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Record W3016646899 · doi:10.1097/aln.0000000000003287

Stress Management Training Improves Overall Performance during Critical Simulated Situations

2020· article· en· W3016646899 on OpenAlexaboutno aff
Florent Sigwalt, Guillaume Petit, Jean‐Noël Evain, Damien Claverie, Monique Bui, Angélique Guinet-Lebreton, Marion Trousselard, Frédéric Canini, D. Chassard, Antoine Duclos, Jean-Jacques Lehot, Thomas Rimmelé, Marc Lilot

Bibliographic record

VenueAnesthesiology · 2020
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialClinical endpointPhysical therapyVisual analogue scaleRating scaleScale (ratio)SurgeryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: High-fidelity simulation improves participant learning through immersive participation in a stressful situation. Stress management training might help participants to improve performance. The hypothesis of this work was that Tactics to Optimize the Potential, a stress management program, could improve resident performance during simulation. METHODS: Residents participating in high-fidelity simulation were randomized into two parallel arms (Tactics to Optimize the Potential or control) and actively participated in one scenario. Only residents from the Tactics to Optimize the Potential group received specific training a few weeks before simulation and a 5-min reactivation just before beginning the scenario. The primary endpoint was the overall performance during simulation measured as a composite score (from 0 to 100) combining a specific clinical score with two nontechnical scores (the Ottawa Global Rating Scale and the Team Emergency Assessment Measure scores) rated for each resident by four blinded independent investigators. Secondary endpoints included stress level, as assessed by the Visual Analogue Scale during simulation. RESULTS: Of the 134 residents randomized, 128 were included in the analysis. The overall performance (mean ± SD) was higher in the Tactics to Optimize the Potential group (59 ± 10) as compared with controls ([54 ± 10], difference, 5 [95% CI, 1 to 9]; P = 0.010; effect size, 0.50 [95% CI, 0.16 to 0.91]). After specific preparation, the median Visual Analogue Scale was 17% lower in the Tactics to Optimize the Potential group (52 [42 to 64]) than in the control group (63 [50 to 73]; difference, -10 [95% CI, -16 to -3]; P = 0.005; effect size, 0.44 [95% CI, 0.26 to 0.59]. CONCLUSIONS: Residents coping with simulated critical situations who have been trained with Tactics to Optimize the Potential showed better overall performance and a decrease in stress level during high-fidelity simulation. The benefits of this stress management training may be explored in actual clinical settings, where a 5-min Tactics to Optimize the Potential reactivation is feasible prior to delivering a specific intervention.

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)0.000
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 score0.023
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.060
GPT teacher head0.337
Teacher spread0.278 · 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

Citations33
Published2020
Admission routes1
Has abstractyes

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