Sezgin Ayabakan

Assistant Professor

Faculty/Staff

User reactions to COVID-19 screening chatbots from reputable providers

Alan R. Dennis, Antino Kim, Mohammad Rahimi, Sezgin Ayabakan

Abstract

Objectives
The objective was to understand how people respond to coronavirus disease 2019 (COVID-19) screening chatbots.

Materials and Methods
We conducted an online experiment with 371 participants who viewed a COVID-19 screening session between a hotline agent (chatbot or human) and a user with mild or severe symptoms.

Results
The primary factor driving user response to screening hotlines (human or chatbot) is perceptions of the agent’s ability. When ability is the same, users view chatbots no differently or more positively than human agents. The primary factor driving perceptions of ability is the user’s trust in the hotline provider, with a slight negative bias against chatbots’ ability. Asian individuals perceived higher ability and benevolence than did White individuals.

Conclusions
Ensuring that COVID-19 screening chatbots provide high-quality service is critical but not sufficient for widespread adoption. The key is to emphasize the chatbot’s ability and assure users that it delivers the same quality as human agents.

Journal of the American Medical Informatics Association, 27:11, pp. 1727–1731, November 2020

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Office: Speakman Hall 201B

Email: ayabakan@temple.edu

Office Phone: 215-204-7142

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