Cricothyroidotomy In Situ Simulation Curriculum (CRIC Study)
Bibliographic record
Abstract
INTRODUCTION: Technical skill acquisition for rare procedures can be challenging given the few real-life training opportunities. In situ simulation (ISS), a training technique that takes place in the actual workplace, is a promising method to promote environmental fidelity for rare procedures. This study evaluated a simulation-based technical skill curriculum for cricothyroidotomy using deliberate practice, followed by an ISS evaluation session. METHODS: Twenty emergency medicine residents participated in a two-part curriculum to improve cricothryoidotomy performance. A pretest established participant baseline technical skill. The training session consisted of two parts, didactic teaching followed by deliberate practice using a task-training manikin. A posttest consisted of an unannounced, high-fidelity ISS, during an emergency department shift. The primary outcome was the mean performance time between the pretest and posttest sessions. Skill performance was also evaluated using a checklist scale and global rating scale. RESULTS: Cricothyroidotomy performance time improved significantly from pretest to posttest sessions (mean difference, 59 seconds; P < 0.0001). Both checklist and global rating scales improved significantly from the pretest to the posttest with a mean difference of 1.82 (P = 0.002) and 6.87 (P = 0.0025), respectively. Postcourse survey responses were favorable for both the overall curriculum experience and the unannounced ISS. CONCLUSIONS: This pilot study demonstrated that unannounced ISS is feasible and can be used to effectively measure cricothyroidotomy performance among EM residents. After a two-part training session consisting of didactic learning and deliberate practice, improved cricothyroidotomy skill performance was observed during an unannounced ISS in the emergency department. The integration of ISS in cricothyroidotomy training represents a promising approach; however, further study is needed to establish its role.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".