Klaudia Osypka, Malgorzata Dziechciaz, Aleksandra Suwalska, Katarzyna Wieczorowska-Tobis, Slawomir Tobis
Overall attitudes were positive, with assistive functions rated more favourably than social functions. Employed students held significantly more favourable views of the robot's social and companion roles and rated its animacy higher than non-employed peers; professional employment, age, and self-rated technological fluency were independent predictors of attitude.
INTRODUCTION: Population ageing and workforce shortages are placing growing pressure on geriatric care systems, prompting interest in humanoid social robots (HSRs) as a potential support for older-adult care. Their successful introduction, however, depends substantially on acceptance by the nursing workforce that will deliver and oversee their use. Nursing students represent a strategically important population for public health workforce planning, since their openness to robotic technologies will shape how readily such tools are adopted in future practice.
METHODS: We conducted a cross-sectional study among 475 nursing students (bachelor's and master's level) at a higher education institution in Poland. After viewing a standardised video depicting the TIAGo HSR, participants completed the Users' Needs, Requirements and Abilities Questionnaire and the Godspeed Questionnaire Series. Students concurrently employed as nurses (n = 107) were compared with non-employed students (n = 368), and multiple logistic regression was used to adjust for potential confounders.
RESULTS: Overall attitudes were positive, with assistive functions rated more favourably than social functions. Employed students held significantly more favourable views of the robot's social and companion roles and rated its animacy higher than non-employed peers; professional employment, age, and self-rated technological fluency were independent predictors of attitude.
DISCUSSION: Concurrent nursing employment is independently associated with more favourable, multidimensional attitudes towards HSRs; this cross-sectional association may support the case for embedding human-robot interaction content in nursing curricula and involving frontline nurses in robot implementation, though longitudinal or experimental work is needed to confirm a causal pathway before this is treated as an established public-health-workforce strategy.