Assessment of self-sufficiency of emergency teams situated in schools

The purpose of occupational health and safety is to minimize the incidence of work accidents and occupational diseases and to ensure that employees perform their duties in a safe and healthy environment. In this context, a risk analysis should be carried out in accordance with the relevant regulations in the workplace, and an emergency action plan should be prepared and renewed, taking into account the times specified in the regulations according to the hazard classes. The results of the risk assessment, which are among the criteria to be taken into consideration during the determination of emergencies, also show the relationship between these two concepts. It is seen that emergency situations have occurred due to various reasons from past to present and as a result of these, both moral and material damages are high. The work to prevent emergencies, as well as the things to be done after they occur, should be clearly stated. It should also be clearly determined by whom the first response will be carried out, especially when an emergency occurs. In this study, the self-efficacy of the emergency teams in the schools was measured and it was aimed to evaluate whether the teams were appropriate for their desire level and groups. After the questionnaire was applied to the emergency teams in schools affiliated to the Gümüşhane Provincial Directorate of National Education, the data set was obtained by coding the answers appropriate for the assessment. The data obtained from the study were analyzed using SPSS 24.0 for Windows statistical software. Before analyzing the data, the skewness and kurtosis values of the scale in the questionnaire were calculated. On the other hand, the scale's "Kolmogorov-Smirnov" test value was found to be p≤0,000, and it was concluded that the data was not normally distributed. Based on this result, the "Mann-Whitney U" and "Kruskal Wallis-H" Tests were used in order to test the hypotheses formed with the arithmetic mean and standard deviation values in the analysis of the data.