Design and Implementation of a Checklist for Prediction of Anesthesia-Induced Nausea and Vomiting in Candidate Patients for Mastectomy

Abstract

Objectives: Prediction of nausea and vomiting can positively contribute to the management of this post-anesthesia adverse effect. Therefore, the present study aimed to design and implement a checklist for predicting anesthesia-induced nausea and vomiting in candidate patients for mastectomy. Materials and Methods: This methodological study was conducted on 300 candidate patients for mastectomy during 2018-2019 at Imam Reza hospital, Tabriz, Iran. The checklist items were designed and developed based on scientific articles, expert opinions, and patient interviews. The Pearson correlation coefficient, Cronbach’s alpha, Spearman-Brown coefficient, factor analysis, the KaiserMeyer-Olsen measure of sampling adequacy, and VARIMAX rotation were used to analyze the data. Eventually, the distribution of data with a normal distribution was compared through the Kolmogorov-Smirnov test. Results: In the first stage, 100 items were collected, which were reduced to 35 cases after modification by a team of experts. Twenty items were ultimately selected after observing the 80/20 response rate. The overall scale reliability was calculated as 0.953 based on Cronbach’s alpha. The correlation coefficient of the first and second implementations was 0.853. Finally, the four extracted factors accounted for 69.51 of the variance of the checklist based on factor analysis. Conclusions: The prediction checklist for post-anesthesia nausea and vomiting in candidate patients for mastectomy comprised adequate psychometric indicators that could be used with high reliability according to the extracted indices.