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Construction and Validation of a Contextualized Competency Framework for Newly Recruited Nurses in Maternal and Child
Nan Wan1, Siying Liu1, Zhaoyi Ye1
1Department of Nursing, Guangdong Pharmaceutical University, Jianghai Street No. 283, Guangzhou 510310, China.
Abstract:
Objectives: Existing nursing competency instruments are generally designed for broad nursing populations and may not fully capture the observable, task-linked, and developmental requirements of newly recruited nurses in maternal and child health (MCH) hospitals. This study developed the Newly recruited nurses' Competency Framework for Maternal and Child Health Hospitals (NCF-MCH) and preliminarily validated its corresponding self-assessment tool. Methods: Guided by Benner's novice-to-expert perspective and Mills' reconceptualised competency terminology, the framework was developed through a structured literature and framework review, item mapping, two-round Delphi consultation, and pilot testing. A cross-sectional survey was conducted among newly recruited nurses from four MCH hospitals. Exploratory factor analysis, confirmatory factor analysis, and reliability and validity analyses were performed. Results: The final framework included six domains and 70 items. The scale showed high internal consistency (Cronbach's α = 0.944), but weak total split-half reliability (0.585). Exploratory factor analysis using principal axis factoring with Promax rotation suggested a six-factor solution explaining 59.01% of the variance. Confirmatory factor analysis showed acceptable absolute fit (χ2/df = 1.675, SRMR = 0.0595, RMSEA = 0.055), whereas incremental fit was marginal (TLI = 0.861, CFI = 0.866). Convergent and discriminant validity analyses provided preliminary support for the multidimensional structure. Conclusions: The NCF-MCH provides a context-specific framework and corresponding self-assessment tool for describing self-perceived competency among newly recruited nurses in MCH hospitals. It may inform professional transition programs and competency-based training, but further external, longitudinal, and objective validation is required.
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