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Record W4397007149 · doi:10.1016/j.jvsvi.2024.100083

Exploring work-life integration in vascular surgery and surgery

2024· article· en· W4397007149 on OpenAlexaff
Cedric Keutcha Kamani, Shreya Jalali, Rita Mancini, Melissa Bouhraoua, Dawn M. Coleman, Laura M. Drudi

Bibliographic record

VenueJVS-Vascular Insights · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversité de MontréalWestern UniversityCentre Hospitalier de l’Université de MontréalUniversity of British Columbia
Fundersnot available
KeywordsWork (physics)Vascular surgeryMedicineSurgeryGeneral surgeryCardiac surgeryEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Introduction There is a growing emphasis on achieving work-life balance (WLB), defined as the balance between work and personal life. However, this concept is gradually shifting towards work-life integration (WLI), which is relevant in the healthcare sector, particularly surgery. We performed a literature review to evaluate factors that contribute to WLI in the field of surgery, with a particular focus on vascular surgery. Methods A literature review of WLI in surgery, specifically vascular surgery, was performed from inception to February 2024. PubMed was searched for papers written in the English and French languages using the MeSH terms "work-life balance" or "work-life integration" in "vascular surgery" or "surgery." Findings were categorized in a tiered framework focused on faculty or staff, trainees (including medical students, residents, or fellows), and people identifying as underrepresented in medicine (URIM). Results Twenty-four articles were identified as relevant for this review. Previous reports have identified a high prevalence of burnout and suicide among the vascular surgery workforce. Collegial support and institutional culture were identified as pivotal in enhancing WLI. Inefficiencies in healthcare delivery, administrative burdens, and a lack of autonomy were recognized as barriers for WLI. Factors specific to gender and parenthood lead to unequal challenges in achieving WLI. Medical trainees' WLI perceptions influenced their specialty choices and risk of burnout. Also, URIM trainees encountered additional obstacles like discrimination and attrition, though some reports indicated a resilience advantage among minority physicians. Conclusion This review has highlighted differences in challenges related to WLI across faculty and staff, trainees, and individuals identifying as URIM and emphasizes the need for systemic and cultural reforms, flexible work arrangements, and greater support for underrepresented groups to foster a healthier work-life ecosystem in healthcare.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0120.012
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.126
GPT teacher head0.270
Teacher spread0.144 · 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 designQualitative
DomainIncentives
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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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