Rest Evaluation for Active Concussion Treatment (ReAct) Protocol: a prospective cohort study of levels of physical and cognitive rest after youth sports-related concussion
Bibliographic record
Abstract
INTRODUCTION: Although current guidelines for the early clinical management of sports-related concussion (SRC) call for a gradual return-to-activity, the optimal level of rest needed to promote recovery remains unknown. This paper describes the protocol of the Rest Evaluation for Active Concussion Treatment (ReAct) study which objectively measures physical and cognitive rest following SRC and its relation to recovery among youth athletes. METHODS AND ANALYSIS: Youth athletes aged 11-17 years are recruited preinjury and enrolled within 72 hours following a physician-diagnosed concussion. Injury information and acute clinical presentation are assessed at the time of injury. Youth participants are prospectively followed to objectively monitor daily physical and cognitive rest using two electronic devices: ActiGraph (to measure physical rest and sleep) and Narrative Clip (to measure cognitive rest), along with self-reported postconcussive symptoms using daily surveys. Other concussion outcomes, including functional outcomes, are assessed by surveying youth and their parents at three time points: (1) within 72 hours of injury, (2) at day 7 postenrolment and (3) at symptom resolution (or a maximum of 45 days postconcussion). ETHICS AND DISSEMINATION: This study has received ethical approval from the Institutional Review Board (IRB) at the participating institution (IRB at Nationwide Children's Hospital, IRB16-00613). The results of the study will be presented at national and international scientific conferences and published in peer-reviewed journals.
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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 | 0.018 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".