Observational studyMedicine2020
High rate of burnout among residents under standardized residency training in a tertiary teaching hospital of middle China: Results from a cross-sectional survey.
Observational study in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Prevalence of burnout among university students in low- and middle-income countries: A systematic review and meta-analysis.PloS one · 2021Pooled it
- Sudden unexpected physicians' death during performing professional duties: increasing social and public health problem.International journal of occupational medicine and environmental health · 2026Review
- Post-call rest regulation and its association with residency program preferences in Türkiye: focus on cardiovascular surgery.BMC medical education · 2026Article
- Empathy fatigue among physicians and its influencing factors: a cross-sectional survey from Southwest China.BMC psychiatry · 2024Article
- The association of sleep quality and burnout among Chinese medical residents under standardized residency training in a tertiary hospital.Sleep & breathing = Schlaf & Atmung · 2023Article
- The Nurse-Physician Relationship During the COVID-19 Pandemic in Shanghai, China: Cross-sectional Study.JMIR formative research · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Burnout has been commonly observed in health care workers. Though research has been conducted involving burnout among doctors in China, few studies have focused on residents during standardized residency training (SRT). The professional status of the residents during SRT remains largely unclear. The present study was conducted in order to clarify the prevalence and potential risk factors of burnout in residents during SRT.An electronic questionnaire comprised 2 parts. The first part was designed to collect some basic characteristic information. Maslach Burnout Inventory-Human Services Survey was included in the second part.As many as 71.05% residents had at least 1 scale of burnout. Emotional exhaustion (EE) was found in 55.6% residents, depersonalization (DP) in 29.7% and reduced personal accomplishment (RPA) in 41.6%. Being older than 27, senior SRT year, working time more than 60 hours per week and poor sleeping quality was independently associated with at least on scale of burnout. Being unable to receive timely supervisor support significantly increased the probability of DP and EE. Not having friends at work or feeling cared for by the hospital were independently related to all 3 symptoms of burnout as well as overall burnout.Burnout rate is high in residents under SRT from middle part of China. Organizational, professional, and social support was demonstrated critical by the potential roles in protecting against burnout. Residents with burnout were prone to considering turnover. Strategies for managing burnout related factors among residents should be focused in future studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.