Usability and Acceptance of a Social Robot in People With Multiple Sclerosis: Comparative Cross-Sectional Study.
6 affiliations
- 1neuroBRITE Research Center, Italian Multiple Sclerosis Foundation, Via Operai 40, Genoa, 16149, Italy, +39 010 2713306.
- 2R&I Lab, Engineering Ingegneria Informatica S.p.A, Rome, Lazio, Italy.
- 3Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, Genoa, Italy.
- 4Department of Life Science, University of Siena, Siena, Italy.
- 5Italian Multiple Sclerosis Foundation, Genoa, Italy.
- 6AISM Rehabilitation Service, Italian Multiple Sclerosis Society, Genoa, Italy.
Abstract
Background
Socially assistive robotics (SAR) is an emerging field integrating robotics, medicine, cognitive and social sciences, and neuroscience. Its potential in multiple sclerosis (MS) remains largely unexplored, although MS affects sensory-motor, cognitive, and psychological domains where SAR could offer substantial benefits.Objective
This study aimed to evaluate the usability of a humanoid robot in people with MS, compare it with age-matched healthy individuals (HIs), and explore usability predictors. Automated written-language analysis was tested as a complementary approach.Methods
In this 2025 cross-sectional study at the Italian MS Foundation laboratory, 20 people with MS (mean age 51.4, SD 11.0 years; n=13, 65% female; mean education 13.0, SD 3.4 years) and 20 age-matched HIs (mean age 47.3, SD 10.1 years; n=12, 60% female; mean education 14.8, SD 2.2 years) completed 4 predefined tasks with the robot Pepper. Usability was assessed using the System Usability Scale (SUS). Attitudes toward robots, robot-related factors, and task-related effort were measured with the General Attitudes Towards Robots Scale (GAToRS), Godspeed questionnaire, and NASA-TLX, respectively. Psychological variables (eg, personality traits from the Italian Ten-Item Personality Inventory [I-TIPI]) and clinical characteristics for people with MS (eg, cognitive functions via the app DIGICOG-MS, upper-limb difficulties with the Arm Function in Multiple Sclerosis [AMSQ]) were collected. Written responses to open-ended questions were analyzed using natural language processing (NLP).Results
SUS scores exceeded the standard cut-off in both groups, with no between-group differences (people with MS: mean 81.00, SD 12.31; HIs: mean 77.75, SD 11.24; r=0.14, 95% CI 0.01-0.42; P=.39), indicating high usability. People with MS reported more negative attitudes toward robots at the societal level (GAToRS S-: r=0.36, 95% CI 0.08-0.63; P=.02) and judged Pepper as more anthropomorphic (r=0.42, 95% CI 0.15-0.67; P=.007) and intelligent (r=0.37, 95% CI 0.09-0.61; P=.02) than HIs. Anthropomorphism was strongly associated with visuospatial memory (DIGICOG-MS: ρ=-0.632, 95% CI -0.84 to -0.26; P=.003) and relatively strong with both verbal memory (DIGICOG-MS: ρ=-0.504, 95% CI -0.77 to -0.08]; P=.02) and agreeableness (I-TIPI: ρ=0.491, 95% CI 0.06-0.77; P=.03). Exploratory forward stepwise regression showed that conscientiousness (I-TIPI: B=2.064, 95% CI 0.679-3.449), negative personal attitudes toward robots (GAToRS P-: B=0.169, 95% CI 0.033-0.306), and perceived upper-limb difficulties (AMSQ: B=0.169, 95% CI 0.033-0.306) explained 64% of SUS variance (adjusted R²=0.568); task-related frustration (NASA-TLX: B=-1.497, 95% CI -2.276 to -0.719) explained 48% (adjusted R²=0.451). NLP analyses revealed no between-group differences in lexical productivity or sentiment-lexicon coverage.Conclusions
This study provides first preliminary evidence that people with MS perceive a social robot as highly usable, comparably to HIs, suggesting MS-related challenges may not hinder human-robot interaction. Psychological factors, prior attitudes toward robots, and clinical characteristics were associated with user experience in the MS group. Future research should explore whether integrating these measures with language-based approaches informs tailored interventions in MS.
