Open AccessUnderstanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets
Author(s) -
Siru Liu,
Jialin Liu
Publication year - 2021
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/28118
Subject(s) - covid-19 , psychology , content analysis , behavioural sciences , construct (python library) , theory of planned behavior , coding (social sciences) , herd immunity , sentiment analysis , social psychology , computer science , medicine , natural language processing , artificial intelligence , control (management) , statistics , sociology , vaccination , infectious disease (medical specialty) , social science , disease , pathology , immunology , psychotherapist , mathematics , programming language
Background Acceptance rates of COVID-19 vaccines have still not reached the required threshold to achieve herd immunity. Understanding why some people are willing to be vaccinated and others are not is a critical step to develop efficient implementation strategies to promote COVID-19 vaccines. Objective We conducted a theory-based content analysis based on the capability, opportunity, motivation–behavior (COM-B) model to characterize the factors influencing behavioral intentions toward COVID-19 vaccines mentioned on the Twitter platform. Methods We collected tweets posted in English from November 1-22, 2020, using a combination of relevant keywords and hashtags. After excluding retweets, we randomly selected 5000 tweets for manual coding and content analysis. We performed a content analysis informed by the adapted COM-B model. Results Of the 5000 COVID-19 vaccine–related tweets that were coded, 4796 (95.9%) were posted by unique users. A total of 97 tweets carried positive behavioral intent, while 182 tweets contained negative behavioral intent. Of these, 28 tweets were mapped to capability factors, 155 tweets were related to motivation, 23 tweets were related to opportunities, and 74 tweets did not contain any useful information about the reasons for their behavioral intentions (κ=0.73). Some tweets mentioned two or more constructs at the same time. Tweets that were mapped to capability ( P <.001), motivation ( P <.001), and opportunity ( P =.03) factors were more likely to indicate negative behavioral intentions. Conclusions Most behavioral intentions regarding COVID-19 vaccines were related to the motivation construct. The themes identified in this study could be used to inform theory-based and evidence-based interventions to improve acceptance of COVID-19 vaccines.