Simulation-based training is increasingly used in nursing education to provide safe, experiential opportunities for developing clinical competence, particularly in high-risk maternity care. However, evidence that simulation improves performance does not explain the psychological mechanism by which learning translates into observable clinical performance. This article develops and demonstrates a mediation framework in which self-confidence is positioned as the intervening mechanism linking simulation-based training to maternal delivery performance. The framework integrates Adult Learning Theory, Social Cognitive Theory, and regression-based causal mediation analysis. A pretest–posttest control-group quasi-experimental design is specified, with simulation-based training as the intervention, post-intervention self-confidence as the mediator, and maternal delivery performance as the outcome, while baseline confidence and performance are treated as covariates. The statistical demonstration uses a synthetic dataset and PROCESS Model 4 with 5,000 bootstrap resamples; therefore, the numerical results are illustrative and must not be interpreted as findings from actual nurses or patients. In the simulated analysis, the intervention positively predicted self-confidence (? = 1.150, p < .001), self-confidence positively predicted maternal delivery performance (? = 4.800, p < .001), and the indirect effect was statistically different from zero (ab = 5.520, 95% bootstrap CI [2.810, 8.650]). The direct effect remained significant (? = 5.200, p = .007), indicating a partial mediation pattern in the synthetic demonstration. The indirect pathway represented approximately 51.5% of the simulated total effect. The study's contribution is therefore methodological and theoretical: it shows how mediation analysis can move evaluation beyond a simple input–output comparison and toward an explicit examination of how confidence may contribute to clinical performance. Empirical validation with real participants is required before the model can support substantive clinical or educational conclusions.
Anselmi, L., Binyaruka, P., & Borghi, J. (2017). Understanding causal pathways within health systems policy evaluation through mediation analysis: An application to payment for performance (P4P) in Tanzania. Implementation Science, 12, 126.
Cant, R. P., & Cooper, S. J. R. (2010). Simulation-based learning in nurse education: Systematic review. Journal of Advanced Nursing, 66(1), 3–15. https://doi.org/10.1111/j.1365-2648.2009.05240.x
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.
Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15(4), 309–334.
Imai, K., Keele, L., & Yamamoto, T. (2010). Identification, inference and sensitivity analysis for causal mediation effects. Statistical Science, 25(1), 51–71.
Jackson, M., McTier, L., Brooks, L., & Wynne, R. (2024). Impact of simulation design elements on undergraduate nursing education: A systematic review. Clinical Simulation in Nursing, 89, 101519. https://doi.org/10.1016/j.ecns.2024.101519
Mendez-Figueroa, H., Bell, C. S., Wagner, S. M., Pedroza, C., Gupta, M., Mulder, I., Lee, K., Blackwell, S. C., Bartal, M. F., & Chauhan, S. P. (2022). Postpartum haemorrhage drills or simulations and adverse outcomes: A systematic review and Bayesian meta-analysis. The Journal of Maternal-Fetal & Neonatal Medicine, 35(26), 10416–10427. https://doi.org/10.1080/14767058.2022.2128659
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behaviour Research Methods, 40, 879–891. https://doi.org/10.3758/BRM.40.3.879
Ropponen, P., Tomietto, M., Pramila-Savukoski, S., Kuivila, H., Koskenranta, M., Liaw, S. Y., & Mikkonen, K. (2025). Impacts of VR simulation on nursing students’ competence, confidence, and satisfaction: A systematic review and meta-analysis of randomised controlled trials. Nurse Education Today, 152, 106756. https://doi.org/10.1016/j.nedt.2025.106756
Rutherford-Hemming, T. (2012). Simulation methodology in nursing education and adult learning theory. Adult Learning, 23(3), 129–137.
Siwatu, K. O., & Chesnut, S. R. (2014). The career development of preservice and inservice teachers: Why teachers’ self-efficacy beliefs matter. In H. Fives & M. Gill (Eds.), International handbook of research on teachers’ beliefs. Routledge.
Vermylen, J. H., Cohen, E. R., Cook, D. A., McGaghie, W. C., Issenberg, S. B., Arnold, J., et al. (2026). Competency-based simulation training for procedural skills: A systematic review and meta-analysis. Simulation in Healthcare, 21(4), 231–240. https://doi.org/10.1097/SIH.0000000000000895
White, H., & Sabarwal, S. (2014). Quasi-experimental design and methods. Methodological Briefs: Impact Evaluation, No. 8. UNICEF Office of Research.
Alghamdi, A. S. S., & Said, F. M. (2026). Self-Confidence as a Mediator of Simulation-Based Training on Maternal Delivery Performance: A Theoretical and Statistical Model for Empirical Validation. International Journal of Academic Research in Business and Social Sciences, 16(9), 967–977.
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