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Record W4391990452 · doi:10.1055/s-0044-1780101

What’s Wrong with Mentorship in Skull Base Surgery and What Needs to Change

2024· article· en· W4391990452 on OpenAlexaff
Janissardhar Skulsampaopol, Sylvia Shitsama, Michael D. Cusimano

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMentorshipSkullBase (topology)Computer scienceMedicineMedical physicsSurgeryMedical educationMathematics

Abstract

fetched live from OpenAlex

Introduction: Skull base surgery is known to be one of the most challenging surgical subspecialties. To become a successful and resilient skull base surgeon (SBS) not only requires proper training but also a mentor who can give guidance about career journey, a family or other support, that is particularly important to life outside work and ultimately to resilience or burnout. Nevertheless, there has been no previous literature investigating mentorship and other aspects of life outside surgery for SBS. Objectives: 1. Assess the current state, characteristics, and, gaps in the mentorship of SBS. 2. Compare mentorship among SBS and non-SBS. Methods: International survey of neurosurgeons (SBS and non-SBS) with uni- and multivariate analyses. Results: Of 404 respondents, 250 who specified their subspecialties ( n = 47 SBS, n = 203 non-SBS) were included. Two-thirds of SBS (66%) had a mentor. Most have one to two mentors and 84% of mentors are other neurosurgeons. All of those who have a mentor reported that mentorship covers surgery/work-related issues, while half provided mentorship in research. A minority provided mentorship in the area of home-life issues (25.8%), emotional support (12.9%), and leisure issues (3.2%). Most mentorship is either both formal or informal (41.9%) or informal (38.7%). Nearly half (48.4%) receive mentorship once a month. In comparing SBS and non-SBS, SBS were over represented by males (OR: 2.60, 95% CI: 1.01–7.89, p = 0.03), work in academic centers (OR: 5.22, 95% CI: 2.25–13.5, p < 0.001), have mentors (OR: 2.16, 95% CI: 1.07–4.49, p = 0.02), other mentors (OR: 2.57, 95% CI: 1.10–6.69, p = 0.02), and be offered leadership positions than non-SBS (OR: 4.3, 95% CI: 1.46–17.16, p = 0.004). There were no differences in SBS and non-SBS for marital status, having a child, age that they had the first child, accessing mentorship program, number of mentors, formality and satisfaction of mentorship, their most important mentor, frequency that they prefer to receive, and perspectives regarding gender of mentor and mentee. Conclusion: SBS more frequently have mentors than non-SBS, but those mentors for both groups generally focus solely on work-related guidance. However, to develop resilience in SBS and non-SBS requires a broader conception of mentorship that includes aspects of life outside of work. We propose that training programs, professional societies, and individual mentees and mentors need to take leadership to embrace this new and broad concept of mentorship. Doing so, has broad implications that will not only benefit the individual, but ultimately patients. Publication History Article published online: 05 February 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 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)0.035
metaresearch head score (Gemma)0.141
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.965
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.141
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0110.014
Scholarly communication0.0180.024
Open science0.0050.007
Research integrity0.0110.018
Insufficient payload (model declined to judge)0.0150.002

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 head0.113
GPT teacher head0.294
Teacher spread0.181 · 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.

Study designNot applicable
DomainIncentives
GenreCommentary

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
Published2024
Admission routes1
Has abstractyes

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