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Record W4395467277 · doi:10.1097/mog.0000000000001034

Ergonomic wellness for the trainee in gastrointestinal endoscopy

2024· review· en· W4395467277 on OpenAlexaff
Nikko Gimpaya, William T. Tran, Samir C. Grover

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2024
Typereview
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHuman factors and ergonomicsAdaptabilityMedicineCurriculumParticipatory ergonomicsPsychological interventionMedical educationPsychologyNursingPoison controlMedical emergencyPedagogy

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Endoscopy-related injuries (ERIs) are prevalent in gastrointestinal endoscopy. The aim of this review is to address the growing concern of ERIs by evaluating the ergonomic risk factors and the efficacy of interventions and educational strategies aimed at mitigating these risks, including novel approaches. RECENT FINDINGS: ERIs are highly prevalent, exacerbated by factors such as repetitive strain, nonneutral postures, suboptimal equipment design, and the procedural learning curve. Female sex and smaller hand sizes have been identified as specific risk factors. Recent guidelines underscore the importance of ergonomic education and the integration of ergonomic principles into the foundational training of gastroenterology fellows. Advances in equipment design focus on adaptability to different hand sizes and ergonomic positions. Furthermore, the incorporation of microbreaks and macrobreaks, along with neutral monitor and bed positioning, has shown promise in reducing the incidence of ERIs. Wearable sensors may be helpful in monitoring and promoting ergonomic practices among trainees. SUMMARY: Ergonomic wellness is paramount for gastroenterology trainees to prevent ERIs and ensure a sustainable career. Effective strategies include ergonomic education integrated into curricula, equipment design improvements, and procedural adaptations such as scheduled breaks and optimal positioning. Sensor-based and camera-based systems may allow for education and feedback to be provided regarding ergonomics to trainees in the future.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.138
GPT teacher head0.427
Teacher spread0.289 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations5
Published2024
Admission routes1
Has abstractyes

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