Şeker, Sevda Arslan; Gül, Şenay; Erkus Kucukkelepce, Gulhan

Personal characteristics, experiences, perceptions, working environment of nurses, and the attitudes of managers during the delivery of health services affect the relationship between emotional labor and job satisfaction. The aim of this study was to investigate the relationship between emotional labor and job satisfaction levels of nurses. The study was a descriptive cross-sectional and conducted 151 nurses who agreed to participate in the study. The data were collected between October and December 2019 using "Personal Information Form", "Job Satisfaction Scale for Nurses" and "Emotional Labor Scale". Descriptive statistics, non-parametric tests, Spearman's Rho correlation and Mann Whitney U test were used in the analysis of the data. In the study, it was determined that there was no significant relationship between the Emotional Labor Scale and Job Satisfaction Scale for Nurses total scores (r=0.071; p=0.0389). A statistically significant, weak and positive linear relationship was found between Surface Acting sub-scale of the Emotional Labor Scale and the Pleasant Work Environment sub-scale of the Job Satisfaction Scale for Nurses (r=0.175; p=0.031). Emotional labor behaviors and job satisfaction of nurses affect health care in many ways. The results of this study are stimulating for managers at all levels.

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Derse, Onur; Göçmen, Elifcan; Narli, Mufide

Risk management has gained substantial attention for the health sector in recent years. Healthcare systems are forced to deal with risk assessment due to deadly accidents. Biochemistry department is one of the most critical units, in which occupational accidents should be controlled preventively. Thus, this paper aims at developing a risk assessment process to minimize the occupational accidents. Failure mode and effects analysis (FMEA) and 5x5 matrix (L Matrix) as most effective quantitative risk analysis methods, are developed for a biochemistry department of a hospital in Turkey to evaluate the risk types discussed in related works and discovered during this work. First, the decision makers’ risk evaluation based on historical data of accidents are adopted to risk management process. Then, with regard to scoring of risk factors such as occurrence, severity and detectability, risk priority numbers and classes are obtained and preventive measures for the high-risk failure modes are determined. Analytic Hierarchy Process (AHP) method has been applied for prioritizing these measures to reduce or eliminate these risk types. Considering the results obtained from the AHP method, a goal programming model is developed to minimize the risk prevention costs. Obtained results demonstrate the effectiveness of the proposed methods.

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