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Record W2345241559 · doi:10.9778/cmajo.20150086

Principles of fatigue in residency education: a qualitative study

2016· article· en· W2345241559 on OpenAlexaffvenue
Taryn Taylor, Christopher Watling, Pim W. Teunissen, Timothy Dornan, Lorelei Lingard

Bibliographic record

VenueCMAJ Open · 2016
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsWestern University
Fundersnot available
KeywordsContext (archaeology)ConceptualizationMedical educationPsychologyGrounded theoryOccupational safety and healthHazardQualitative researchInclusion (mineral)Applied psychologyMedicineSocial psychologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Proposals to implement fatigue-management strategies in residency education assume that medicine shares the view of other risk-adverse industries that fatigue is hazardous. This view is an essential underpinning of fatigue-management strategies that other industries have embedded as part of their workplace occupational health and safety programs. We sought to explore how residents understand fatigue in the context of their training environment. METHODS: We interviewed 21 residents in 7 surgical and nonsurgical programs at Western University in 2014. All participants met the inclusion criteria of routinely working 24-hour call shifts while enrolled in their training program. Data collection and analysis occurred iteratively in keeping with constructivist grounded theory methodology and informed theoretical sampling to sufficiency. RESULTS: Four predominant principles of fatigue captured how the social learning environment shaped residents' perceptions of fatigue. These included the conceptualization of fatigue as (a) inescapable and therefore accepted, (b) manageable through experience, (c) necessary for future practice and (d) surmountable when required. INTERPRETATION: This study elaborates our understanding of how principles of fatigue are constructed and reinforced by the training environment. Whereas fatigue is seen as a collective hazard in other industries, our data showed that, in residency training, fatigue may be seen as a personal challenge. Consequently, fatigue-management strategies that conceptualize fatigue as an occupational threat may have a limited impact on resident behaviour and patient safety.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.146
GPT teacher head0.465
Teacher spread0.319 · 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

Citations21
Published2016
Admission routes2
Has abstractyes

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