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Record W6921000265 · doi:10.6084/m9.figshare.17076465

Impact of the resident duty hours on in-training examination score: A nationwide study in Japan

2021· article· en· W6921000265 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDutySignificant differenceNames of the days of the weekMean differenceBalance (ability)

Abstract

fetched live from OpenAlex

The relationship between duty hours (DH) and the performance of postgraduate residents is needed to establish appropriate DH limits. This study explores their relationship using the General Medicine In-training Examination (GM-ITE). In this cross-sectional study, GM-ITE examinees of 2019 had participated. We analyzed data from the examination and questionnaire, including DH per week (eight categories). We examined the association between DH and GM-ITE score, using random-intercept linear models with and without adjustments. Five thousand five hundred and ninety-three participants (50.7% PGY-1, 31.6% female, 10.0% university hospitals) were included. Mean GM-ITE scores were lower among residents in Category 2 (45–50 h; mean score difference, −1.05; <i>p</i> p = 0.008) compared with residents in Category 5 (60–65 h; Reference). PGY-2 residents in Categories 2–4 had lower GM-ITE scores compared to those in Category 5. University residents in Category 1 and Category 5 showed a large mean difference (−3.43; <i>p</i> = 0.01). DH &lt;60–65 h per week was independently associated with lower resident performance, but more DH did not improve performance. DH of 60–65 h per week may be the optimal balance for a resident's education and well-being.

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)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.080
GPT teacher head0.355
Teacher spread0.275 · 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 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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