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Record W4390703284 · doi:10.1097/ta.0000000000004223

Trauma surgeons experience compassion fatigue: A major metropolitan area survey

2024· article· en· W4390703284 on OpenAlexaboutno aff
Lea Hoefer, Leah C. Tatebe, Purvi P. Patel, Anna F. Tyson, Samuel Kingsley, Grace Chang, Matt Kaminsky, James Doherty, David Hampton

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsCompassion fatigueMedicineBurnoutClinical psychologyUnivariate analysisCoping (psychology)Quality of life (healthcare)EmpathyPsychologyDemographyInternal medicineMultivariate analysisPsychiatryNursing

Abstract

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INTRODUCTION: Compassion fatigue (CF), the physical, emotional, and psychological impact of helping others, is composed of three domains: compassion satisfaction (CS), secondary traumatic stress (STS), and burnout (BO). Trauma surgeons (TSs) experience work-related stress resulting in high rates of CF, which can manifest as physical and psychological disorders. We hypothesized that TSs experience CF and there are potentially modifiable systemic factors to mitigate its symptoms. METHODS: All TSs in a major metropolitan area were eligible. Personal and professional demographic information was obtained. Each participant completed six validated surveys: (1) Professional Quality of Life scale, (2) Perceived Stress Scale, (3) Multidimensional Scale of Perceived Social Support, (4) Adverse Childhood Events Questionnaire, (5) Brief Coping Inventory, and (6) Toronto Empathy Questionnaire. Compassion fatigue subscale risk scores (low, <23; moderate, 23-41; high, >41) were recorded. Linear regression analysis assessed the demographic and environmental factors association with BO, STS, and CS. Variables significant on univariate analysis were included in multivariate models to determine the independent influence on BO, STS, and CS. Significance was p ≤ 0.05. RESULTS: There were 57 TSs (response rate, 75.4% [n = 43]; White, 65% [n = 28]; male, 67% [n = 29]). Trauma surgeons experienced CF (BO, 26 [interquartile range (IQR), 21-32]; STS, 23 [IQR, 19-32]; CS, 39 [IQR, 34-45]). The Perceived Stress Scale score was significantly associated with increased BO (coefficient [coef.], 0.52; 95% confidence interval [CI], 0.28-0.77) and STS (coef., 0.44; 95% CI, 0.15-0.73), and decreased CS (coef., -0.51; 95% CI, -0.80 to -0.23) ( p < 0.01). Night shifts were associated with higher BO (coef., 1.55; 95% CI, 0.07-3.03; p = 0.05); conversely, day shifts were associated with higher STS (coef., 1.94; 95% CI, 0.32-3.56; p = 0.03). Higher Toronto Empathy Questionnaire scores were associated with greater CS (coef., 0.33; 95% CI, 0.12-0.55; p < 0.01). CONCLUSION: Trauma surgeons experience moderate BO and STS associated with modifiable system- and work-related stressors. Efforts to reduce CF should focus on addressing sources of workplace stress and promoting empathic care. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.477
Teacher spread0.362 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2024
Admission routes1
Has abstractyes

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