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タイトル: Understanding Human Papillomavirus Vaccination Hesitancy in Japan Using Social Media: Content Analysis
著者: Liu, Junyu
Niu, Qian
Nagai-Tanima, Momoko
Aoyama, Tomoki  kyouindb  KAKEN_id  orcid https://orcid.org/0009-0002-5172-5477 (unconfirmed)
キーワード: human papillomavirus
HPV
HPV vaccine
vaccine confidence
large language model
stance analysis
topic modeling
発行日: 11-Feb-2025
出版者: JMIR Publications Inc.
誌名: Journal of Medical Internet Research
巻: 27
論文番号: e68881
抄録: Background: Despite the reinstatement of proactive human papillomavirus (HPV) vaccine recommendations in 2022, Japan continues to face persistently low HPV vaccination rates, which pose significant public health challenges. Misinformation, complacency, and accessibility issues have been identified as key factors undermining vaccine uptake. Objective: This study aims to examine the evolution of public attitudes toward HPV vaccination in Japan by analyzing social media content. Specifically, we investigate the role of misinformation, public health events, and cross-vaccine attitudes (eg, COVID-19 vaccines) in shaping vaccine hesitancy over time. Methods: We collected tweets related to the HPV vaccine from 2011 to 2021. Natural language processing techniques and large language models (LLMs) were used for stance analysis of the collected data. Time series analysis and latent Dirichlet allocation topic modeling were used to identify shifts in public sentiment and topic trends over the decade. Misinformation within opposed-stance tweets was detected using LLMs. Furthermore, we analyzed the relationship between attitudes toward HPV and COVID-19 vaccines through logic analysis. Results: Among the tested models, Gemini 1.0 pro (Google) achieved the highest accuracy (0.902) for stance analysis, improving to 0.968 with hyperparameter tuning. Time series analysis identified significant shifts in public stance in 2013, 2016, and 2020, corresponding to key public health events and policy changes. Topic modeling revealed that discussions around vaccine safety peaked in 2015 before declining, while topics concerning vaccine effectiveness exhibited an opposite trend. Misinformation in topic "Scientific Warnings and Public Health Risk" in the sopposed-stance tweets reached a peak of 2.84% (47/1656) in 2012 and stabilized at approximately 0.5% from 2014 onward. The volume of tweets using HPV vaccine experiences to argue stances on COVID-19 vaccines was significantly higher than the reverse. Conclusions: Based on observation on the public attitudes toward HPV vaccination from social media contents over 10 years, our findings highlight the need for targeted public health interventions to address vaccine hesitancy in Japan. Although vaccine confidence has increased slowly, sustained efforts are necessary to ensure long-term improvements. Addressing misinformation, reducing complacency, and enhancing vaccine accessibility are key strategies for improving vaccine uptake. Some evidence suggests that confidence in one vaccine may positively influence perceptions of other vaccines. This study also demonstrated the use of LLMs in providing a comprehensive understanding of public health attitudes. Future public health strategies can benefit from these insights by designing effective interventions to boost vaccine confidence and uptake.
著作権等: ©Junyu Liu, Qian Niu, Momoko Nagai-Tanima, Tomoki Aoyama. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.02.2025.
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
URI: http://hdl.handle.net/2433/292399
DOI(出版社版): 10.2196/68881
PubMed ID: 39933163
出現コレクション:学術雑誌掲載論文等

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