A Systematic Review of the Evidence for Using Simulation to Replace Clinical Experience for Paramedic Students
Bibliographic record
Abstract
Background In health professions education there is a shortage of clinical training opportunities and an increasing demand for workers, creating a need for alternative methods to clinical placements. One alternative method to replace clinical experience is simulation-based education. Currently, the efficacy of simulation as a clinical replacement in paramedicine is unknown. To understand the current state of evidence for substituting clinical experience with simulation in paramedic education, provide implications for SBE implementation, and direct further research in this area a systematic review, following the PRISMA checklist guide, was conducted. Methods Five databases were searched. Primary source studies of all designs investigating replacing clinical experience in paramedicine were included, with eight articles assessed for eligibility screening. Three studies were selected for final inclusion, quality assessment and critical appraisal. Results Inter-rater reliability was good for the quality assessment and quality appraisal ratings were moderate to strong, though the articles were of low levels of evidence. None of the studies directly addressed whether simulation-based education can be used as a clinical replacement, though both learners and program directors found value in simulation and felt a combination of simulation and clinical time was best. Communication skills and high-acuity low-frequency situations were identified as most appropriate for simulation substitution. Discussion The findings of the systematic review indicate a willingness to engage in simulation to replace some clinical experience and certain skill areas that could be suitable for simulation, but no practical recommendations can be made due to the low level of study design based on the levels of evidence and lack of evidence for direct clinical substitution. Simulation as a replacement for clinical experience has support in other health professions, but further research is needed in paramedicine to investigate its efficacy and to inform future educational 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 | 0.021 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".