social factors related to young people’s contraception remain unclear. To identify the key factors, we applied en...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Zongchao Liu, Zhi Lin, Wenzhen Cao, Rui Li, Lilong Liu, Hanbin Wu, Kun Tang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	public health contraception machine learning young people Pediatrics RJ1-570
Acceso en línea:	https://doaj.org/article/4aaa48e5ce324d78a02af14f7b5be798
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:4aaa48e5ce324d78a02af14f7b5be798
record_format	dspace
spelling	oai:doaj.org-article:4aaa48e5ce324d78a02af14f7b5be7982021-11-25T17:14:01ZIdentify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods10.3390/children81109682227-9067https://doaj.org/article/4aaa48e5ce324d78a02af14f7b5be7982021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9067/8/11/968https://doaj.org/toc/2227-9067Sexually active young people face an increasing public health burden of unintended pregnancies and sexually transmitted diseases due to improper contraception. However, environmental and social factors related to young people’s contraception remain unclear. To identify the key factors, we applied ensemble machine learning methods to the data of 12,280 heterosexual Chinese college students who reported sexual intercourse experience in the National College Student Survey on Sexual and Reproductive Health in 2020 (NCSS-SRH 2020). In the order of variable importance, convenient access to contraceptives, certain attitudes towards sex, sexual health knowledge level, being an only-child, and purchasing a bachelor’s or master’s degree were positively associated with a high frequency of contraceptive use. In contrast, smoking, free access to contraceptives, a specific attitude towards marriage, and negotiation with a sexual partner were negatively associated with a higher frequency of contraceptive use. Our analysis provides insights into young people’s contraceptive use under a typically conservative culture of sexuality. Compared to previous studies, we thoroughly investigated internal and external factors that might impact young people’s decision on contraception while having sex. Under a conservative culture of sexuality, the effects of the external factors on young people’s contraception may outweigh those of the internal factors.Zongchao LiuZhi LinWenzhen CaoRui LiLilong LiuHanbin WuKun TangMDPI AGarticlepublic healthcontraceptionmachine learningyoung peoplePediatricsRJ1-570ENChildren, Vol 8, Iss 968, p 968 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	public health contraception machine learning young people Pediatrics RJ1-570
spellingShingle	public health contraception machine learning young people Pediatrics RJ1-570 Zongchao Liu Zhi Lin Wenzhen Cao Rui Li Lilong Liu Hanbin Wu Kun Tang Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods
description	Sexually active young people face an increasing public health burden of unintended pregnancies and sexually transmitted diseases due to improper contraception. However, environmental and social factors related to young people’s contraception remain unclear. To identify the key factors, we applied ensemble machine learning methods to the data of 12,280 heterosexual Chinese college students who reported sexual intercourse experience in the National College Student Survey on Sexual and Reproductive Health in 2020 (NCSS-SRH 2020). In the order of variable importance, convenient access to contraceptives, certain attitudes towards sex, sexual health knowledge level, being an only-child, and purchasing a bachelor’s or master’s degree were positively associated with a high frequency of contraceptive use. In contrast, smoking, free access to contraceptives, a specific attitude towards marriage, and negotiation with a sexual partner were negatively associated with a higher frequency of contraceptive use. Our analysis provides insights into young people’s contraceptive use under a typically conservative culture of sexuality. Compared to previous studies, we thoroughly investigated internal and external factors that might impact young people’s decision on contraception while having sex. Under a conservative culture of sexuality, the effects of the external factors on young people’s contraception may outweigh those of the internal factors.
format	article
author	Zongchao Liu Zhi Lin Wenzhen Cao Rui Li Lilong Liu Hanbin Wu Kun Tang
author_facet	Zongchao Liu Zhi Lin Wenzhen Cao Rui Li Lilong Liu Hanbin Wu Kun Tang
author_sort	Zongchao Liu
title	Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods
title_short	Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods
title_full	Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods
title_fullStr	Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods
title_full_unstemmed	Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods
title_sort	identify key determinants of contraceptive use for sexually active young people: a hybrid ensemble of machine learning methods
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4aaa48e5ce324d78a02af14f7b5be798
work_keys_str_mv	AT zongchaoliu identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods AT zhilin identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods AT wenzhencao identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods AT ruili identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods AT lilongliu identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods AT hanbinwu identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods AT kuntang identifykeydeterminantsofcontraceptiveuseforsexuallyactiveyoungpeopleahybridensembleofmachinelearningmethods
_version_	1718412585332637696

Identify Key Determinants of Contraceptive Use for Sexually Active Young People: A Hybrid Ensemble of Machine Learning Methods

Ejemplares similares