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Record W4417265949 · doi:10.62199/2475-4757.1316

Evaluating Ergonomics Education in United States Ophthalmology Residency Programs

2025· article· en· W4417265949 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Academic Ophthalmology · 2025
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Health Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHuman factors and ergonomicsCurriculumOccupational safety and healthPoison controlSuicide preventionInjury prevention

Abstract

fetched live from OpenAlex

Background: Musculoskeletal disorders are prevalent among ophthalmologists because of occupational risks that include repetitive movements and uncomfortable postures. Teaching proper ergonomic practices early in an ophthalmologist’s career may help avoid outcomes such as chronic pain and early retirement. Purpose: To investigate the level of formal ergonomics education in U.S. ophthalmology residencies. Methods: An Association of University Professors of Ophthalmology (AUPO) approved survey was distributed to program directors and coordinators of 113 residency programs via the AUPO email listserv. Results: The survey had a response rate of 33.6%. Of the 38 programs that responded, only 13 (34.2%) had a formal ergonomics curriculum. The average instruction time was 2.25 hours per year, with didactic sessions being the primary mode of education. Although 80% of respondents from programs with ergonomics curricula considered ergonomic education “very important,” only 60% of those without formal curricula did. Conclusion: Despite sporadic teaching in some programs, there is a significant gap in standardized ergonomics education across residencies.

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.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.202
GPT teacher head0.578
Teacher spread0.376 · 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