Scenario-based artificial intelligence education and professional identity in nursing students: a qualitative futures study
BMC MEDICAL EDUCATION, cilt.1, sa.1, ss.1-16, 2026 (SCI-Expanded, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 1 Sayı: 1
- Basım Tarihi: 2026
- Doi Numarası: 10.1186/s12909-026-10618-8
- Dergi Adı: BMC MEDICAL EDUCATION
- Derginin Tarandığı İndeksler: Social Science Premium Collection (ProQuest), Biomedical Reference Collection: Corporate Edition (EBSCO), Education Collection (ProQuest), Health Research Premium Collection (ProQuest), Scopus, Agricultural & Environmental Science Database, Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), EMBASE, MEDLINE, Directory of Open Access Journals
- Sayfa Sayıları: ss.1-16
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet
Özet
Aim/objective
To explore nursing students’ future-oriented perceptions of professional identity and autonomy in AI-mediated nursing futures through structured scenario-based foresight, with SWOT (strengths, weaknesses, opportunities, and threats) incorporated as a framework for developing alternative 2050 scenarios.
Background
Artificial intelligence is rapidly transforming healthcare systems and nursing practice. Preparing future nurses requires not only technological literacy but also the development of ethical reasoning, professional identity, and autonomous decision-making in AI-mediated environments.
Design
Qualitative descriptive study using scenario-based foresight methodology.
Methods
The study was conducted with undergraduate nursing students enrolled in an AI elective course. Students developed individual written scenarios envisioning nursing and healthcare in 2050 using a structured scenario development form supported by SWOT prompts. Fourteen students voluntarily participated. Scenario narratives were analysed using thematic analysis, and the resulting themes and subthemes were subsequently classified under the four predefined SWOT dimensions.
Results
Students articulated a dual trajectory regarding AI integration in nursing. On one hand, AI was associated with risks such as algorithmic dominance, ambiguity in professional accountability, and the potential weakening of relational care. On the other hand, students envisioned opportunities for strengthened professional agency through expanded roles including ethical stewardship, digital advocacy, and decision-support partnership. Across scenarios, autonomy and human-centred care emerged as central values guiding students’ evaluations of AI in nursing.
Conclusions
Scenario-based AI education may support nursing students’ critical reflection on professional identity and autonomy. Educational approaches that integrate foresight activities with ethical and professional discussions may better prepare future nurses to navigate AI-mediated healthcare environments.