Burnout and depression among anesthesiology trainees in the United States: An updated National Survey

Bui, Danny; Winegarner, Andrew; Kendall, Mark C.; Almeida, Marcela; Apruzzese, Patricia; Oliveira, Gildasio De

doi:10.1016/j.jclinane.2022.110990

Cited by 8 publications

(6 citation statements)

References 14 publications

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“…Bui et al found working more than 70 h a week and overnight calls were independent risk factors for increased odds of burnout and independently associated with depression [ 5 ], findings similar to the results shown in 2013. Working longer hours continues to be a common risk factor for burnout and depression.…”

supporting

confidence: 75%

“…In a national survey of all anesthesiology trainees, Bui et al [ 5 ] reevaluated the prevalence of burnout and depression in anesthesiology trainees in the United States nearly a decade after their first evaluation in 2013. In addition, the authors desired to investigate the risk factors contributing to burnout and depression among anesthesiology residents utilizing an abbreviated version of the validated Maslach Burnout Inventory to assess job-related burnout.…”

mentioning

confidence: 99%

“…Despite the reported reduction in the Bui et al survey [ 5 ], burnout rates in anesthesiology trainees continue to be high and comparable to other specialties. The high burnout rate is concerning due to the association with higher rates of suicide and substance use in the field of anesthesiology.…”

mentioning

confidence: 99%

“…In addition to the prevalence of burnout, Bui et al reported the relationship between residents' burnout and the poor quality of patient care [ 5 ]. In a meta-analysis reviewing 82 studies, provider burnout was negatively associated with quality of care, including medical errors, patient satisfaction, quality indicators, and perceptions of safety [ 9 ].…”

mentioning

confidence: 99%

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Burnout and depression in anesthesiology trainees: A timely assessment to guide a roadmap for change

Mohamed

Fahy

2023

Journal of Clinical Anesthesia

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supporting

confidence: 75%

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confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Burnout and depression in anesthesiology trainees: A timely assessment to guide a roadmap for change

Mohamed

Fahy

2023

Journal of Clinical Anesthesia

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“…Furthermore, it has been associated with mental health disorders, including depression, anxiety disorders, substance abuse, and even suicide (7). Additionally, high levels of burnout have been shown to compromise patient safety and the overall quality of care, highlighting the need for early identi cation and prevention of nurse burnout (8,9). In this regard, developing a predictive model for nurse burnout is signi cant.…”

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confidence: 99%

Development and validation of a nomogram for predicting high-burnout risk in nurses

Ning,

Chen,

Yang

et al. 2023

Preprint

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Background Nurses are one of the occupational populations that are most susceptible to burnout and high-burnout nurses experienced significantly impacts their physical and mental health, and even compromises patient safety and the quality of care. Therefore, it is crucial to identify and prevent burnout among nurses at an early stage. Developing a predictive model for high-burnout is essential for this purpose. Methods A cross-sectional study was conducted among 2,750 Chinese nurses using an online survey. Data were collected by the 15-item Chinese Maslach Burnout Inventory-General Survey (CMBI-GS) and self-administered questionnaires that included demographic, behavioral, health-related, and occupational variables. Multivariate logistic regression analysis and nomogram were used to identify the factor associated with high-burnout risk. Stata 16.0 software was used for data analysis. Results A total of 2,750 nurses from 23 provinces of mainland China were included, with 1,925 participants (70%) in a development set and 825 participants (30%) in a validation set. Workplace violence, shift work, working time per week, depression, stress, self-reported health, and drinking were significant contributors to high-burnout risk and a nomogram was developed using these factors. The receiver operating characteristic (ROC) curve analysis demonstrated that the area under the curve (AUC) of the model was 0.808 in the development set and 0.790 in the validation set. For calibration analysis, the Hosmer-Lemeshow tests produced P values of 0.697 and 0.640 in the two sets, respectively. The nomogram demonstrated a high net benefit in the clinical decision curve in both sets. Conclusion This study has developed and validated a predictive nomogram for identifying high-burnout in nurses. The nomogram will assist nursing managers in identifying at-high-risk nurses, understanding related factors and implementing early interventions. Additionally, our study provides a tool for nurses to monitor their risk of high-burnout and overall mental health.

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Aftershock: The Rippling Effects of Abortion Restrictions Across US Society

Portney,

Sweet

2024

The Mental Health Clinician’s Handbook for Abortion Care

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Burnout and depression among anesthesiology trainees in the United States: An updated National Survey

Cited by 8 publications

References 14 publications

Burnout and depression in anesthesiology trainees: A timely assessment to guide a roadmap for change

Burnout and depression in anesthesiology trainees: A timely assessment to guide a roadmap for change

Development and validation of a nomogram for predicting high-burnout risk in nurses

Aftershock: The Rippling Effects of Abortion Restrictions Across US Society

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