Fostering Emotional Engagement and Sustained Interaction in Care Homes Through Empathetic Human-Robot Conversation

Social isolation is a critical health concern for older adults — especially in institutional care, where limited social interaction is linked with depression, cognitive decline, and poorer physical health. Empathetic human-robot interaction offers a promising avenue to address these emotional and mental health challenges. We report on a two-stage evaluation of an LLM-powered social robot designed to support emotionally attuned conversations with older adults. In a lab study ( \(N=40\) ), the robot achieved high scores on four empathy-related measures. We then deployed a fully autonomous system for 10 weeks in a residential care home (five residents; up to 45 minutes per session). Across repeated interactions, participants showed sustained engagement and predominantly mid-depth self-disclosure, alongside affective trust and occasional cognitive trust. Exploratory analyses indicated that higher empathic appropriateness co-occurred with deeper disclosure and increased over sessions for most participants. To our knowledge, these findings provide early field evidence that autonomous, LLM-driven conversational robots can maintain emotionally supportive dialogue with older adults, fostering emotional engagement, trust, and sustained interaction over time, mechanisms that may contribute to reducing perceived social isolation.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Human-Robot Interaction
Published
2026-09-24
DOI
https://doi.org/10.1145/3840294
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Fostering Emotional Engagement and Sustained Interaction in Care Homes Through Empathetic Human-Robot Conversation

Tony Belpaeme, Maria J. Pinto-Bernal, Kato Boels
ACM Transactions on Human-Robot Interaction
Social Robot Interaction and HRI
article

Fostering Emotional Engagement and Sustained Interaction in Care Homes Through Empathetic Human-Robot Conversation

Tony Belpaeme, Maria J. Pinto-Bernal, Kato Boels
article en

Abstract

Social isolation is a critical health concern for older adults — especially in institutional care, where limited social interaction is linked with depression, cognitive decline, and poorer physical health. Empathetic human-robot interaction offers a promising avenue to address these emotional and mental health challenges. We report on a two-stage evaluation of an LLM-powered social robot designed to support emotionally attuned conversations with older adults. In a lab study ( \(N=40\) ), the robot achieved high scores on four empathy-related measures. We then deployed a fully autonomous system for 10 weeks in a residential care home (five residents; up to 45 minutes per session). Across repeated interactions, participants showed sustained engagement and predominantly mid-depth self-disclosure, alongside affective trust and occasional cognitive trust. Exploratory analyses indicated that higher empathic appropriateness co-occurred with deeper disclosure and increased over sessions for most participants. To our knowledge, these findings provide early field evidence that autonomous, LLM-driven conversational robots can maintain emotionally supportive dialogue with older adults, fostering emotional engagement, trust, and sustained interaction over time, mechanisms that may contribute to reducing perceived social isolation.

ACM Transactions on Human-Robot Interaction
Ghent University (BE)
No poverty
Openalex Percentile: Top 7%
Social Robot Interaction and HRI
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.