The Impact of Crisis Management Training on Disaster Nursing Competencies: a Pre-Test and Post-Test Evaluation
The Impact of Crisis Management Training on Disaster Nursing Competencies: a Pre-Test and Post-Test Evaluation
This study aims to evaluate the effectiveness of crisis management training designed for third-year nursing students. Crisis management in the healthcare sector holds critical importance during unforeseen events such as natural disasters and emergencies. The ability of nurses to effectively plan, make quick decisions, and manage crises successfully plays a vital role in ensuring patient safety and operational efficiency. The primary objective of this research is to enhance nursing students' crisis management skills and to assess the extent to which these skills can be improved through targeted training.
The study employs a pre-test and post-test design. The participants will consist of third-year nursing students. A pre-test will be administered before the training to assess the participants' existing knowledge and skills in crisis management. The training content will focus on crisis management concepts, planning strategies, rapid decision-making processes, and team coordination. Additionally, intervention approaches to natural disasters such as earthquakes will be addressed in detail. At the conclusion of the training, a post-test will be conducted to evaluate the program's effectiveness.
The data collection process will utilize the Disaster Nursing Preparedness and Response Competency Scale, a standardized tool designed to measure students' levels of preparedness, problem-solving skills during crises, and intervention effectiveness. The training program will adopt an interactive approach, integrating both theoretical and practical components.
The study hypothesizes that crisis management training will significantly enhance the disaster nursing competencies of nursing students. The findings aim to reveal whether the training leads to a substantial improvement in the knowledge and skill levels of the participants.
The study is scheduled to be conducted at a private university in Istanbul in March 2025. The study population comprises all third-year nursing students enrolled in the nursing program at the university during the study period (N=70). No sampling method will be used, as the study aims to include the entire population. The training program will consist of a single session and will incorporate feedback from students and motivation-enhancing activities. Slavin's Effective Teaching Model will be employed, featuring presentations and interactive sessions. Data will be collected using a Personal Information Form and the Disaster Nursing Preparedness and Response Competency Scale.
The collected data will be analyzed using SPSS for Windows 22.0. The normality of data distribution will be assessed using the Kolmogorov-Smirnov Test. If the Kolmogorov-Smirnov Test indicates p>0.05p > 0.05p>0.05, the data will be considered normally distributed. Conversely, if p<0.05p < 0.05p<0.05, the data will be deemed non-normally distributed, and skewness and kurtosis values will be examined. Changes in repeated measurements will be analyzed using a Repeated Measures ANOVA if the data is normally distributed, or the Friedman Test if it is not.
Descriptive statistics will be employed to summarize the general characteristics of the data, including the means and distributions of pre-test and post-test scores. To evaluate the impact of the training program, a Paired Samples T-Test will be conducted to assess the differences between pre-test and post-test scores within the same group. This analysis will measure the program's effects on time management and procrastination behaviors. Additionally, effect sizes (e.g., Cohen's d) will be calculated to evaluate the magnitude and significance of the intervention's effects.
Variance analysis (ANOVA) may also be used to determine significant differences between groups if deemed necessary. Furthermore, a Power Analysis will be conducted to assess whether the study has an adequate sample size. These analyses will provide meaningful and reliable interpretations of the study findings.
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Exclusion Criteria: