Evidence map›Paper›PMID 35111713›Full record

ArticleFrontiers in public health2021

Burnout and Well-Being Among Medical Professionals in China: A National Cross-Sectional Study.

Ying Xiao, Dong Dong, Huanyu Zhang, Peipei Chen, Xiangyan Li, Zhuang Tian, Zhicheng Jing, Shuyang Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
10.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 40 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Ying XiaoState Key Laboratory of Complex Severe and Rare Diseases, Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Dong DongShenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
Huanyu ZhangShenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
Peipei ChenState Key Laboratory of Complex Severe and Rare Diseases, Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiangyan LiMedical Science Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Zhuang TianState Key Laboratory of Complex Severe and Rare Diseases, Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Zhicheng JingState Key Laboratory of Complex Severe and Rare Diseases, Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Shuyang ZhangState Key Laboratory of Complex Severe and Rare Diseases, Department of Cardiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Peking Union Medical College Hospital · CNChinese University of Hong Kong, Shenzhen · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo determine the profile of Chinese medical professionals with burnout symptoms at the national level and identify the association between capability well-being and burnout. DESIGN AND

settingA cross-sectional study in a nonrandom national sample of medical staff from 6 provinces across western, central and eastern China.

participantsPhysicians, medical laboratory scientists, nurses, and general practitioners aged 18 years or above who submitted a completed online questionnaire from June 2019 to January 2020 successfully (

main outcome measuresThe prevalence of burnout symptoms was assessed by the 22-item Maslach Burnout Inventory-Human Services Survey (MBI-HSS), which consists of three domains: emotional exhaustion (EE), depersonalization (DP), and personal achievement (PA). The overall high burnout was defined as EE score ≥27 or DP score ≥10. The capability well-being was measured by the Investigating Choice Experiments Capability Measure for Adults (ICECAP-A) and the overall ICECAP-A score was calculated using the UK value set, ranging from a score of 0-1. Multivariable logistic regression analysis was used to identify the association between well-being and the overall high burnout.

resultsAmong the 25,120 participants, 60.8% of the participants reported at least one symptom of burnout, whereas 11.2% reported all three symptoms of burnout. In the adjusted model, ICECAP-A score was independently associated with high burnout (AOR = 0.018, 95% CI = 0.015-0.022). Medical staff who were males, with shorter working years, working in tertiary hospitals, and those with the specialties of psychiatry, intensive care, emergency medicine, internal medicine, oncology, and pediatrics were at higher risk of reporting burnout symptoms.

conclusionThe burnout symptoms were relatively common among Chinese medical staff and they were found to be independently associated with capability well-being in health professionals. Interventions should be enhanced on vulnerable groups to reduce burnout and promote well-being in future studies.

Indexed as

Burnout, ProfessionalGeneral PractitionersAdultChildChinaCross-Sectional StudiesFemaleHumansMaleSurveys and Questionnairesburnoutcapability well-beingChinamedical professionalsnational-level

Identifiers

PMID35111713
PMCPMC8801677
OpenAlexW3126067682

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.