Determinants of Nursing Education Resilience in Master of Science in Nursing Programs: Fixed-Effects Panel Evidence from Pakistan, 2014-2024

Abstract

Background: The transformation of health professions education by artificial intelligence and digital tools places increased pressure on postgraduate nursing programs to demonstrate institutional resilience. Despite this urgency, empirical determinants of Nursing Education Resilience (NER) at the institutional level are largely unmeasured, particularly in lower-middle-income country settings. Aim: The study designed to identify and measure institutional predictors of NER in accredited Master of Science in Nursing (MSN) programs in Pakistan, 2014-2024. Method: A balanced panel data was constructed from accredited MSN institutions of Pakistan. The pooled ordinary least squares, random effects and fixed effects (FE) models were estimated using EViews 10. Model selection was based on the Hausman specification test. Six institutional predictors were investigated: adoption of AI curriculum, digital infrastructure, faculty digital competency, student engagement, research output and policy support. The pre-estimation diagnostics were the panel unit root tests and the inter-predictor correlation analysis. Results: The random effects specification was rejected by the Hausman test (p = 0.0003). It was determined that the main source of NER change over time is attributable to changes that occur within institutions. Faculty digital competence and the lead time in the adoption of AI curriculum were the most significant positive predictors of NER in the preferred FE model. Each expressed digital infrastructure, student engagement, research outputs, and policy support as positive effects that reached levels of statistical significance. The confirmed stationarity and the moderate inter-predictor correlations confirmed the econometric specification. Conclusion: The main factor behind the resilience of nursing education is the development of institutional capacity manifested through faculty development, curriculum integration of AI and support of governance. This finding provides evidence for nurse educators and accreditors as well as health workforce policy makers of Pakistan and other similar resource constrained settings.