AI chatbot interventions in combatting marijuana-impaired driving

The role of gender, linguistic style, and hypocrisy induction

Dados Bibliográficos

ID21498331
AutoresYuhosua Ryoo (0000-0001-8153-9320, University of Minnesota, Duluth, autor correspondente), Victoria Halfacre (Southern Illinois University School of Medicine), Eunjin Kim (0000-0003-4007-4461, Annenberg School for Communication and Journalism, University of Southern California), Hye Jin Yoon (0000-0002-8937-0600, University of Georgia)
Ano2025
Volume44
Fascículo7
Páginas1311-1340
Data de publicação2025-10-03
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoInternational Journal of Advertising (JOURNAL)
Identificadores do periódicoISSN: 0265-0487 • E-ISSN: 1759-3948
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/02650487.2025.2452048
OpenAlexW4406739897
IdiomaEN
Citações recebidas3
Referências citadas89

This study explores the effectiveness of AI chatbots in public safety advertising campaigns against marijuana-impaired driving, specifically focusing on the role of hypocrisy induction, gender, and linguistic styles. In our online experiment, participants engaged with a chatbot delivering either hypocrisy-inducing or neutral messages about driving under marijuana influence. The chatbot, characterized as male or female, utilized either formal or casual language. Results revealed that hypocrisy induction is most effective when delivered by a casually speaking female chatbot or a formally speaking male chatbot. The heightened guilt among participants explains the effectiveness of this approach. The Language Expectancy Theory (LET) serves as a theoretical framework, elucidating how the alignment of chatbot gender and linguistic style enhances the hypocrisy induction effect. This research highlights the potency of AI chatbots in leveraging public safety advertising campaigns and offers guidance on optimizing their design by aligning gender and language style with campaign goals

Advertising · Art · Business · Hypocrisy · Linguistics · Literature · Political science · Psychological intervention · AI in Service Interactions · Blood donation and transfusion practices · Law · Psychology · Sentiment Analysis and Opinion Mining · Social Psychology