Designing Smart Agents to Support Physician-Patient Interactions: The Effect of Varying Communication Styles

This dissertation reports five experiments exploring the use of AI-based smart agents to support physician-patient interactions. In each experiment, a sample of female participants evaluates video tapes of simulated physician-patient interactions in a setting involving early stage breast cancer diagnosis. Experiment 1 manipulates communication style (empathetic/impassive) for both a human physician (played by an actor) and an avatar that mimics the human. Empathetic styles elicit more liking and trust from patients and are also more persuasive. The avatar loses less than the human physician on desirable patient outcomes when communication style changes from empathetic to impassive. A mediation analysis shows that the communication style and physician type effects flow serially through liking and trust to persuasion. Experiment 2 reports an extended replication, adding a new avatar with less resemblance to the human physician. The findings match those of Experiment 1: both avatars have similar effects on liking, trust, and persuasion and are similarly anthropomorphized. Experiment 3 examines whether the patient's mindset (hope/fear about the cancer prognosis) influences likely patient outcomes. The mindset manipulation does not influence patient outcomes, but we find support for the core serial mediation model (from liking to trust to persuasion). Experiment 4 explores whether it matters how the avatar is deployed. Introducing the avatar as the physician's assistant lowers its evaluations perhaps because the patients feel deprioritized. The human physician is evaluated significantly higher on all outcome dimensions. Experiments 1-4 focused on the first phase of a standard three-phased physician-patient interaction protocol. Experiment 5 examines communication style (empathetic/ impassive) and physician type (human/avatar) effects across the three sequential phases. Patient outcomes improve monotonically over the three interaction phases across all study conditions. Overall, our studies show that an empathetic communication style is more effective in eliciting higher levels of liking, trust, and persuasion. The human physician and the avatar elicit similar levels of these desirable patient interaction outcomes. The avatar loses less when communication style changes from empathetic to impassive, suggesting that patients may have lower expectations of empathy from avatars. Thus, if carefully deployed, smart agents acting as physicians' avatars may effectively support physician-patient interactions.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Business, Executive Business Research

Department dc:contributor.department

Business

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2022

Author dc:creator

• Ravella, Haribabu

Chair dc:contributor.committeechair

• Chakravarti, Dipankar

Committee members dc:contributor.committeemember

• Bagchi, Rajesh
• Jiang, Juncai
• Herr, Paul Michael

• Marketing
• Smart Agents
• Artificial Intelligence (AI) Agents
• Human-Machine Interactions
• Communication Style
• Empathy
• Liking
• Trust
• Persuasion
• Hope
• Fear
• Physician-Patient Interactions
• Healthcare

Statement dc:rights

• Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:33489

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/107853