What Matters Most in Simulation Scenario Design? A Mixed-Methods Analysis of Expert Perspectives

Abstract Introduction: Simulation is a key component of healthcare training, but the creation of effective simulation scenarios is challenging and not well formalized. While best practice recommendations are available, empirical evidence to inform design priority is scarce for educators. We examine in this paper, what components of the task simulation experts consider to be more critical, and how this varies with expertise. Methods: A convergent parallel mixed methods study was performed. An online survey was performed of 35 simulation phase experts consisting of structured quantitative weight scoring and qualitative written components. Descriptive statistics and non-parametric statistics were performed on the quantitative data. Qualitative responses were analyzed thematically according to Braun and Clarke’s six-step method for identifying prominent themes. Results: Learning Objectives had highest mean normalized weight (29.2%, SD=9.6), followed by Scenario Flow & Structure (24.7%, SD=10.3). Learning Objectives was the top factor for participants with more than 10 years' experience versus Complexity and Fidelity for participants with 1–3 years of experience. Nine core themes were identified using thematic analysis: Learning Objectives, Learner Adaptation, and Fidelitywere referenced most commonly. Variation by level of experience highlights shifting pedagogical concerns. Discussion: Results indicate agreement about the importance of learning objectives, with experience-based variations in relative importance. For senior instructors alignment to the curriculum was emphasized, whereas for novices realism and task difficulty. These trends indicate a development in design cognition and the necessity of adaptive frameworks sensitive to instructional maturity. Conclusion: This work offers empirical context for simulation design prioritization and demonstrates the pedagogical transformation of expert judgment. It argues for flexible, experience-driven models to help educators create appropriate and effective simulation scenarios in their own contexts.