Bridging the health literacy gap through AI chatbot design

The Impact of Gender and Doctor Cues on Chatbot Trust and Acceptance

Bibliographic Data

ID6431215
AuthorsEunjoo Jin (0000-0003-4058-922X), Yuhosua Ryoo (0000-0001-8153-9320), Woojin Kim (0000-0001-5865-4654), Y Greg Song (0000-0002-9821-4263)
Year2024
Volume35
Issue3
Pages1299-1329
Publication date2024-09-16
Open AccessYes
TypeARTICLE
VenueInternet Research (JOURNAL)
Journal identifiersISSN: 1066-2243 • E-ISSN: 2054-5657
PublisherEmerald Publishing Limited (PUBLISHER • GB)
DOI10.1108/intr-08-2023-0702
OpenAlexW4402807928
LanguageEN
Citations received8
References cited87

Purpose Notwithstanding their potential benefits especially for individuals with low health literacy, users are still somewhat skeptical about the reliability of healthcare chatbots. The present study aims to address this challenge by investigating strategies to enhance users’ cognitive and emotional trust in healthcare chatbots. Particularly, this study aims to understand the effects of chatbot design cues in increasing trust and future chatbot use intention for low health literacy users. Design/methodology/approach We conducted two experimental studies with a final sample of 327 (Study 1) and 241 (Study 2). Three different chatbots were developed (Chatbot design: Bot vs Male-doctor vs Female-doctor). Participants were asked to have a medical consultation with the chatbot. Participants self-reported their health literacy scores. The PROCESS model 7 was used to analyze the hypotheses. Findings The results showed that the female-doctor cues elicited greater cognitive and emotional trust, whereas the male-doctor cues only led to greater cognitive trust (vs bot-like cues). Importantly, this study found that users’ health literacy is a significant moderating factor in shaping cognitive and emotional trust. The results indicated that both the female and male-doctor cues’ positive effects on cognitive trust were significant for those with lower levels of health literacy. Furthermore, the positive effect of the female-doctor cues on emotional trust was also significant only for those whose health literacy level was low. The increased cognitive and emotional trust led to greater future intention to use the chatbot, confirming significant moderated mediation effects. Originality/value Despite the strong economic and educational benefits of healthcare chatbots for low health literacy users, studies examining how healthcare chatbot design cues affect low health literate users surprisingly remained scarce. The results of this study suggest that healthcare chatbots can be a promising technological intervention to narrow the health literacy gap when aligned with appropriate design cues

Bridging (networking · Chatbot · Literacy · Medical education · Pedagogy · World Wide Web · AI in Service Interactions · Computer Science · Digital Mental Health Interventions · Medicine · Mobile Health and mHealth Applications · Psychology

Tools

Open DOI