The mediating role of empathy in the impact of compassion fatigue on burnout among nurses

Background

The burnout levels of nurses, who have an important place in the delivery of health services, are increasing day by day. As the burnout levels of nurses increase, there may be undesirable situations such as compassion fatigue specific to them, their patients and their institutions.

Purpose

The aim of this study is to determine the effect of compassion fatigue seen in nurses on burnout and the mediating role of empathy in this effect.

Methods

The research was conducted on nurses working in three public hospitals operating in Sakarya, Turkey, between 2 January and 16 April 2019. Since the research was conducted in more than one hospital, the minimum number of participants was determined for each hospital using the stratified sampling method in the first stage. In the second stage, the participants were selected by convenience sampling method. Descriptive statistics, linear regression and process macro regression analysis were used to analyse the data.

Results

The results showed the effect of nurses' compassion fatigue on burnout and empathy (β = 0.673). In addition, empathy has a mediating role in the effect of compassion fatigue on burnout (β = 0.251).

Conclusions/implications for practice

Reducing the burnout levels of nurses, who have a very important place in the delivery of health services, is important for both themselves and patients. It is recommended that the results of this study, which may contribute to the development of the awareness of nurse managers, should be made with the ability to understand the symptoms of compassion fatigue and burnout, teaching coping methods and providing support by experts when necessary.

Air pollution modelling in Erzurum city

Various techniques have been applied to air pollution modelling. In this study, a model was developed by applying a continuity equation to the air control volume over Erzurum city centre. Model parameters were calculated by regression analysis, using SO2 and particle concentrations taken in 1989-1990 and 1990-1991 winter seasons. Multiple correlation coefficients, R2, for all analyses were of the same order of 97%. According to this model, daily polluting concentrations are not only influenced by daily meterological parameters but also by the values of previous days. The proposed model allows estimation of daily polluting concentrations by means of meteorological data.