Conference paper
Medical Interviewing with a Robot Instead of a Doctor Who Do we Trust More with Sensitive Information?
HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, pp 570-572
01 Apr 2020
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.
Metrics
Details
- Title
- Medical Interviewing with a Robot Instead of a Doctor Who Do we Trust More with Sensitive Information?
- Creators
- Shawn Joshi - Drexel UniversityEwart J. de Visser - United States Air Force AcademyBenjamin Abramoff - University of PennsylvaniaHasan Ayaz - Drexel University
- Publication Details
- HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, pp 570-572
- Conference
- HRI '20: 2020 ACM/IEEE International Conference on Human-Robot Interaction (Cambridge, United Kingdom, 23 Mar 2020–26 Mar 2020)
- Series
- ACM IEEE International Conference on Human-Robot Interaction; 2020
- Publisher
- Assoc Computing Machinery
- Number of pages
- 3
- Resource Type
- Conference paper
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000643728500188
- Scopus ID
- 2-s2.0-85083203205
- Other Identifier
- 991019169163704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Cybernetics
- Robotics