Evaluation of reliability and validity regarding the Chinese version of Critical Cultural Competence Scale for clinical nurses

Patients from different social environments and cultural backgrounds have different nursing needs. If nurses ignore the cultural differences of patients, it is easy to lead to the strained nurse-patient relationship, affect the nursing effect and cause harm to patients. Critical cultural competence (CCC) can help nurses to meet the nursing needs of patients from different cultural backgrounds, which is beneficial to building a harmonious nurse-patient relationship and improving the quality of nursing. Almutairi, et al designed the Critical Cultural Competence Scale (CCCS) which can be used to evaluate accurately nurses' CCC. No studies have reported the development of a critical cultural competence measurement tool for nurses or the introduction of foreign scales in China. This study aims to conduct Chinese and cross-cultural debugging and test the reliability of the English version of the CCCS in order to form CCCS suitable for Chinese cultural background and provide an effective evaluation tool for investigating the current situation of clinical nurses' CCC. This study used Brislin's back-translation model to translate and back-translation the English version of CCCS. The Chinese version of CCCS was then created through cross-cultural debugging by expert consultation and a pre-survey with a sample size of 30 clinical nurses. From August to October 2019, 580 clinical nurses were surveyed using a whole group sampling method. The participants were randomly divided into 2 groups with a 7꞉3 ratio. One group ( =406) was used for exploratory factor analysis and reliability analysis, while the other group ( =174) was used for confirmatory factor analysis. Six experts used the scale-level content validity index (S-CVI) and the item-level content validity index (I-CVI) to assess content validity. In the exploratory factor analysis, items were screened using the critical ratio method, and were tested using the KMO (Kalser-Meyer-Olkin) index, Bartlett's sphericity test, and principal component analysis. In the confirmatory factor analysis, average variance extracted (AVE), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), and root mean square error of approximation (RMSEA) were used to assess the degree of fit of the constructed model. For the total scale and the 4 subscales, the Cronbach's α coefficient, split-half reliability, and retest reliability were used to assess the scale's reliability. The S-CVI was 0.930, while the I-CVI ranged from 0.83