SynthesisJournal of general internal medicine2024
A Systematic Review of the Single-Item Burnout Question: Its Reliability Depends on Your Purpose.
Synthesis in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Chronic stress in relation to clinical burnout: an integrative scoping review of definitions and measurement approaches.Frontiers in psychology · 2025Pooled it
- Work-related Well-Being, Turnover Intention, and Completed Turnover in a Cohort of US Patient Care Workers.Journal of occupational and environmental medicine · 2026Article
- Training satisfaction, competency gaps and well-being in gastroenterology residency in Spain: results of a national SEPD survey.BMC gastroenterology · 2026Article
- Burnout in sickle cell disease-focused hematology-oncology-trained physicians: a national cross-sectional study.Blood advances · 2026Article
- Stress, burnout, and depressive symptoms among nurses in a Lebanese academic medical center: a cross-sectional wellness needs assessment.BMC nursing · 2026Article
- Benefits and harms of copyright restrictions and conditions on burnout and other psychometric assessment scales.PloS one · 2026Article
- The effect of previous team environment on the current motivation in Japanese varsity soccer players.Frontiers in sports and active living · 2026Article
- Thriving from Work Questionnaire: Validation of a Measure of Worker Wellbeing Among Older U.S. Workers.International journal of environmental research and public health · 2025Article
- Self-reported mental health outcomes of International medical graduates in Australia: a cross-sectional survey.Frontiers in medicine · 2025Article
- Comment on study by Hagan et al.: The Single-Item Burnout Question.Journal of general internal medicine · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSurveillance of burnout by the gold-standard Maslach Burnout Inventory (MBI) is hindered by cost and length. The validity and benchmarking of the commonly recommended and used single-item burnout question (SIBOQ) are unknown. We sought to (1) derive an equation for predicting the gold standard MBI from the SIBOQ and (2) measure the correlation of the SIBOQ with the full MBI and its subscales.
methodsWe sought studies in PubMed along with citations by and to included studies. We included studies that either correlated the SIBOQ and the MBI or reported the rates of burnout measured by both instruments. Two reviewers extracted data and CLARITY risk of bias. We used generalized linear mixed regression to separately quantify the predictive (benchmarking) and explanatory (hot-spotting) capabilities of the SIBOQ. We created a regression equation for converting SIBOQ scores to MBI scores. We meta-analyzed correlation coefficients (r) for the SIBOQ and MBI subscales. For all analyses, we considered an r of 0.7 as acceptable reliability for group-level comparisons.
resultsWe included 17 studies reporting 6788 respondents. All studies had a high risk of bias, as no study had a response rate over 75% and no study was able to examine non-responders. The correlations (r) of the SIBOQ with the overall MBI were explanatory r = 0.82 and predictive r = 0.56. Regarding MBI subscales, the correlations of the SIBOQ with emotional exhaustion were adequate with r = 0.71 (95% CI 0.67-0.74; I DISCUSSION: The SIBOQ's usually adequate explanatory abilities allow "hot-spotting" to identify subgroups with high or low burnout within a single, homogenous survey fielding. However, the predictive ability of the SIBOQ indicates insufficient reliability in comparing local results to external benchmarks.
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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.