Cultural Adaptation and Psychometric Evaluation of the Nursing Decision-Making Instrument Into European Portuguese

Abstract

Introduction Nurses are continually faced with multiple demands to make decisions in their clinical practice. The Nursing Decision-Making Instrument (NDMI) assesses nurses’ decision-making styles during the several stages of this process. Objectives To adapt the NDMI into European Portuguese and evaluate the psychometric properties of the Portuguese version in a population of Portuguese nurses. Methods Descriptive study design was used to examine psychometric properties of NDMI. Nonprobability convenience sample of 339 Portuguese direct-care nurses. Data were collected using a questionnaire comprising sociodemographic and professional data and the NDMI–Portuguese version (NDMI-PT). An exploratory factor analysis (EFA; n = 125) and a confirmatory factor analysis (CFA; n = 214) were carried out using IBM SPSS (v. 24) and AMOS (v. 22). Results The EFA revealed a structure of four latent factors, which represent the reorganized stages of the decision-making process. The CFA found a good overall fit of the model (χ 2 /df = 2.13; comparative fit index [CFI] = 0.91; goodness of fit index [GFI] = 0.82; Tucker-Lewis Index [TLI] = 0.90; root mean square error of approximation [RMSEA] = 0.07; maximum-likelihood expected cross-validation index [MECVI] = 3.13). The psychometric analysis of the theoretical structure revealed that the four factors reflect the decision-making stages and have a better overall fit than the empirical structure (χ 2 /df = 1.82; CFI = 0.94; GFI = 0.86; TLI = 0.93; RMSEA = 0.06; MECVI = 2.55). The analysis of the construct reliability of the NDMI-PT revealed that the overall internal consistency was excellent ( α =0.96). Conclusions This study revealed that the empirical and theoretical structures were appropriate and valid for the sample under analysis. The NDMI-PT is a reliable and valid tool for assessing nurses’ decision-making styles. Studies should be conducted to gain further insight into the robustness of this validated tool.