Towards Digital Empathy in Healthcare Chatbots: A Conceptual Framework and Empirical Study

Empathy is a crucial element of effective healthcare communication, with profound effects on patient experience and treatment outcomes. However, the increasing pressures on healthcare providers often push empathy to the sidelines. Conversational agents like chatbots offer a possible solution with their potential to integrate empathy and scalability. Yet, disparities in their design and understanding of empathy can lead to less appropriate and satisfying user responses. This research develops a comprehensive framework for empathy in healthcare contexts and assesses its application in text-based healthcare chatbots. Conducted as an online experiment with 1'000 participants who have chronic conditions, the study examines the effects of distinct verbal empathic expressions (i.e., empathic self-awareness and active listening) displayed by a healthcare chatbot in a medical interview scenario. This research aims to foster an effective healthcare environment and improve patient-chatbot-interactions by enhancing the understanding and implementation of digital empathy in healthcare chatbots.

Publication Details

Journal
Journal of the Association for Information Systems
Published
2024-12-15
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards Digital Empathy in Healthcare Chatbots: A Conceptual Framework and Empirical Study

Journal of the Association for Information Systems
AI in Service Interactions
article

Towards Digital Empathy in Healthcare Chatbots: A Conceptual Framework and Empirical Study

article en

Abstract

Empathy is a crucial element of effective healthcare communication, with profound effects on patient experience and treatment outcomes. However, the increasing pressures on healthcare providers often push empathy to the sidelines. Conversational agents like chatbots offer a possible solution with their potential to integrate empathy and scalability. Yet, disparities in their design and understanding of empathy can lead to less appropriate and satisfying user responses. This research develops a comprehensive framework for empathy in healthcare contexts and assesses its application in text-based healthcare chatbots. Conducted as an online experiment with 1'000 participants who have chronic conditions, the study examines the effects of distinct verbal empathic expressions (i.e., empathic self-awareness and active listening) displayed by a healthcare chatbot in a medical interview scenario. This research aims to foster an effective healthcare environment and improve patient-chatbot-interactions by enhancing the understanding and implementation of digital empathy in healthcare chatbots.

Journal of the Association for Information Systems
Quality Education
Openalex Percentile: Top 56%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.