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Record W4407243291 · doi:10.1055/s-0045-1803130

Exploring Professional Quality of Life, Self-Compassion and Wellness in Skull Base Surgeons

2025· article· en· W4407243291 on OpenAlexaff
Janissardhar Skulsampaopol, Sylvia Shitsama, Michael D. Cusimano

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2025
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsCompassionPsychologyQuality of life (healthcare)SkullQuality (philosophy)Base (topology)Medical educationMedicinePsychotherapistSurgeryPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Introduction: Skull base surgery (SBS) is a highly rewarding but at times stressful subspecialty given the complexity of patients and current work environments that can contribute to stress, anxiety and reduced professional quality of life for surgeons. Measures of professional quality of life include compassion satisfaction, compassion fatigue and burnout. Despite the importance of these issues, there are currently no studies that focus primarily on the elements of professional quality of life and other components of wellness among skull base surgeons (SBS). Objectives: This article aims to assess the levels of compassion satisfaction, self-compassion, self-esteem, compassion fatigue and burnout among (SBS) and compare these with non-skull base surgeons (non-SBS). Method: An international electronic survey, developed using a physician wellness framework, was distributed to neurosurgeons. Only those who responded to the question regarding their subspecialty were included in the analysis. Results: Out of a total of 250 responses, 47 were skull base surgeons (SBS) and 203 were non-skull base surgeons (non-SBS). More SBS were male (OR: 2.60, 95% CI: 1.02–7.89, p = 0.03) and practiced in academic centers (OR: 5.22, 95% CI: 2.25–13.51, p < 0.001) compared to non-SBS. There was no significant difference between SBS and non-SBS in terms of age, relationship status, work experience and region of practice. Both SBS and non-SBS had high compassion satisfaction (66 vs. 72.3%, p = 0.39), normal self-esteem (95.7 vs. 94.1%, p = 0.65), and similar rates of burnout (34 vs. 32.7%, p = 0.86). There was no significant difference in levels of self-compassion between the two groups. However, SBS HAD higher levels of compassion fatigue compared to non-SBS ( p = 0.004). SBS are more likely to experience high levels of anxiety, stress, and depression due to reaction/responses from the physician colleagues they work with compared to non-SBS (34.8 vs. 21.4%, OR: 1.96, 95% CI: 0.91–4.11, p = 0.055). Other sources of high levels of anxiety, stress, and depression reported by skull base surgeons (SBS) is from the reactions/responses from the patients they try to help (31.1%), people outside of work (20%), and non-medical colleagues, such as nurses and administrators (17.8%). Conclusion: Although SBS have high levels of compassion satisfaction, self-compassion and self-esteem which are protective factors against burnout, SBS experience higher levels of compassion fatigue compared to their non-SBS counterparts. Surgical/medical colleagues were found to be the most critical source of stress, anxiety, depression among SBS. To improve the wellness of SBS, it is vital to address both individual and organizational factors. Organized skull base surgery societies can take a leading role in advocating for and implementing comprehensive wellness strategies worldwide. Publication History Article published online: 07 February 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

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)0.003
metaresearch head score (Gemma)0.011
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.211
GPT teacher head0.382
Teacher spread0.171 · 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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Citations0
Published2025
Admission routes1
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