Abstract
During the COVID-19 pandemic, the emergence of the infodemic and vaccine hesitancy posed a significant challenge to adequate vaccine uptake. In response, conversational AI services such as chatbots have become an increasingly popular tool in the field of health ser-vice delivery and communication to increase individuals’ health literacy and vaccination intention. However, few studies have performed a rigorous evaluation of the effectiveness of chatbots as a means of improving vaccine confidence and acceptance. In Thailand, Hong Kong, and Singapore, from February 11th to June 30th, 2022, we conducted multisite randomised controlled trials (RCT) on 2,045 adults with unvaccinated dependent family members who were vulnerable (i.e., seniors) and had been refusing/delaying vaccination, or newly eligible for vaccines (i.e., children). After a week of using multilingual COVID-19 vaccine chatbots, the differences in vaccine confidence – measured by the Vaccine Confidence Index – and acceptance were compared between the intervention and control groups. Factors of vaccine confidence and acceptance were explored. Compared to non-users, a smaller pro-portion of chatbot users reported a decrease of confidence in vaccine effectiveness in the Thailand child group [Intervention: 4·3 % vs. Control: 17%, P=0·023] and Hong Kong child group [10% vs. 26%, P=0·034], and of vaccine effectiveness in reducing severe conditions in the Thailand senior group [12% vs. 21%, P=0·024].
There was no significant change in vaccine confidence or acceptance in the Singapore child group and Hong Kong senior group. Employing the RE-AIM framework, process evaluation indicated strong acceptance and implementation support for vaccine chatbots from stakeholders, with high levels of sustainability and scalability. This study was the first multisite, parallel RCT on vaccine chatbots and reported mixed success in improving vaccine confidence and acceptance among highly hesitant Asian subpopulations. Deploying chatbots as a complement to existing vaccination strategies could identify users’ main concerns for rejecting/delaying vaccination and facilitate a targeted communication and engagement strategy.
Acknowledgement
The report has been prepared by Ms. Chayapat Rachatan, Ms. Madison Silzle and advised by Ms.Saudamini Dabak from the Health Intervention and Technology Assessment Program (HITAP), Ministry of Public Health, Thailand. We thank Kristi Yoonsup Lee, Vivian Hanxiao Kong, Shirley L. L. Kwok, Zhengdong Wu, Eric H.Y. Lau, Kathy Leung, Joseph T. Wu, and Leesa Lin from the Laboratory of Data Discovery for Health (D24H) and The University of Honk Kong (HKU) for their leadership on this project and contributions to the analysis and manuscript. We thank Minah Park and Alex Cook from the National University of Singapore (NUS), Aly Passanante, Ed Pertwee, and Heidi J. Larson from the London School of Hygiene and Tropical Medicine (LSHTM), and Javier A. Elkin from the World Health Organization (WHO) for their inputs on the study.
We thank Supatnuj Sorndamrih, Wattaporn Thanomsing, Nicha Krishnamra and Sindh R from the Thai Health Promotion Foundation (ThaiHealth) for their support on using the chatbot in Thailand; Dr. Yot Teerawattananon, Assoc. Prof. Wanrudee Isaranuwatchai, Dr. Pritaporn Kingkaew and Ms. Benjarin Santatiwongchai from HITAP for their inputs on the study.
The findings, interpretations and conclusions expressed in this report do not necessarily reflect the views of the funding or participating agencies.
