Cognitive appraisals and team performance under stress: A simulation study
Bibliographic record
Abstract
OBJECTIVES: The present study explored how challenge and threat responses to stress relate to performance, anxiety, confidence, team identity and team characteristics (time spent in training and postgraduate experience) in a medical simulation-based team competition. METHODS: The study was conducted during a national simulation-based training event for residents, the SIMCUP Italia 2018. The SIMCUP is a simulation competition in which teams of four compete in simulated medical emergency scenarios. Cross-sectional data were collected prior to the 3 days of the competition. Subjects included 95 participants on 24 teams. Before the competition on each day, participants completed brief self-report measures that assessed demands and resources (which underpin challenge and threat responses to stress), cognitive and somatic anxiety, self-confidence and team identification. Participants also reported time (hours) spent practising as a team and years of postgraduate experience. A team of referees judged each scenario for performance and assigned a score. A linear mixed model using demands and resources was built to model performance. RESULTS: The data showed that both demands and resources have positive effects on performance (31 [11-50.3] [P < .01] and 54 [25-83.3] [P < .01] percentage points increase for unitary increases in demands and resources, respectively); however, this is balanced by a negative interaction between the two (demands * resources interaction coefficient = -10 [-16 to -4.2]). A high level of resources is associated with better performance until demands become very high. Cognitive and somatic anxieties were found to be correlated with demands (Pearson's r = .51 [P < .01] and Pearson's r = .48 [P < .01], respectively). Time spent training was associated with greater perceptions of resources (Pearson's r = .36 [P < .01]). CONCLUSIONS: We describe a model of challenge and threat that allows for the estimation of performance according to perceived demands and resources, and the interaction between the two. Higher levels of resources and lower demands were associated with better performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".