Reliability and validity of the Italian Version of the Chase Nurse Manager Competencies Scale - Dhurata Ivziku; Lucia Filomeno; Daniela Forte; Rosario Caruso; Gianluca Conte; Arianna Magon; Raffaella Gualandi; Marco Di Muzio; Daniela Tartaglini (Elsevier, 2024)
Objectives: This study aimed to translate and test the psychometric properties of the Chase Nurse Manager Competency Instrument (CNMCI) among Italian nurse managers and to provide further support for the scale's validity testing. Methods: An instrument translation and cross-sectional validation study was conducted. The English version was translated into Italian using the translation method, which included pre-translation (establishing equivalence), initial translation, pretesting, review, and administration. From August 2022 to June 2023, 349 nurse managers were recruited through a web survey from 31 public and private healthcare organizations in North, Central, and Southern Italy. Validity assessments included content and structural validity. Reliability was evaluated using Cronbach's α coefficient and test-retest reliability. Results: The content validity confirmed all the items of the CNMCI in the Italian version, including the two measurement sections, "knowledge and understand" and "ability to implement and/or use." The instrument's item-content validity index (I-CVI) ranged from 0.83 to 1.00, while the scale-level content validity index (S-CVI) for both instrument sections was 0.97. The confirmatory factor analysis showed an acceptable fit. In the "knowledge and understand" section, Cronbach's α coefficient was 0.978, and in the "ability to implement and/or use" section, Cronbach's α coefficient was 0.976. The correlation coefficient between each dimension was 0.494-0.908. The test-retest reliability score was 0.82, suggesting good instrument consistency. Conclusions: Overall, the Italian CNMCI demonstrates good reliability and validity for measuring nurse managers' core competencies and supports the construct's multi-dimensionality. Also, our findings support the hierarchical nature of the factors, further supporting the validity of the instrument.