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ORIGINAL RESEARCH article

Front. Commun.
Sec. Health Communication
Volume 9 - 2024 | doi: 10.3389/fcomm.2024.1420312

An Investigation of Public Trust in Autonomous Humanoid Robot Doctors: A Preparation

Provisionally accepted
Do Kyun D. Kim Do Kyun D. Kim *
  • University of Louisiana at Lafayette, Lafayette, United States

The final, formatted version of the article will be published soon.

    As a preparation for our future healthcare system with artificial intelligence (AI)-based autonomous robots, this study investigated the level of public trust in autonomous humanoid robot (AHR) doctors that would be enabled by AI technology and introduced to the public for the sake of better healthcare accessibility and services in the future. Employing the most frequently adopted scales in measuring patients' trust in their primary care physicians (PCPs), this study analyzed 413 survey responses collected from the general public in the United States and found trust in AHR nearly matched the level of trust in human doctors, although it was slightly lower.Based on the results of data analysis, this study provided explanations about the benefits of using AHR doctors and some proactive recommendations in terms of how to develop AHR doctors, how to implement them in actual medical practices, more frequent exposure of humanoid robots to the public, and the need of interdisciplinary collaboration to enhance public trust in AHR doctors, which is urgently demanded because the placement of such advanced robot technology in the healthcare system is unavoidable as experienced more in these days. The limitations arising from the non-experimental design, a voluntary response sampling through social media, and few theories on communication with humanoid robots remain tasks for future studies.

    Keywords: health technology acceptance, artificial intelligence, autonomous humanoid robots, Patient-doctor communication, robotic healthcare service, Health communication technology

    Received: 19 Apr 2024; Accepted: 24 Sep 2024.

    Copyright: © 2024 Kim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Do Kyun D. Kim, University of Louisiana at Lafayette, Lafayette, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.