The Effects of Nursing Supervision Using the GROW Model on the Competency of Professional Nurses in High-Alert Medication Administration in Neurosurgical Intensive Care Unit - Sangsae, Lapathrada; Apiraknapanon, Panta (Journal of health and health management, 2025)
The objective of this quasi-experimental research with one group measuring before and after the experiment was to compare the competency, knowledge, practice and attitude of the professional nurses in the administration of high-risk drugs before and after nursing supervision using the GROW Model Concept. The sample group was 24 professional nurses working in the Neurosurgical Intensive Care Unit. Research instrument used for conducting research and collect data was the nursing supervision model manual for the administration of high-risk drugs in the Neurosurgical Intensive Care Unit based upon GROW Model. Data collection tools included Personal Information Form, Competency test for knowledge questionnaire, Competency questionnaire practical aspect, and attitude competency questionnaire. The Content Validity Index (CIV) values were 0.82, 0.88, 0.92, and 0.90 respectively and the Index of Item Objective Congruence (IOC) values were 0.82, 0.88, 0.92, and 0.88 respectively. Data were analyzed by finding frequency, percentage, mean, standard deviation and paired t-test by setting the statistical significance level at the 0.01 level. The results of the research found that the competency of professional nurses in administering high-risk drugs after nursing supervision using the GROW Model Concept statistically significantly higher than before nursing supervision using GROW Model Concept (p<0.01) in all three areas that were knowledge, practice and attitude. The results of this study show that the nursing supervision approach using the GROW Model Concept can be applied to develop the competency of professional nurses in the area of effective management of high-risk drugs in nursing units by helping to promote nurses’ knowledge, practical skills and decision-making for managing high-risk drugs.