Development and feasibility of an evidence-informed self-management education program in pediatric concussion rehabilitation
Bibliographic record
Abstract
BACKGROUND: Concussion is a considerable public health problem in youth. However, identifying, understanding and implementing best evidence informed recovery guidelines may be challenging for families given the vast amount of information available in the public domains (e.g. Internet). The objective of this study was to develop, implement and evaluate the feasibility of an evidence-informed self-management education program for concussion recovery in youth. METHODS: Synthesis of best evidence, principles of knowledge translation and exchange, and expert opinion were integrated within a self-management program framework to develop a comprehensive curriculum. The program was implemented and evaluated in a children's rehabilitation hospital within a universal health care system. A retrospective secondary analysis of anonymous data from a program evaluation survey was used to evaluate program feasibility, to identify features of importance to program participants and to assess changes in participants' knowledge. RESULTS: The program, "Concussion & You" includes a comprehensive, evidence informed, population specific curriculum that teaches participants practical strategies for management of return to school and play, sleep, nutrition, relaxation and energy conservation. A 'wheel of health' is used to facilitate participants' self-management action plan. Results from eighty-seven participant surveys indicate that the program is feasible and participant knowledge increased in all areas of the program with the highest changes reported in knowledge about sleep hygiene, rest and energy conservation. CONCLUSION: Findings indicate that "Concussion & You" is a feasible program that is acceptable to youth and their families, and fills a health system service gap.
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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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".