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Background: Midwifery practice in Hungary is characterized by chronic stress, which may in turn lead to burnout and impaired perinatal care. However, little is known about the degree and potential stressors of burnout, which hinder the development of strategies to promote well-being among midwives in Hungary. Aim: To assess the prevalence of burnout and identify persistent individual and occupational stressors among midwives in Hungary over the past decade to inform prevention. Methods: We conducted two cross-sectional studies among midwives in 2014 and 2022. We used the Maslach Burnout Inventory to assess burnout (emotional exhaustion, depersonalization, and personal accomplishment) over time. We also collected data on individual and work characteristics. We performed a multivariate regression analysis to explore associations between burnout and respondents' characteristics. Findings: The degree and prevalence of emotional exhaustion among midwives increased significantly between 2014 (N = 224) and 2022 (N = 152). High workload, not feeling valued at work, poorly perceived health status and work dissatisfaction emerged as a significant positive correlate of emotional exhaustion or depersonalization in both studies. Living alone showed both a positive and inverse association with burnout in 2014 and 2022, respectively. Work satisfaction was a positive correlate of personal accomplishment in both studies. Conclusions: Our results add to and confirm the growing body of evidence about the high prevalence of burnout among midwives in Hungary. We identified potential risk factors and outcomes of burnout, which remained unchanged over time. To prevent or reduce burnout among midwives, future interventions should focus on addressing these potential persistent risk factors. However, the time-varying role of factors influencing burnout makes it advisable to review preventive interventions from time to time.

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INTRODUCTION: The healthcare sector is the most studied area of burnout, as the mental health of healthcare workers has a significant impact on the mental health of the people they care for. OBJECTIVE: The aim of our study was to investigate whether there have been changes in the dimensions of burnout among midwives, and how the relationships between burnout and the individual factors and working conditions that influence it have evolved, using national data from 2014 and 2022. METHOD: An anonymous, voluntary, questionnaire-based survey of midwives working exclusively in maternity units was conducted using the Maslach Burnout Inventory questionnaire, which measures burnout, and questions on respondents' demographic characteristics and working conditions. Multivariate ordinal logistic regression was used to explore associations between burnout and respondent characteristics, and associations were characterized by odds ratios. RESULTS: Among the dimensions of burnout, no change in depersonalization was observed in 2022, but both emotional exhaustion and personal ineffectiveness were significantly more common in 2022 than in 2014. Responses from 224 midwives in 2014 and 152 midwives in 2022 were analyzed. Looking at the influencing factors, higher levels of burnout in 2014 were significantly associated with poorer perceived health, lack of a partner, smoking, shorter time in healthcare, having a job in a larger city, feeling overworked and dissatisfied. In 2022, on the other hand, younger age, smoking, shorter time in healthcare, feeling overworked, dissatisfied and unvalued were associated with higher levels of burnout. Looking at the combined effect of these factors, willingness to attend a health promotion lecture and having a second job also showed a significant effect on burnout in 2022. DISCUSSION: The authors discuss the change in burnout among midwives and the possible reasons for the correlations shown. CONCLUSION: The results of the first study on burnout among midwives in Hungary show that improving the working conditions of midwives is essential for the functioning of family-friendly midwifery. In addition, to prevent burnout, more emphasis should be placed on the prevention of the risk factors identified in the study in education and training. Orv Hetil. 2023; 164(40): 1592-1599.

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Introduction: Burnout syndrome among healthcare workers is a well-known problem. Its occurrence and the roots have been addressed in several studies. The daily work of the specialist employees in the neonatal intensive care units is extremely stressful physically and mentally. Objective: The study assessed the frequency and intensity of burnout phenomenon among healthcare professionals working in neonatal intensive care units and examined the relations between institutional levels, occupation, and work experience. Method: Data were collected in 2019 using the Maslach Burnout Inventory (MBI) questionnaire compiled by

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INTRODUCTION: Simulation models can contribute substantially to our understanding and ability to control the dynamic processes underlying impaired glucose metabolism in diabetic patients. AIM: The aim of this paper is to outline a new comprehensive, physiologically-based dynamic model of glucose homeostasis incorporating up-to-date quantitative knowledge about glucose metabolism and its control by insulin and glucagon. METHOD: The model is composed of three submodels for glucose, insulin, and glucagon. RESULTS: The glucose submodel specifies the dynamics of glucose absorption following meals, hepatic glucose production and uptake, peripheral glucose uptake, kidney excretion, and insulin-independent uptake of glucose in the brain and red blood cells. The insulin submodel includes equations for insulin absorption, pancreatic insulin release and insulin clearance. The glucagon model specifies the hormone secretion and elimination kinetics. Algebraic equations are used to specify (i) how the hormones affect glucose production and utilisation in various compartments such as liver, muscle and fat tissues, and (ii) how glucose levels modify insulin and glucagon release from the pancreas. Setting the values of various model parameters is used to generate virtual individual patients. CONCLUSIONS: The model allows the simulation of 24-hour blood glucose profiles for both insulin-dependent non-insulin dependent diabetic patients.

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Self monitoring of blood glucose is the cornerstone of diabetes management. However, the data obtained by self monitoring of blood glucose have rarely been used with the highest advantage. Few physicians routinely download data from memory-equipped glucose meters and analyse these data systematically at the time of patient visits. There is a need for improved methods for the display and analysis of blood glucose data along with a modular approach for identification of clinical problems. The authors present a systematic methodology for the analysis and interpretation of self monitoring blood glucose data in order to assist the management of patients with diabetes. This approach utilizes the followings 1) overall quality of glycemic control; 2) severity and timing of hypoglycemia and hyperglycemia; 3) variability of blood glucose readings; 4) various temporal patterns extracted from recorded data and 5) adequacy of self monitoring blood glucose data. Based on reliable measures of the quality of glycaemic control and glucose variability, a prioritized problem list is derived along with the probable causes of the detected problems. Finally, problems and their interpretation are used to guide clinicians to choose therapeutic actions and/or recommend behaviour change in order to solve the problems that have been identified.

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