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Facilitating acceptance, trust, and ethical integration of socially assistive robots among nurses : a quasi-experimental study
Izidor Mlakar, Igor Robert Roj, Vojko Flis, Valentino Šafran, Urška Smrke, 2025, original scientific article

Abstract: Objectives: To evaluate the impact of different types of demonstrations (no demonstration, video demonstration, and face-to-face demonstration) on nurses’ acceptance, trust, and ethical considerations regarding socially assistive robots. Methods: The study employed a quasi-experimental design involving 312 nurses: 201 with no exposure to socially assistive robots, 97 exposed via video demonstrations, and 14 exposed through live face-to-face demonstrations in a hospital room. Participants completed self-report measures assessing their perceptions of ethical acceptability, trust, and acceptance of socially assistive robots. Results: Participants exposed to any kind of demonstration reported significantly higher perceptions of ethical acceptability compared to those with no exposure. Among demonstration types, live face-to-face demonstrations resulted in higher overall ethical acceptability, satisfaction, and acceptance compared to video demonstrations. Conclusions: Demonstrations, particularly face-to-face interactions, play a crucial role in fostering ethical acceptability and overall acceptance of socially assistive robots. These findings highlight the importance of incorporating live demonstrations in strategies to improve healthcare professionals’ trust and acceptance of robotic technology.
Keywords: ethical acceptability, acceptance, socially assistive robots, nurses, quasi experimental study
Published in DKUM: 29.05.2025; Views: 0; Downloads: 2
Full text (7,33 MB)

The influence of human age on order picking performance with collaborative robots : Experimental Insights
Thilini Ranasinghe, Minqi Zhang, Eric Grosse, Dominic Loske, Jakob Marolt, Tone Lerher, 2025, published scientific conference contribution

Abstract: This study investigates the impact of integrating autonomous mobile robots (AMRs) into order picking, with a particular focus on how age influence human performance. Our research employs a multimethod approach, combining descriptive statistics, ANOVA, and post-experiment survey data analysis to evaluate the effects of AMR-assisted picking compared to manual cart picking. The results demonstrate that AMRs significantly reduce order-picking times (OPTs) and variability in performance across both age groups, with the older group showing an OPT improvement of 23.68%, and the younger group 29.40%. The ANOVA revealed that age significantly influenced OPTs. Additionally, the survey data indicated that participants perceived AMRs as simple to use and collaborative, with a strong positive correlation between AMR positioning and collaboration experience. These findings highlight the benefits of AMRs in enhancing efficiency and consistency in warehouse operations. The study underscores the importance of considering human factors in the design and implementation of robotic systems, paving the way for a human-centric Industry 5.0. Future research should attempt to achieve empirical data from real industrial operations, with the focus on larger sample sizes and the long-term effects of AMR integration on job satisfaction and overall performance.
Keywords: order picking, aging, autonomous mobile robots, experimental study
Published in DKUM: 27.03.2025; Views: 0; Downloads: 2
Full text (1,40 MB)
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