Dataset Information

Burnout in Gastroenterology Unit Nurses.

ABSTRACT: (1) Background: Burnout syndrome is a significant problem in nursing professionals but may be dependent on the type of care that they provide. The objectives of our study are to identify and explore risk factors associated with burnout among gastroenterology nurses. Identifying the risk factors involved is an essential element for prevention programs. (2) Methods: We performed an analytical descriptive cross-sectional study. Burnout was measured using an adapted version of the Maslach Burnout Inventory (MBI) questionnaire. Strength of association between burnout scores and risk factors was calculated using Fischer's exact test; (3) Results: Our subjects were all female nurses. Work-related risk factors, such as an increased workload and a large number of night shifts have been associated with burnout in nurses, together with a lack of physical activity. We found no significant associations with sociodemographic factors; (4) Conclusions: Gastroenterology nurses are affected by high levels of emotional exhaustion. Work-related risk factors and a sedentary lifestyle result in a greater prevalence of burnout. In this category of healthcare workers, preventive actions are needed. The physical activity outside work could be a protective factor for burnout, and an exercise program could contribute to the effectiveness of well-established burnout intervention programs.

SUBMITTER: Socaciu AI

PROVIDER: S-EPMC7246650 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Burnout in Gastroenterology Unit Nurses.

Socaciu Andreea Iulia AI Ionut Razvan R Barsan Maria M Ungur Andreea Petra AP Rajnoveanu Armand Gabriel AG

International journal of environmental research and public health 20200430 9

(1) Background: Burnout syndrome is a significant problem in nursing professionals but may be dependent on the type of care that they provide. The objectives of our study are to identify and explore risk factors associated with burnout among gastroenterology nurses. Identifying the risk factors involved is an essential element for prevention programs. (2) Methods: We performed an analytical descriptive cross-sectional study. Burnout was measured using an adapted version of the Maslach Burnout In ...[more]

PMID: 32365748

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Project description:Objectives: The purpose of this study was to provide a scoping review on how to address and mitigate burnout in the profession of clinical oncology. Also, it examines how artificial intelligence (AI) can mitigate burnout in oncology. Methods: We searched Ovid Medline, PubMed, Scopus, and Web of Science, for articles that examine how to address burnout in oncology. Results: A total of 17 studies were found to examine how burnout in oncology can be mitigated. These interventions were either targeted at individuals (oncologists) or organizations where the oncologists work. The organizational interventions include educational (psychosocial and mindfulness-based course), art therapies and entertainment, team-based training, group meetings, motivational package and reward, effective leadership and policy change, and staff support. The individual interventions include equipping the oncologists with adequate training that include-communication skills, well-being and stress management, burnout education, financial independence, relaxation, self-efficacy, resilience, hobby adoption, and work-life balance for the oncologists. Similarly, AI is thought to be poised to offer the potential to mitigate burnout in oncology by enhancing the productivity and performance of the oncologists, reduce the workload and provide job satisfaction, and foster teamwork between the caregivers of patients with cancer. Discussion: Burnout is common among oncologists and can be elicited from different types of situations encountered in the process of caring for patients with cancer. Therefore, for these interventions to achieve the touted benefits, combinatorial strategies that combine other interventions may be viable for mitigating burnout in oncology. With the potential of AI to mitigate burnout, it is important for healthcare providers to facilitate its use in daily clinical practices. Conclusion: These combinatorial interventions can ensure job satisfaction, a supportive working environment, job retention for oncologists, and improved patient care. These interventions could be integrated systematically into routine cancer care for a positive impact on quality care, patient satisfaction, the overall success of the oncological ward, and the health organizations at large.

Project description:BackgroundAs a common social phenomenon, nurses' occupational burnout has a high incidence rate, which seriously affects their mental health and nursing level. The current assessment mostly uses the total score model and explores the influence of external factors on burnout, while the correlation between burnout items or dimensions is less explored. Ignoring the correlation between the items or dimensions may result in a limited understanding of nurse occupational burnout. This paper explores the item and dimension network structure of the Maslach Burnout Inventory-General Survey (MBI-GS) in Chinese nurses, so as to gain a deeper understanding of this psychological construct and identify potential targets for clinical intervention.MethodsA total of 493 Chinese nurses were recruited by cluster sampling. All participants were invited to complete the survey on symptoms of burnout. Network analysis was used to investigate the item network of MBI-GS. In addition, community detection was used to explore the communities of MBI-GS, and then network analysis was used to investigate the dimension network of MBI-GS based on the results of community detection. Regularized partial correlation and non-regularized partial correlation were used to describe the association between different nodes of the item network and dimension network, respectively. Expected influence and predictability were used to describe the relative importance and the controllability of nodes in both the item and dimension networks.ResultsIn the item network, most of the strongly correlated edges were in the same dimension of emotional exhaustion (E), cynicism (C) and reduced professional efficacy (R), respectively. E5 (Item 5 of emotional exhaustion, the same below) "I feel burned out from my work", C1 "I have become more callous toward work since I took this job", and R3 "In my opinion, I am good at my job" had the highest expected influence (z-scores = 0.99, 0.81 and 0.94, respectively), indicating theirs highest importance in the network. E1 "I feel emotionally drained from my work" and E5 had the highest predictability (E1 = 0.74, E5 = 0.74). It shows that these two nodes can be interpreted by their internal neighbors to the greatest extent and have the highest controllability in the network. The spinglass algorithm and walktrap algorithm obtained exactly the same three communities, which are consistent with the original dimensions of MBI-GS. In the dimension network, the emotional exhaustion dimension was closely related to the cynicism dimension (weight = 0.65).ConclusionsThe network model is a useful tool to study burnout in Chinese nurses. This study explores the item and domain network structure of nurse burnout from the network perspective. By calculating the relevant indicators, we found that E5, C1, and R3 were the most central nodes in the item network and cynicism was the central node in the domain network, suggesting that interventions aimed at E5, C1, R3 and cynicism might decrease the overall burnout level of Chinese nurses to the greatest extent. This study provides potential targets and a new way of thinking for the intervention of nurse burnout, which can be explored and verified in clinical practice.

Dataset Information

Burnout in Gastroenterology Unit Nurses.

Publications

Burnout in Gastroenterology Unit Nurses.

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