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BibTeX
@article{podda2026usability,
title = {{Usability and Acceptance of a Social Robot in People With Multiple Sclerosis: Comparative Cross-Sectional Study.}},
author = {Jessica Podda and Alice Bollini and Alessia Susini and Domenico Presenza and Keven T Kearney and Ester Cecchella and Erica Grange and Mario Alberto Battaglia and Andrea Tacchino and Giampaolo Brichetto},
journal = {JMIR rehabilitation and assistive technologies},
year = {2026},
month = oct,
doi = {10.2196/94068},
url = {https://europepmc.org/article/MED/42906529},
note = {CC BY},
}
RIS
TY - JOUR
TI - Usability and Acceptance of a Social Robot in People With Multiple Sclerosis: Comparative Cross-Sectional Study.
AU - Jessica Podda
AU - Alice Bollini
AU - Alessia Susini
AU - Domenico Presenza
AU - Keven T Kearney
AU - Ester Cecchella
AU - Erica Grange
AU - Mario Alberto Battaglia
AU - Andrea Tacchino
AU - Giampaolo Brichetto
PY - 2026
DA - 2026/10/21
JO - JMIR rehabilitation and assistive technologies
DO - 10.2196/94068
UR - https://europepmc.org/article/MED/42906529
AB - Background Socially assistive robotics (SAR) is an emerging field integrating robotics, medicine, cognitive and social sciences, and neuroscience. Its potential in multiple sclerosis (MS) remains largely unexplored, although MS affects sensory-motor, cognitive, and psychological domains where SAR could offer substantial benefits.Objective This study aimed to evaluate the usability of a humanoid robot in people with MS, compare it with age-matched healthy individuals (HIs), and explore usability predictors. Automated written-language analysis was tested as a complementary approach.Methods In this 2025 cross-sectional study at the Italian MS Foundation laboratory, 20 people with MS (mean age 51.4, SD 11.0 years; n=13, 65% female; mean education 13.0, SD 3.4 years) and 20 age-matched HIs (mean age 47.3, SD 10.1 years; n=12, 60% female; mean education 14.8, SD 2.2 years) completed 4 predefined tasks with the robot Pepper. Usability was assessed using the System Usability Scale (SUS). Attitudes toward robots, robot-related factors, and task-related effort were measured with the General Attitudes Towards Robots Scale (GAToRS), Godspeed questionnaire, and NASA-TLX, respectively. Psychological variables (eg, personality traits from the Italian Ten-Item Personality Inventory [I-TIPI]) and clinical characteristics for people with MS (eg, cognitive functions via the app DIGICOG-MS, upper-limb difficulties with the Arm Function in Multiple Sclerosis [AMSQ]) were collected. Written responses to open-ended questions were analyzed using natural language processing (NLP).Results SUS scores exceeded the standard cut-off in both groups, with no between-group differences (people with MS: mean 81.00, SD 12.31; HIs: mean 77.75, SD 11.24; r=0.14, 95% CI 0.01-0.42; P=.39), indicating high usability. People with MS reported more negative attitudes toward robots at the societal level (GAToRS S-: r=0.36, 95% CI 0.08-0.63; P=.02) and judged Pepper as more anthropomorphic (r=0.42, 95% CI 0.15-0.67; P=.007) and intelligent (r=0.37, 95% CI 0.09-0.61; P=.02) than HIs. Anthropomorphism was strongly associated with visuospatial memory (DIGICOG-MS: ρ=-0.632, 95% CI -0.84 to -0.26; P=.003) and relatively strong with both verbal memory (DIGICOG-MS: ρ=-0.504, 95% CI -0.77 to -0.08]; P=.02) and agreeableness (I-TIPI: ρ=0.491, 95% CI 0.06-0.77; P=.03). Exploratory forward stepwise regression showed that conscientiousness (I-TIPI: B=2.064, 95% CI 0.679-3.449), negative personal attitudes toward robots (GAToRS P-: B=0.169, 95% CI 0.033-0.306), and perceived upper-limb difficulties (AMSQ: B=0.169, 95% CI 0.033-0.306) explained 64% of SUS variance (adjusted R²=0.568); task-related frustration (NASA-TLX: B=-1.497, 95% CI -2.276 to -0.719) explained 48% (adjusted R²=0.451). NLP analyses revealed no between-group differences in lexical productivity or sentiment-lexicon coverage.Conclusions This study provides first preliminary evidence that people with MS perceive a social robot as highly usable, comparably to HIs, suggesting MS-related challenges may not hinder human-robot interaction. Psychological factors, prior attitudes toward robots, and clinical characteristics were associated with user experience in the MS group. Future research should explore whether integrating these measures with language-based approaches informs tailored interventions in MS.
SN - 2369-2529
ER -