Nursing Assistant Students’ Digital Cultural Intelligence and Clinical Adaptability in a North African Health College: A Cross-Sectional Study

  • Ridouane Oulhiq Mohammedi V University of Rabat
  • Shi ching W TransWorld University
  • Pichayapor Ratt iSirindhorn College of Public Health Yala
  • Maurizio Martin Cavani Brain Universidad Peruanai Cayetano Heredia
Keywords: Clinical Adaptability, Digital Cultural Intelligence, Multicultural Healthcare Education, Nursing Assistant Students, Structural Equation Modeling

Abstract

Purpose of the study: This study examined the predictive relationship between digital cultural intelligence and clinical adaptability among nursing assistant students at a health sciences college in Morocco.

Methodology: A cross-sectional design was employed with 287 students who had completed at least one clinical placement. Data were analysed using partial leas squares structural equation modellingi (PLS-SEM) to test a theory-driven conceptual framework. Measurement model evaluation confirmed satisfactory reliability and validity (CR > 0.90; AVE > 0.50; HTMT < 0.85). Structural analysis revealed that digital cultural intelligence significantly predicted clinical adaptability (β = 0.64, p < 0.001), explaining 41% of the variance (R² = 0.41). Predictive relevance was supported (Q² = 0.29), and robustness checks using covariance-based SEM confirmed acceptable model fit indices.

Main Findings: The findings indicate that the capacity to navigate culturally diverse interactions within digitally mediated healthcare environments is a substantial determinant of adaptive clinical reasoning, flexible communication, and ethical responsiveness. By empirically validating digital cultural intelligence as a multidimensional construct in vocational nursing education, this study advances theoretical integration between intercultural competence and adaptive expertise frameworks.

Novelty/Originality of this study: This study contributes Global South evidence to international nursing education research and provides a predictive model for curriculum innovation in digitally transitioning healthcare contexts.

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Published
2025-12-13
How to Cite
Oulhiq, R., W, S. ching, Ratt, P., & Brain, M. M. C. (2025). Nursing Assistant Students’ Digital Cultural Intelligence and Clinical Adaptability in a North African Health College: A Cross-Sectional Study. Journal of Health Innovation and Environmental Education, 2(2), 259-268. https://doi.org/10.37251/jhiee.v2i2.2917
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Articles