ArticleCureus2026
Artificial Intelligence-Based Adaptive Simulation Integrated With a Workforce Decision-Support System to Improve Simulated Nursing Leadership Performance: A Randomized Controlled Study.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
1 author.
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Abstract
Background The growing integration of artificial intelligence (AI) in healthcare necessitates that nurse leaders develop advanced competencies in decision-making, communication, and data-informed clinical judgment. Traditional simulation-based education, while effective, often relies on fixed scenarios with limited adaptability and minimal real-time decision support. AI-enhanced simulation offers a potential solution by creating responsive, adaptive learning environments that support leadership development. Methods This randomized controlled, parallel-group, pretest-posttest trial included 130 final-year nursing students who were randomly allocated to an intervention group (n = 65), receiving AI-adaptive simulation integrated with an AI-based workforce decision-support system, or a control group (n = 65). Twenty-one clinical preceptors served as trained and blinded outcome assessors and were not included in the randomized sample. Leadership performance was assessed using the Creighton Simulation Evaluation Instrument (C-SEI). Secondary outcomes included team performance, general self-efficacy, and AI acceptance. Results At Week 10, the intervention group demonstrated greater improvement in leadership performance than the control group (between-group difference in change = 5.20, 95% CI 4.18-6.22, p < 0.001), with a large standardized effect (Cohen's d = 1.78). Greater improvements were also observed in team performance (between-group difference in change = 0.63, 95% CI 0.44-0.82, p < 0.001, d = 1.24) and general self-efficacy (between-group difference in change = 5.30, 95% CI 3.82-6.78, p < 0.001, d = 1.37). Intervention-group students reported favorable AI acceptance, including perceived usefulness and ease of use. Conclusions AI-adaptive simulation integrated with an AI-based workforce decision-support system was associated with improved leadership performance, team performance, and self-efficacy among final-year nursing students under controlled simulation conditions. Further research is needed to determine whether these effects are sustained and transfer to clinical practice.
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