ArticleBMJ public health2026
Identifying barriers to human papillomavirus vaccination in China: a topic modelling analysis of social media (2018-2024).
Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Study of Human Papillomavirus Vaccine-Related Social Media Content Across Eight Social Media Platforms: Scoping Review of Communication Content, Information Sources, and Analytical Approaches.Journal of medical Internet research · 2026Article
- Analysis of factors influencing HPV vaccination willingness of parents of students in China based on the theory of planned behavior.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The low coverage of human papillomavirus (HPV) vaccination hinders the elimination of cervical cancer in China. This study aimed to investigate barriers to HPV vaccination using social media data to promote vaccine uptake. Methods: Social media posts related to HPV vaccination were analysed on Weibo, China's leading social media platform from 1 May 2018 to 20 April 2024. Machine learning models, including sentence transformer fine-tuning and bidirectional encoder representations from transformers, were employed for topic modelling. Results: From 4 342 736 collected Weibo posts, 817 788 (18.8%) from 610 472 unique users identified barriers to HPV vaccination in mainland China. Key perceived barriers included concerns over adverse effects such as arm pain following vaccination (107 493; 13.1%), adverse effects such as cold and delayed menstruation (77 245; 9.4%) and perceived HPV screening requirement for vaccination and limited vaccine benefits (40 880; 5.0%). Practical barriers predominantly addressed the lack of supply (228 606; 28.0%), age restrictions (135 626; 16.6%) and long waiting time (76 627; 9.4%) for 9-valent vaccine. Temporal analysis revealed fluctuations in barrier prevalence. Conclusions: Artificial intelligence methodologies are feasible and valuable in analysing large-scale, publicly available social media data to improve public health. Our results highlight the importance of addressing both perceived and practical barriers to HPV vaccination and provide actionable insights on targeted strategies for reducing HPV-related diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.