Utopian or dystopian? A mixed-methods study of nursing and midwifery students' perceptions of artificial intelligence and robot-assisted person-centred care in education


Sengul T., Sarikose S., UNCU B., Ozayabakan R., KAYA N.

NURSE EDUCATION TODAY, vol.162, 2026 (SCI-Expanded, SSCI, Scopus) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 162
  • Publication Date: 2026
  • Doi Number: 10.1016/j.nedt.2026.107049
  • Journal Name: NURSE EDUCATION TODAY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, CINAHL, Education Abstracts, Educational research abstracts (ERA), MEDLINE
  • Istanbul University Affiliated: No

Abstract

Background: The integration of artificial intelligence (AI) and robotic technologies into healthcare is increasing, making it important to understand how future professionals view these innovations. This study explored nursing and midwifery students' perspectives on using these technologies in care and the cognitive, ethical, and personcentred factors shaping their readiness and willingness. Methods: A convergent parallel mixed-methods design was used. The study was conducted between September and December 2025 with students from three universities. In the quantitative phase, students completed surveys that included the Service Robot Integration Willingness Scale, the Medical Artificial Intelligence Readiness Scale, and the Patient-Centred Care Competency Scale. Descriptive statistics, correlations, and hierarchical regression were conducted. Qualitative data were gathered through six online focus groups and analysed thematically. Both strands were integrated at interpretation, guided by the Technology Adoption Model and the Person-Centred Nursing Framework. Findings: Quantitative data from 761 students and qualitative data from 45 participants showed that students demonstrated high readiness for AI, strong person-centred care competence, and moderately high willingness to integrate service robots. Person-centred competence significantly moderated the relationship between AI readiness and willingness, suggesting that humanistic values can support technology acceptance. Qualitative findings expanded these results: students viewed AI through both utopian (efficiency, safety, personalised care) and dystopian (loss of human touch, ethical risk, system failure) perspectives (Theme 1). They emphasised the continued importance of empathy, relational presence, and ethical judgement (Theme 2). Additional concerns included professional identity, accountability, and privacy (Theme 3). Students also highlighted the need for digital literacy, simulation-based training, and institutional readiness for effective implementation (Theme 4). Conclusion: Acceptance of AI and robotics increased when these technologies supported, rather than replaced, person-centred care. The moderating effect of person-centred competence suggests that humanistic values are essential for preparing students to use AI ethically and confidently. Education should integrate digital, ethical, and relational training to support safe and meaningful integration.