The Effect of Message Framing on the Emotional State in a Statically Visualized Chatbot Conversation Towards Vaccination

The COVID-19 vaccine is one of the critical components in combating the virus and ending the current pandemic. Although billions of people have been vaccinated and vaccines have been proven safe, misinformation is a factor that keeps people from getting vaccinated. Since vaccination is a complex and personal topic, misinformation can alter the person’s emotional state and make the person unsure in accepting the vaccine. The communication strategy of authorities and governments must tackle the topics around misinformation. Message framing is an approach that frames parts of the sentences in a positive/benefits (gain) or negative/costs (loss) way to influence people’s emotional state and, consequently, decision making. Therefore, it is an applied approach in health communication in general. Whether it works in a chatbot-based vaccine communication on COVID-19 remains open and is the subject of this paper. This paper investigated the effect of framed messages by (1) developing a mockup prototype, including (2) a set of framed messages based on the major controversial concerns around COVID-19 vaccination and (3) testing it using an online questionnaire. The questionnaire had a total response of 116 participants randomized into two groups of 58 each for gain and loss-framed messages. The results showed a significance on the emotional state anxiety (p=.035) for the gain-framed messages, which positively impacted the emotional state of these respondents because they reported being less anxious after visualizing the mockup prototype. No further significance was observed for the other emotional states. Overall, the respondents rated the mockup prototype positively.

Brufatto Pereira, Eliane, 2021

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Pimmer, Christoph, Martin, Andreas, Pande, Charuta
Keywords
Views: 19 - Downloads: 0
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Brufatto Pereira, Eliane
Betreuende Dozierende
Pimmer, Christoph, Martin, Andreas, Pande, Charuta
Publikationsjahr
2021
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten