Do family physicians, emergency department physicians, and pediatricians give consistent sport-related concussion management advice?
Bibliographic record
Abstract
OBJECTIVE: To identify differences and gaps in recommendations to patients for the management of sport-related concussion among FPs, emergency department physicians (EDPs), and pediatricians. DESIGN: A self-administered, multiple-choice survey was e-mailed to FPs, EDPs, and pediatricians. The survey had been assessed for content validity. SETTING: Two community teaching hospitals in the greater Toronto area in Ontario. PARTICIPANTS: Two hundred seventy physicians, including FPs, EDPs, and pediatricians, were invited to participate. MAIN OUTCOME MEASURES: Identification of sources of concussion management information, usefulness of concussion diagnosis strategies, and whether physicians use common terminology when explaining cognitive rest strategies to patients after sport-related concussions. RESULTS: The response rate was 43.7%. Surveys were completed by 70 FPs, 23 EDPs, and 11 pediatricians. In total, 49% of FP, 52% of EDP, and 27% of pediatrician respondents reported no knowledge of any consensus statements on concussion in sport, and 54% of FPs, 86% of EDPs, and 78% of pediatricians never used the Sport Concussion Assessment Tool, version 2. Only 49% of FPs, 57% of EDPs, and 36% of pediatricians always advised cognitive rest. CONCLUSION: This study identified large gaps in the knowledge of concussion guidelines and implementation of recommendations for treating patients with sport-related concussions. Although some physicians recommended physical and cognitive rest, a large proportion failed to consistently advise this strategy. Better knowledge transfer efforts should target all 3 groups of physicians.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".