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Medical Interviewing with a Robot Instead of a Doctor: Who do We Trust More with Sensitive Information?

Published: 01 April 2020 Publication History

Abstract

Patients often do not trust their physicians with confidential, private information. They are worried about judgment, and ultimately this leads to poorer health outcomes. Physicians also do not listen to specific groups of people, biasing healthcare decisions. It may, therefore, be helpful to complement or delegate some of a physician's tasks to a robot. People are more willing to disclose private information to robots, which they find unbiased without negative judgment [2]. Robots can ask all relevant questions regardless of sex, gender, or sexual orientation [11]. This proposal explores the use of robotics within medicine, evaluating patient trust and information disclosure, to supplement and promote unbiased healthcare provider decisions. The experiment will employ a physician to conduct 90 patient interviews between three groups (G) using the standardized Brown Interview Checklist, either with (G1) or without (G2) a proxy robot. Patients interviewed by the robot will be split between those aware (G2a) or unaware (G2b) that a physician will be controlling the robot. We hypothesize that using a physical robot will improve information disclosure with less stress, and perhaps even off-load physician workload for more targeted and appropriate healthcare decisions.

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Cited By

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  • (2024)Effects of Robots’ Character and Information Disclosure on Human–Robot Trust and the Mediating Role of Social PresenceInternational Journal of Social Robotics10.1007/s12369-024-01114-416:4(811-825)Online publication date: 16-Mar-2024
  • (2023)Is a Humorous Robot More Trustworthy?Social Robotics10.1007/978-981-99-8715-3_27(322-335)Online publication date: 3-Dec-2023
  • (2022)Leveraging the Science to Understand Factors Influencing the Use of AI-Powered Avatar in Healthcare ServicesJournal of Technology in Behavioral Science10.1007/s41347-022-00277-z7:4(588-602)Online publication date: 9-Sep-2022
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cover image ACM Conferences
HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
March 2020
702 pages
ISBN:9781450370578
DOI:10.1145/3371382
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 01 April 2020

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Author Tags

  1. doctor-patient relationship
  2. human robot interaction
  3. information disclosure
  4. medical interview

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View all
  • (2024)Effects of Robots’ Character and Information Disclosure on Human–Robot Trust and the Mediating Role of Social PresenceInternational Journal of Social Robotics10.1007/s12369-024-01114-416:4(811-825)Online publication date: 16-Mar-2024
  • (2023)Is a Humorous Robot More Trustworthy?Social Robotics10.1007/978-981-99-8715-3_27(322-335)Online publication date: 3-Dec-2023
  • (2022)Leveraging the Science to Understand Factors Influencing the Use of AI-Powered Avatar in Healthcare ServicesJournal of Technology in Behavioral Science10.1007/s41347-022-00277-z7:4(588-602)Online publication date: 9-Sep-2022
  • (2022)Effect of Robot’s Listening Attitude Change on Self-disclosure of the ElderlyInternational Journal of Social Robotics10.1007/s12369-022-00934-614:9(1935-1950)Online publication date: 12-Oct-2022

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