Effect of simulation on cognitive load in health care professionals and students: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: The objective of this review is to assess the effect of simulation activities and their design features on cognitive load in health care professionals and students. INTRODUCTION: Simulation activities are now widely implemented in health care professionals' education. However, the mechanisms by which simulations and their design features lead to health care professionals' and students' learning remains unclear. Still, because of their high interactivity and complexity, simulation activities have the potential to impact the cognitive load of learners. Synthesizing evidence regarding this phenomenon could help simulation educators identify the design features that affect learners' cognitive load, and explain why some simulation activities are more effective than others. INCLUSION CRITERIA: This review will consider experimental and quasi-experimental studies in which the effect of a simulation activity on cognitive load in health care professionals or students from any discipline or level of practice is evaluated. All academic and health settings will be included. METHODS: Following the guidelines of the JBI methods for systematic reviews of effectiveness, CINAHL, Embase, ERIC, MEDLINE, PsycINFO, and Web of Science will be searched for studies published in English or French, without a date limit. Retrieved studies will be independently screened for inclusion, then critically appraised for methodological quality by two reviewers using standardized JBI tools. Data extraction will be done independently using adapted tools from JBI. Where possible, data will be pooled using meta-analytical methods. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42020187723.
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 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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".