JMIR Publications

ABSTRACT

Background:

The human papillomavirus (HPV) vaccine is a major advancement in cancer prevention and this primary prevention tool has the potential to reduce and eliminate HPV-associated cancers; however, the safety and efficacy of vaccines in general and HPV vaccine specifically have come under attack, particularly through the spread of misinformation on social media. The popular social media platform Instagram represents a significant source of exposure to health (mis)information; one in three U.S. adults use Instagram.

Objective:

To characterize pro- and anti-HPV vaccine networks on Instagram, and to describe misinformation within the anti-HPV vaccine network.

Methods:

From April to December 2018, publicly available English-language Instagram posts containing hashtags #HPV, #HPVVaccine or #Gardasil were collected using Netlytic software (n=16,607). We randomly selected 10% of the sample and content analyzed relevant posts (n=580) for text, image, social networking features, and holistic attributes (e.g., sentiments, personal stories). Among anti-vaccine posts, we organized elements of misinformation within four broad dimensions: 1) misinformation theoretical domains, 2) vaccine debate topics, 3) evidence base, and 4) health beliefs. We conducted univariate, bivariate, and network analyses on the sub-sample of posts to quantify role and position of individual posts in the network.

Results:

Compared to pro-vaccine posts (n=324; 55.9%), anti-vaccine posts (n=256; 44.1%) were more likely to originate from individuals (64.1% anti-vaccine versus 25.0% pro-vaccine; P<.001) and include personal narrative (37.1% versus 25.6%; P=.003). In the anti-vaccine network, core misinformation characteristics included mentioning #Gardasil, purporting to reveal a lie (i.e., concealment), conspiracy theories, unsubstantiated claims, and risk of vaccine injury. Information/resource posts clustered around misinformation domains including falsification, nanopublications, and vaccine-preventable disease; whereas personal narrative posts clustered around different domains of misinformation, including concealment (i.e., revealing lies), injury, and conspiracy theories. The most liked post (n=6,634 likes) in our full sub-sample was a positive personal narrative post, created by a non-health individual; the most liked post (n=5,604 likes) in our anti-vaccine sub-sample was an informational post created by a health individual.

Conclusions:

Identifying characteristics of misinformation related to HPV vaccine on social media will inform targeted interventions (e.g., network opinion leaders) and help sow corrective information and stories tailored to different falsehoods.