The Barriers and Facilitators to Transfer of Ultrasound-Guided Central Venous Line Skills From Simulation to Practice: Exploring Perceptions of Learners and Supervisors
Bibliographic record
Abstract
UNLABELLED: PHENOMENON: Ultrasound-guided central venous line insertion is currently the standard of care. Randomized controlled trials and systematic reviews show that simulation is superior to apprenticeship training. The purpose of this study is to explore, from the perspectives of participants in a simulation-training program, the factors that help or hinder the transfer of skills from simulation to practice. APPROACH: Purposeful sampling was used to select and study the experience and perspective of novice fellows after they had completed simulation training and then performed ultrasound-guided central venous line in practice. Seven novice pediatric intensive care unit fellows and six supervising faculty in a university-affiliated academic center in a large urban city were recruited between September 2012 and January 2013. We conducted a qualitative study using semistructured interviews as our data source, employing a constructivist, grounded theory methodology. FINDINGS: Both curricular and real-life factors influence the transfer of skills from simulation to practice and the overall performance of trainees. Clear instructions, the opportunity to practice to mastery, one-on-one observation with feedback, supervision, and further real-life experiences were perceived as factors that facilitated the transfer of skills. Concern for patient welfare, live trouble shooting, complexity of the intensive care unit environment, and the procedure itself were perceived as real-life factors that hindered the transfer of skills. Insights: As more studies confirm the superiority of simulation training versus apprenticeship training for initial student learning, the faculty should gain insight into factors that facilitate and hinder the transfer of skills from simulation to bedside settings and impact learners' performances. As simulation further augments clinical learning, efforts should be made to modify the curricular and bedside factors that facilitate transfer of skills from simulation to practice settings.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".