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Record W1994882116 · doi:10.1097/bot.0000000000000003

The Effect of Sleep Deprivation on a Resident's Situational Awareness in a Trauma Scenario

2013· article· en· W1994882116 on OpenAlexaff
Alexandra Stratton, Andrew Furey, Micheal Hogan

Bibliographic record

VenueJournal of Orthopaedic Trauma · 2013
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineSleep deprivationSituational ethicsComprehensionPhysical therapyClinical psychologyPsychiatryCognitionPsychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: Situational awareness (SA) refers to the perception of elements in one's environment, the comprehension of their meaning, and the projection of their status in the near future. The SA global assessment technique (SAGAT) is an assessment tool validated for use in a trauma simulation. The goal of this study was to determine the effect of sleep deprivation on residents' performance in a trauma simulation, evaluated by the SAGAT. METHODS: A power analysis determined that 9 residents would be needed to show a significant difference in SAGAT scores (7%). Therefore, 9 surgical residents on an intensive care unit rotation underwent 2 trauma simulations. One session was performed in the rested condition, and the other was for postcall. The SAGAT was used to evaluate the residents' performance. The rested and postcall scores were compared. RESULTS: Using a paired t test, the SAGAT scores were analyzed. The average rested score was 80.13% (range, 50%-94%), and the sleep-deprived score was 80.09% (range, 72%-91%). There was no significant difference between the residents' rested and the postcall SAGAT scores (P = 0.99). CONCLUSIONS: From this study, the resident SA in a trauma simulation does not seem to be affected by 1 night of sleep deprivation, as demonstrated by the lack of significant difference in SAGAT scores; however, more research in this area is needed. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.022
GPT teacher head0.327
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2013
Admission routes1
Has abstractyes

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