Fact-Checking #Breastfeeding: Analyzing TikTok Videos Related to Breastfeeding Information.

Abstract

Objective: To systematically characterize and fact-check breastfeeding-related content on TikTok and assess its accuracy against established evidence-based recommendations.

Design: This study employed quantitative content analysis to examine TikTok videos tagged with #breastfeeding to quantify breastfeeding information patterns, engagement metrics, and creator types. Only videos sharing breastfeeding information in English (regardless of country) were included. Videos were coded using a predefined framework developed by the study authors.

Main outcome measures: Engagement metrics, creator type, and video accuracy.

Analysis: Interrater reliability was calculated using Cohen's kappa. Descriptive statistics were used to determine the frequency of videos in each category. A 1-way analysis of variance was applied to assess differences in engagement between evidence-based, non-evidence-based, or misinformation videos. Multivariate analysis of variance was performed to analyze differences in engagement based on video accuracy.

Results: Of the 224 videos analyzed, 65% were classified as evidence-based, while 32% were non-evidence-based. Misinformation outperformed the other categories in shares, saves, and views. No significant differences in engagement metrics were found between evidence-based and non-evidence-based videos.

Conclusions and implications: These findings offer insights into how breastfeeding information is portrayed on TikTok and may inform strategies to improve the dissemination of accurate, evidence-based content on social media platforms.