Influences of Occupational Burnout and Personality on Lipid Peroxidation Among Nurses in Shahroud City, Iran

Monitoring of mental health in occupational populations: a study on the role and application of HDL-related inflammatory index

Background

Mental disorders in occupational populations pose significant health and economic burdens, but there exists a lack of practical and objective biomarkers for occupational mental health monitoring. Our study aims to explore the correlation between high-density lipoprotein (HDL)-related inflammatory markers and negative psychological symptoms in occupational populations. We also seek to evaluate the potential application effectiveness of these indicators as biomarkers for identifying the impact of mental health on occupational populations. Moreover, the indicators found in this study can be used as indicators for identifying high-risk groups prone to inflammatory responses caused by negative psychological symptoms.

Methods

Our study adopted a cross-sectional design with a combination of questionnaires and biochemical index tests for 1920 eligible occupational populations. The Depression Anxiety Stress Scales-21 (DASS-21) was used to measure participants' levels of anxiety, depression, and stress. Collect individual and occupational characteristics of survey respondents through self-administered questionnaires. Blood samples are also collected to measure high-density lipoprotein cholesterol levels and peripheral blood cell counts. We employed statistical analyses including correlation analysis, Receiver Operating Characteristic (ROC) curve analysis, and univariate and multivariate regression.

Results

The final sample size included in the analysis was 1,434. The results showed that stress, anxiety, and depressive symptoms were significantly correlated with all four HDL-related inflammatory indices (p < 0.05). Especially for MHR, compared to those without symptoms, individuals experiencing stress, anxiety, or depression had an OR of 2.75 (95% CI: 1.90, 3.99), 3.27 (95% CI: 2.25, 4.78), and 3.02 (95% CI: 2.08, 4.40) for abnormally high levels, respectively. In addition, subgroup analyses showed that lower monthly incomes, longer working hours and frequent night shifts might be promoting factors for elevated HDL-related inflammatory levels. Receiver Operating Characteristic (ROC) analysis further demonstrated that PHR and MHR exhibit good predictive ability for all three psychological symptoms, with AUC values exceeding 0.6. Notably, for individuals with over 30 years of work experience, the predictive performance AUC is even higher, reaching above 0.7.

Conclusion

The results of this study suggest that PHR and MHR are expected to be potential biomarkers for identifying health problems caused by negative psychological symptoms in occupational groups, providing valuable information for occupational mental health assessment. Preventive measures should be implemented for high-risk groups, including those with low income, long working hours, and frequent night shifts, to mitigate potential health impacts.

Relationships Between Burnout and Neuroticism Among Emergency Department Nurses: A Network Analysis

AIM

Although neuroticism has a negative impact on burnout among healthcare workers, there is little research exploring the specific interactions between different components of burnout and neuroticism. This study aims to investigate this relationship among nurses in Emergency Departments (ED) through network analysis method (NAM).

DESIGN

A cross-sectional investigative survey was conducted.

METHODS

A total of 408 Chinese nurses were recruited from ED of five hospitals in 2023 through Questionnaire Star. Components of burnout were measured by the 15-item Maslach Burnout Inventory-General Survey (MBI-GS), while components of neuroticism were measured by a subscale of the Eysenck Personality Questionnaire-Revised, Short Scale for Chinese (EPQ-RSC) questionnaire. NAM was applied to build relationship between components of burnout and neuroticism and identify the bridge expected influence (BEI).

RESULTS

Within burnout-neuroticism network, the relations between the components of burnout and neuroticism were mainly positive. Nt5 ('Anxious')-EE1 ('Exhausted'; weight = 0.281) and Nt5 ('Anxious')-EE5 ('Breakdown'; weight = 0.280) had stronger connections. Among the neuroticism, Nt5 ('Anxious') showed the strongest positive BEI, while Nt12 ('Guilty') showed the strongest negative BEI. Feeling anxiety and less guilt conscience in neuroticism were the critical factors to impact burnout of nurses in ED. Awareness of these relationships can help to develop strategies to identify and curtail burnout.

PATIENT OR PUBLIC CONTRIBUTION

A total of 408 emergency nurses participated in this survey.

Explanatory Models of Burnout Diagnosis Based on Personality Factors in Primary Care Nurses

Burnout in the primary care service takes place when there is a high level of interaction between nurses and patients. Explanatory models based on psychological and personality related variables provide an approximation to level changes in the three dimensions of the burnout syndrome. A categorical-response ordinal logistic regression model, based on a quantitative, crosscutting, multicentre, descriptive study with 242 primary care nurses in the Andalusian Health Service in Granada (Spain) is performed for each dimension. The three models included all the variables related to personality. The risk factor friendliness was significant at population level for the three dimensions, whilst openness was never significant. Neuroticism was significant in the models related to emotional exhaustion and depersonalization, whilst responsibility was significant for the models referred to depersonalization and personal accomplishment dimensions. Finally, extraversion was also significant in the emotional exhaustion and personal accomplishment dimensions. The analysis performed provides useful information, making more readily the diagnosis and evolution of the burnout syndrome in this collective.