A randomized pilot study evaluating socially assistive robot effects on patient engagement and care quality

Healthcare faces significant challenges, including workforce shortages and increasing demands. Socially assistive robots (SARs) have emerged as potential solutions to augment care, but their implementation in hospital wards remains largely unexplored. We conducted a randomized external pilot study (ISRCTN Registry, ISRCTN96689284, registered 24/02/2022) evaluating SAR intervention feasibility and effects on patient engagement and perceived quality of care (co-primary outcomes) and health-related quality of life (secondary outcome) in surgical wards. Patients (N = 229) at University Medical Center Maribor were allocated to SAR intervention (standard care + SAR) or control groups (standard care only). The SAR utilized validated, story-driven conversational capabilities providing standardized patient education, support, and basic triage through predefined dialog flows. While overall effects on patient engagement and perceived care quality were limited, the intervention showed positive impact on pain management. Contextual factors moderated intervention effects, highlighting SAR potential in specific domains. No substantial negative effects were detected. High retention rates demonstrated practical feasibility of SAR implementation in surgical settings.

Authors

Institutions

Publication Details

Journal
npj Digital Medicine
Published
2025-12-02
DOI
https://doi.org/10.1038/s41746-025-02117-9
Citations
1
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
2.44

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A randomized pilot study evaluating socially assistive robot effects on patient engagement and care quality

Urška Smrke, Izidor Mlakar, Nejc Plohl, Valentino Šafran et al.
1 citations
npj Digital Medicine
Social Robot Interaction and HRI
2.44
article

A randomized pilot study evaluating socially assistive robot effects on patient engagement and care quality

Urška Smrke, Izidor Mlakar, Nejc Plohl, Valentino Šafran, Vojko Flis, Samo Horvat, Igor Robert Roj, Bojan Ilijevec
article en
1 citations

Abstract

Healthcare faces significant challenges, including workforce shortages and increasing demands. Socially assistive robots (SARs) have emerged as potential solutions to augment care, but their implementation in hospital wards remains largely unexplored. We conducted a randomized external pilot study (ISRCTN Registry, ISRCTN96689284, registered 24/02/2022) evaluating SAR intervention feasibility and effects on patient engagement and perceived quality of care (co-primary outcomes) and health-related quality of life (secondary outcome) in surgical wards. Patients (N = 229) at University Medical Center Maribor were allocated to SAR intervention (standard care + SAR) or control groups (standard care only). The SAR utilized validated, story-driven conversational capabilities providing standardized patient education, support, and basic triage through predefined dialog flows. While overall effects on patient engagement and perceived care quality were limited, the intervention showed positive impact on pain management. Contextual factors moderated intervention effects, highlighting SAR potential in specific domains. No substantial negative effects were detected. High retention rates demonstrated practical feasibility of SAR implementation in surgical settings.

npj Digital MedicineVol. 8(1)
University of Maribor (SI), University Clinical Centre Maribor (SI)
European Commission, Javna Agencija za Raziskovalno Dejavnost RS
Openalex Percentile: Top 8%
Social Robot Interaction and HRI
2.44
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.