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Record W2009976210 · doi:10.1080/10401334.2014.859932

Impact of Acute Stress on Resident Performance During Simulated Resuscitation Episodes: A Prospective Randomized Cross-Over Study

2014· article· en· W2009976210 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

VenueTeaching and Learning in Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStressorMedicineStress (linguistics)ResuscitationEmergency medicinePhysical therapyClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Medical trainees have identified stress as an important contributor to their medical errors in acute care environments. PURPOSES: The objective of this study was to determine if the addition of acute stressors to simulated resuscitation scenarios would impact on residents' simulated clinical performance. METHODS: Fifty-four residents completed a control and a high-stress simulated scenario on separate visits. Stress measures were collected before and after scenarios. Two assessors independently evaluated residents' videotaped performance. RESULTS: Both control and high-stress scenarios triggered significant stress responses among participants; however, stress responses were not significantly different between control and high-stress conditions. No difference in performance was found between control and high-stress conditions (F value = 2.84, p = .098). CONCLUSIONS: Residents exposed to simulated resuscitation scenarios experienced significant stress responses irrespective of the presence of acute stressors during these scenarios. This anticipatory stressful response could impact on resident learning and performance and should be further explored.

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)0.005
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 score0.067
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.016
GPT teacher head0.402
Teacher spread0.386 · 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