Chinese Women's Concept of Childbirth Based on the Social Media Topic "What Does Childbirth Mean to a Woman": Content and Thematic Analysis.

childbirth benefit childbirth cost childbirth willingness risk perception social media

Journal

JMIR pediatrics and parenting
ISSN: 2561-6722
Titre abrégé: JMIR Pediatr Parent
Pays: Canada
ID NLM: 101727244

Informations de publication

Date de publication:
05 Jan 2024
Historique:
received: 04 07 2023
accepted: 16 11 2023
revised: 15 11 2023
medline: 5 1 2024
pubmed: 5 1 2024
entrez: 5 1 2024
Statut: epublish

Résumé

In recent years, women's fertility desire has attracted increasing attention in China. This study aims to detect attitudes toward giving birth among young female users on Douban, a very popular Chinese social media platform. A total of 2634 valid posts from 2489 users discussing the topic "What does childbirth mean to a woman" on Douban were crawled and retained for analysis. We utilized content and thematic analysis methods to capture users' concepts of childbirth. The findings reveal that a significant majority of users conveyed generally neutral (1060/2634, 40.24%) or negative (1051/2634, 39.90%) attitudes toward childbirth, while only about one-fifth of users expressed positive (523/2634, 19.86%) sentiments. Notably, posts with negative attitudes garnered more replies and likes, and the proportion of posts expressing negativity exhibited fluctuations over time. Health risk (339/2634, 12.87%) emerged as the most frequently cited aspect of childbirth cost, with subjective happiness and the fulfillment of mental needs identified as primary benefits. Surprisingly, only a minimal number of posts (10/2634, 0.38%) touched upon the traditional objective benefits of raising children for old-age care. Thematic analysis results suggest that discussions about fertility on social media platforms might contribute to an exaggerated perception of health risks among women. Additionally, a lack of knowledge about childbirth was observed, partially attributable to longstanding neglect and avoidance of communication on these matters, likely influenced by traditional cultural biases. Moreover, there is a prevailing assumption that women should naturally sacrifice themselves for childbirth and childcare, influenced by the idealization of the female figure. Consequently, women may harbor hesitations about having a baby, fearing the potential loss of their own identity in the process. The results indicate a shift in the perception of childbirth among modern Chinese women over time, influenced by their increasing social status and the pursuit of self-realization. Implementing strategies such as public education on the health risks associated with pregnancy and delivery, safeguarding women's rights, and creating a supportive environment for mothers may enhance women's willingness to undergo childbirth. RR2-10.2196/preprints.50468.

Sections du résumé

BACKGROUND BACKGROUND
In recent years, women's fertility desire has attracted increasing attention in China.
OBJECTIVE OBJECTIVE
This study aims to detect attitudes toward giving birth among young female users on Douban, a very popular Chinese social media platform.
METHODS METHODS
A total of 2634 valid posts from 2489 users discussing the topic "What does childbirth mean to a woman" on Douban were crawled and retained for analysis. We utilized content and thematic analysis methods to capture users' concepts of childbirth.
RESULTS RESULTS
The findings reveal that a significant majority of users conveyed generally neutral (1060/2634, 40.24%) or negative (1051/2634, 39.90%) attitudes toward childbirth, while only about one-fifth of users expressed positive (523/2634, 19.86%) sentiments. Notably, posts with negative attitudes garnered more replies and likes, and the proportion of posts expressing negativity exhibited fluctuations over time. Health risk (339/2634, 12.87%) emerged as the most frequently cited aspect of childbirth cost, with subjective happiness and the fulfillment of mental needs identified as primary benefits. Surprisingly, only a minimal number of posts (10/2634, 0.38%) touched upon the traditional objective benefits of raising children for old-age care. Thematic analysis results suggest that discussions about fertility on social media platforms might contribute to an exaggerated perception of health risks among women. Additionally, a lack of knowledge about childbirth was observed, partially attributable to longstanding neglect and avoidance of communication on these matters, likely influenced by traditional cultural biases. Moreover, there is a prevailing assumption that women should naturally sacrifice themselves for childbirth and childcare, influenced by the idealization of the female figure. Consequently, women may harbor hesitations about having a baby, fearing the potential loss of their own identity in the process.
CONCLUSIONS CONCLUSIONS
The results indicate a shift in the perception of childbirth among modern Chinese women over time, influenced by their increasing social status and the pursuit of self-realization. Implementing strategies such as public education on the health risks associated with pregnancy and delivery, safeguarding women's rights, and creating a supportive environment for mothers may enhance women's willingness to undergo childbirth.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
RR2-10.2196/preprints.50468.

Identifiants

pubmed: 38180784
pii: v7i1e50512
doi: 10.2196/50512
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e50512

Informations de copyright

©Ting Yang, Yihan Wu, Nuo Han, Tianli Liu. Originally published in JMIR Pediatrics and Parenting (https://pediatrics.jmir.org), 05.01.2024.

Auteurs

Ting Yang (T)

Institute of Population Research, Peking University, Beijing, China.

Yihan Wu (Y)

Graduate School of Education, Peking University, Beijing, China.

Nuo Han (N)

Chinese Academy of Sciences Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
School of Data Science, City University of Hong Kong, Hong Kong SAR, China.

Tianli Liu (T)

Institute of Population Research, Peking University, Beijing, China.

Classifications MeSH