Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot: Cross-Sectional Study.

Journal: JMIR mHealth and uHealth
PMID: 38096007

Abstract

BACKGROUND: The COVID-19 pandemic influenced many to consider methods to reduce human contact and ease the burden placed on health care workers. Conversational agents or chatbots are a set of technologies that may aid with these challenges. They may provide useful interactions for users, potentially reducing the health care worker burden while increasing user satisfaction. Research aims to understand these potential impacts of chatbots and conversational recommender systems and their associated design features.

Authors

  • Akanksha Singh
    Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.
  • Benjamin Schooley
    IT & Cybersecurity, Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, United States.
  • Nitin Patel
    Hackensack Meridian Health, Hackensack, NJ, United States.

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