| Literature DB >> 35103579 |
H Fues Wahl1, B Wikman Erlandson2, C Sahlin1, M Nyaku3, G Benĉina4.
Abstract
Vaccine hesitancy is listed as one of the top 10 global health threats by the WHO. Existing studies investigating the relationship between vaccine hesitancy and social media have found that misinformation and vaccine concerns on social media can cause significant declines in vaccine coverage rates. The objective of this study was to provide insight into the dynamics of vaccine messages on Twitter in Scandinavia (Denmark, Norway, Sweden), by analyzing tweets in local languages during 2019. A validated measure, the 5C scale, was used to map relevant predictors of vaccination behavior, capturing the factors confidence (in vaccines and the system that delivers them), complacency (not perceiving diseases as high risk), constraints (structural and psychological barriers), calculation (engagement in extensive information searching) and collective responsibility (willingness to protect others). A total of 1794 tweets met the inclusion criteria (DK: 48%, NO: 15%, SE: 37%), predominantly tweeted by private users (86%). The HPV vaccine was mentioned in 81% of tweets. Tweets were classified as expressing confidence (61%), complacency (18%), constraints (15%), calculation (15%), and collective responsibility (4%). Confidence in vaccines and the system that delivers them was expressed in 57%. A lack of confidence was expressed in 4% of all tweets, in combination with calculation in 39%. Analyzing public sentiment toward vaccination on Twitter is a useful tool to leverage for better understanding of the dynamics behind vaccine hesitancy. This analysis could provide actionable information for healthcare professionals and public health authorities to mitigate online misinformation and public vaccine concerns.Entities:
Keywords: 5C model; Social media; Twitter; medicine and media; sentiment analysis; vaccination; vaccine hesitancy
Mesh:
Substances:
Year: 2022 PMID: 35103579 PMCID: PMC8993101 DOI: 10.1080/21645515.2022.2026711
Source DB: PubMed Journal: Hum Vaccin Immunother ISSN: 2164-5515 Impact factor: 3.452
Descriptive information mapped for each tweet
| General information | Language: Swedish, Norwegian, Danish Private (private individual account, i.e., cannot be classified under any of the below categories) Authority (e.g., Public Health Agency) News Agency Other organization (e.g., patient organization, hospital, quality of care registers etc.) |
| Vaccine information | HPV vaccine
Stratified by male and female, if relevant Stratified by adult and child, if relevant |
The 5C scale, measuring psychological antecedents of vaccination (Betsch et al.[28]). Each tweet was classified based on whether the author agreed, disagreed, or had a neutral sentiment in relation to the 5C item
| Confidence | Vaccinations are effective ( Regarding vaccines, I am confident that public authorities decide in the best interest of the community ( |
| Complacency | My immune system is so strong, it also protects me against diseases ( Vaccine-preventable diseases are not so severe that I should get vaccinated ( |
| Constraints | For me, it is inconvenient to receive vaccinations ( Visiting the doctor’s makes me feel uncomfortable; this keeps me from getting vaccinated ( Willingness to pay/affordability prevents me from getting vaccinated* ( Physical constraints prevent me from getting vaccinated* ( |
| Calculation | For each and every vaccination, I closely consider whether it is useful for me ( It is important for me to fully understand the topic of vaccination before I get vaccinated ( |
| Collective responsibility | I get vaccinated because I can also protect people with a weaker immune system ( Vaccination is a collective action to prevent the spread of diseases ( |
*Sub-items related to affordability/willingness-to-pay and physical constraints were not part of the original scale but were added to capture these constraints.
(R): Item with (R) is reverse coded in relation to sub-items.
Figure 1.Flow chart for inclusion and exclusion of tweets.
Figure 2.Breakdown of tweets by language, vaccine information, and author.
Figure 3.5C classification by language and C.
Figure 4.Tweets classified within confidence.