The Portrayal of Cesarean Section on Instagram: Mixed Methods Social Media Analysis

Autor: Rana Islamiah Zahroh, Marc Cheong, Alya Hazfiarini, Martha Vazquez Corona, Fitriana Murriya Ekawati, Ova Emilia, Caroline SE Homer, Ana Pilar Betrán, Meghan A Bohren
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: JMIR Formative Research, Vol 8, p e46531 (2024)
Druh dokumentu: article
ISSN: 2561-326X
DOI: 10.2196/46531
Popis: BackgroundCesarean section (CS) rates in Indonesia are rapidly increasing for both sociocultural and medical reasons. However, there is limited understanding of the role that social media plays in influencing preferences regarding mode of birth (vaginal or CS). Social media provides a platform for users to seek and exchange information, including information on the mode of birth, which may help unpack social influences on health behavior. ObjectiveThis study aims to explore how CS is portrayed on Instagram in Indonesia. MethodsWe downloaded public Instagram posts from Indonesia containing CS hashtags and extracted their attributes (image, caption, hashtags, and objects and texts within images). Posts were divided into 2 periods—before COVID-19 and during COVID-19—to examine changes in CS portrayal during the pandemic. We used a mixed methods approach to analysis using text mining, descriptive statistics, and qualitative content analysis. ResultsA total of 9978 posts were analyzed quantitatively, and 720 (7.22%) posts were sampled and analyzed qualitatively. The use of text (527/5913, 8.91% vs 242/4065, 5.95%; P
Databáze: Directory of Open Access Journals