Welcome

The proliferation of anti-vaccination arguments, especially on the Internet and social media, is a threat to the success of many immunisation programmes. Effective rebuttal of such contrarian arguments requires an approach that goes beyond addressing flaws in the arguments, by also considering the attitude roots—i.e, the underlying psychological attributes driving a person’s belief—of opposition to vaccines. Through a systematic literature review of 152 scientific articles and thematic analysis of 2,414 anti-vaccination arguments, we developed a hierarchical taxonomy of anti-vaccination arguments that not only identifies 62 common and recurring themes, but, crucially, relates the arguments to 11 attitude roots that explain why an individual might express opposition to vaccination.

This taxonomy has been validated in both linguistic and psychological terms. First, we used a dataset of COVID-19 anti-vaccine misinformation to develop a computational model through a combination of human coding and machine learning algorithms. The human coders identified attitude roots for a sample of 582 debunked claims about COVID-19 vaccinations, and the natural language processing model predicted these assigned roots with considerable skill. Second, we recruited 1250 participants from the British general population to measure their endorsements of anti-vaccination arguments included in the taxonomy. We found that an single factor model accounting for the 11 attitude roots was an optimal solution in a factor analysis,  and that anti-vaccination argument endorsement was significantly predicted by 11 well-established psychological measures expected to be associated with the attitude roots. In addition, using all the attitude roots, we identified 4 anti-vaccination and 4 pro-vaccination profiles amongst our participants’ responses to the psychological variables. Overall, this taxonomy serves as a validated theoretical framework to link expressed opposition of vaccines to their underlying psychological processes.