Online Health Communities: The Impact of AI Conversational Agents on Users

Alain Osta, Angelika Kokkinaki, Charbel Chedrawi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The literature lacks evidence on the acceptability of AI conversational agents (chatbots) and the motivations for their adoption in healthcare industry. This paper aims to examine the acceptance of these chatbots based on the UTAUT model in Online Health Communities (OHCs) and to explore what kind of impact these particular features have on the users’ intentions, and the actual use of these communities. Based on a quantitative methodology approach, we rely on the UTAUT model to study OHCs users’ behavior and intentions towards such AI conversational agents/chatbots. The study shows that the UTAUT has proved to be a strong and reliable model for evaluating the adoption and application of AI conversational agents (chatbots) in OHCs. A questionnaire was employed to collect data, and respondents are chosen using the cluster sampling approach. On a 7 Likert scale, respondents were asked to select which choice best suited their reaction to any of the topics presented. A total of 632 answers from 62 countries were received, with 443 of them being complete. Many tests were used to examine the data such as the bivariate and multivariate analysis. Since the returned p-value for most of the hypotheses tested was 0.05, the majority of the hypotheses tested were accepted. Findings showed the interrelations between AI conversational agents/chatbots and OHCs on users’ Behavioral Intention (BI). The main constructs of the UTAUT model (Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions) had a significant impact on the participants’ BI and Usage Behavior (UB) for AI conversational agents/chatbots in OHCs. As for moderators, gender and age had no effect on BI and UB. Understanding the main factors that have a significant impact on users’ intentions to use chatbots in OHCs determines the significance of those results.

Original languageEnglish
Title of host publicationInformation Systems - 18th European, Mediterranean, and Middle Eastern Conference, EMCIS 2021, Proceedings
EditorsMarinos Themistocleous, Maria Papadaki
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages14
ISBN (Print)9783030959463
Publication statusPublished - 2022
Event18th European, Mediterranean, and Middle Eastern Conference on Information Systems, EMCIS 2021 - Virtual, Online
Duration: 8 Dec 20219 Dec 2021

Publication series

NameLecture Notes in Business Information Processing
Volume437 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356


Conference18th European, Mediterranean, and Middle Eastern Conference on Information Systems, EMCIS 2021
CityVirtual, Online


  • AI conversational agents
  • Chatbots
  • Online Health Communities


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