RESIDENTS’ AND RECENT GRADUATES’ PERSPECTIVES ON SIMULATION TRAINING IN NEONATAL RESUSCITATION COMPETENCY ACQUISITION
Bibliographic record
Abstract
Abstract BACKGROUND Simulation training has been incorporated into Canadian residency programs in order to teach both the technical and behavioral skills of resuscitation. Current literature speaks to ‘improvement’ in skills following a simulation encounter. Residents’ perspectives on competency acquisition through simulation training have not been previously reported. OBJECTIVES To explore the perspectives of residents and recent graduates on simulation as an educational modality for competency acquisition in neonatal resuscitation DESIGN/METHODS This project employed an interpretive design qualitative methodology, using an a priori educational theory incorporating the principles of social cognitive theory, deliberate practice, distributive practice, and ‘choke phenomenon’. Semi structured focus groups of residents and paediatricians were used for data collection. Interpretive analysis in the style of Crabtree and Miller was employed. Data validity was optimized through member checking and triangulation of themes across investigators. Validity criteria as described by Lincoln and Guba were applied. Institutional ethics board approval was obtained. RESULTS Participants recognized the important role of simulation which allowed for a safe space to practice in order to become familiar with the algorithm and the equipment of resuscitation. Strengths associated with simulation training included: teaching geared toward the junior learner on the team, the opportunity to build and consolidate learning, and ideal preparation for examinations. In particular, given the current limited neonatal clinical exposure (constraints of reduced workload and hours), simulation was often seen as the trainee’s only opportunity for leading resuscitation. However, both groups of participants highlighted that for neonatal resuscitation the technology was less important than the scenario itself, i.e. ‘high fidelity is not the doll, it’s the stress of the situation’. They identified a lack of the ‘fear’ element in simulated scenarios, with a controlled comfortable environment, artificial ‘time component’, and ‘hypothetical resolution’ of every scenario. Finally, participants identified another potential pitfall of simulation which led to overconfidence and a false sense of expertise that cannot be translated to the ‘real baby’. CONCLUSION Participants perceived simulation to be a useful training modality for aspects of competency acquisition in neonatal resuscitation but highlighted a number of challenges and gaps toward preparedness for practice. In the development of future curricula in competency based training models, educators should consider in the design, graduated levels of simulation aimed toward transition to practice.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".