Analysis of the reliability and validity of the competency inventory registered nurses scale
Keywords:
Nursing competence, Psychometric validation, Reliability, Construct validity, Exploratory factor analysis, MongoliaAbstract
Background: Ensuring the quality of healthcare services relies heavily on the professional competence of nurses. This study aimed to assess the internal consistency and construct validity of a competency assessment questionnaire developed for nurses working in tertiary-level hospitals in Ulaanbaatar, Mongolia. Aim: The aim of this study is to determine the internal reliability and construct validity of the questionnaire used to assess nurses’ competency. Materials and Methods: A cross-sectional study design was conducted among 390 nurses employed at tertiary hospitals in Ulaanbaatar. Data were analyzed using SPSS version 25.0. Internal reliability was evaluated using Cronbach’s alpha, and construct validity was assessed through exploratory factor analysis (EFA). Results: The 55-item questionnaire demonstrated excellent internal reliability (Cronbach’s alpha=0.981). The Kaiser-Meyer-Olkin (KMO) measure was 0.972, and Bartlett’s test of sphericity was significant (p<0.001), indicating the data were suitable for factor analysis. Conclusions: 1. The internal consistency of the questionnaire showed a Cronbach’s alpha coefÏcient of 0.981, indicating excellent reliability. In addition, the Cronbach’s alpha values for each of the seven subscales were all above 0.90, demonstrating strong inter-item correlations and stability of the measurement indicators. The developed questionnaire is a highly reliable and valid tool for assessing the competencies of nurses in Mongolia. Its strong psychometric properties support its use in both research and professional development contexts. 2. Factor analysis was conducted using the Varimax rotation method to evaluate the construct validity of the questionnaire. The Kaiser-Meyer-Olkin (KMO) measure was 0.972, and Bartlett’s Test of Sphericity was significant (p<0.001), indicating that the data were suitable for factor analysis. The analysis identified seven factors, each with a loading above 0.60, confirming the high construct validity of the measurement tool.
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