Posted: Mar 31, 2023
The global nursing shortage represents one of the most pressing challenges in contemporary healthcare systems, with new nurse turnover rates reaching alarming levels across multiple healthcare settings. Traditional approaches to understanding and addressing nurse retention have predominantly employed qualitative methodologies and cross-sectional survey designs, which while valuable, have limitations in capturing the dynamic, multi-level complexity of factors influencing nurse career decisions. Clinical mentorship programs have emerged as a promising intervention strategy, yet the mechanisms through which these programs influence retention remain inadequately understood. This research introduces an innovative computational framework that transcends conventional methodological boundaries to provide new insights into mentorship effectiveness.
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