An examination of concussion education programmes: a scoping review methodology
Bibliographic record
Abstract
OBJECTIVES: The primary purpose was to review the literature on concussion education programmes. The secondary purpose was to inform knowledge translation strategies for concussion researchers and practitioners. DESIGN: Research on concussion education programmes is relatively new. As a result, the current study implemented a scoping review methodology, which is a type of literary search used to provide a preliminary assessment of the size and scope of a body of literature, as well as identify strengths, weaknesses and gaps in the research. METHODS: A five-stage process for conducting a scoping review was followed for this study: (a) identifying the research questions, (b) identifying relevant studies, (c) identifying the study selection criteria, (d) charting the data and (e) reporting the results. RESULTS: Concussion education programmes have been developed and implemented with populations ranging in age from 9 to 49 years and have used interactive oral presentations, educational videos and computer-based learning programmes. Although the content of these programmes varied, the topics generally addressed salient aspects of concussion injury and recovery. Quantitative instruments have been the preferred methods for assessment. CONCLUSIONS: Education programmes aimed at improving participants' long-term concussion knowledge, behaviours and attitudes of concussions are needed. Researchers must consider using a knowledge translation framework to enhance concussion education programmes. The application of such a framework can lead to novel and interesting ways of disseminating information about concussive injury and recovery.
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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 | 0.056 | 0.109 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.032 | 0.024 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".