Background: Despite being committed to the immunization agenda set by the WHO, Italy is currently experiencing decreasing vaccination rates and increasing incidence of vaccine-preventable diseases. Our aim is to analyze Italian online debates on pediatric immunizations through a content analytic approach in order to quantitatively evaluate and summarize users' arguments and information sources. Methods: Threads were extracted from 3 Italian forums. Threads had to include the keyword Vaccin* in the title, focus on childhood vaccination, and include at least 10 posts. They had to have been started between 2008 and June 2014. High inter-coder reliability was achieved. Exploratory analysis using k-means clustering was performed to identify users' posting patterns for arguments about vaccines and sources. Results: The analysis included 6544 posts mentioning 6223 arguments about pediatric vaccinations and citing 4067 sources. The analysis of argument posting patterns included users who published a sufficient number of posts; they generated 85% of all arguments on the forum. Dominating patterns of three groups were identified: (1) an anti-vaccination group (n= 280) posted arguments against vaccinations, (2) a general pro-vaccination group (n= 222) posted substantially diverse arguments supporting vaccination and (3) a safety-focused pro-vaccination group (n= 158) mainly forwarded arguments that questioned the negative side effects of vaccination. The anti-vaccination group was shown to be more active than the others. They use multiple sources, own experience and media as their cited sources of information. Medical professionals were among the cited sources of all three groups, suggesting that vaccination-adverse professionals are gaining attention. Conclusions: Knowing which information is shared online on the topic of pediatric vaccinations could shed light on why immunization rates have been decreasing and what strategies would be best suited to address parental concerns. This suggests there is a high need for developing automated approaches to detect misleading or false information on the Internet.
Bibliographical noteFunding Information:
The authors would like to thank the hosts of the three forums (alfemminile.com, nostrofiglio.it, and pianetamamma.it) for giving their permission to extract the data. They also wish to thank Teresa Cafaro, Ilaria Mammolo, Geo Medolago and Jessica Buzzolini for their support during the coding process and Dr. Uwe Hartung for his precious comments during the development of the codebook. The authors are grateful to the Swiss National Science Foundation (SNSF) for supporting their research.
© 2015 Elsevier Ltd.
- Anti-vaccination movement
- Childhood vaccinations
- Cluster analysis
- Content analysis
- Online forums