Kobayashi, Takaaki; Nishina, Yuka; Tomoi, Hana; Harada, Ko; Tanaka, Kyuto; Matsumoto, Eiyu; Horimukai, Kenta; Ishihara, Jun; Sasaki, Shugo; Inaba, Kanako; +4 more... Seguchi, Kyosuke; Takahashi, Hiromizu; Salinas, Jorge L; Yamada, Yuji; (2022) Corowa-kun: A messenger app chatbot delivers COVID-19 vaccine information, Japan 2021. Vaccine, 40 (32). pp. 4654-4662. ISSN 0264-410X DOI: https://doi.org/10.1016/j.vaccine.2022.06.007
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Abstract
BACKGROUND: There is a long history in Japan of public concerns about vaccine adverse events. Few studies have assessed how mobile messenger apps affect COVID-19 vaccine hesitancy. METHODS: Corowa-kun, a free chatbot, was created on February 6, 2021 in LINE, the most popular messenger app in Japan. Corowa-kun provides instant, automated answers to 70 frequently asked COVID-19 vaccine questions. A cross-sectional survey with 21 questions was performed within Corowa-kun during April 5-12, 2021. RESULTS: A total of 59,676 persons used Corowa-kun during February-April 2021. Of them, 10,192 users (17%) participated in the survey. Median age was 55 years (range 16-97), and most were female (74%). COVID-19 vaccine hesitancy reported by survey respondents decreased from 41% to 20% after using Corowa-kun. Of the 20% who remained hesitant, 16% (1,675) were unsure, and 4% (364) did not intend to be vaccinated. Factors associated with vaccine hesitancy were: age 16-34 (odds ratio [OR] = 3.7; 95% confidential interval [CI]: 3.0-4.6, compared to age ≥ 65), female sex (OR = 2.4; Cl: 2.1-2.8), and history of a previous vaccine side-effect (OR = 2.5; Cl: 2.2-2.9). Being a physician (OR = 0.2; Cl: 0.1-0.4) and having received a flu vaccine the prior season (OR = 0.4; Cl: 0.3-0.4) were protective. CONCLUSIONS: A substantial number of people used the chabot in a short period. Mobile messenger apps could be leveraged to provide accurate vaccine information and to investigate vaccine intention and risk factors for vaccine hesitancy.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
Research Centre | Covid-19 Research |
PubMed ID | 35750541 |
Elements ID | 181207 |