Does Sleep Quality Influence Recovery Outcomes After Postconcussive Injury in Children and Adolescents?
Bibliographic record
Abstract
OBJECTIVE: To determine whether objective parameters of sleep quality differ throughout recovery between children and adolescents who experienced an early return to school (RTS) and those who had a delayed RTS or did not return at all during the study period. SETTING: Sleep parameters reflective of sleep quality were evaluated in participants' natural sleeping habitat throughout 9 weeks postinjury. PARTICIPANTS: Ninety-four children and adolescents (aged 5-18 years) with diagnosed concussion. DESIGN: Prospective cohort. Participants followed RTS protocols. MAIN MEASURES: Actigraphy-derived estimates of total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), average arousal length (AAL), and number of arousals (NOAs) per hour were assessed. The length of time from injury until RTS was determined for each participant. Participants were categorized into an early RTS or delayed RTS group based on their time to RTS. RESULTS: Both TST and SE were significantly greater in the early RTS group. WASO duration, AAL, and NOAs were significantly greater in the delayed RTS group. Differences between RTS groups were most apparent during weeks 1 to 5 postinjury. CONCLUSIONS AND CLINICAL IMPLICATIONS: Participants who returned to school earlier had significantly better objective sleep quality than participants who experienced a delayed RTS. This study provides evidence in support of a relationship between sleep quality and time to RTS in children and adolescents with concussion. Considering early monitoring of sleep, education regarding sleep hygiene, and access to age-appropriate sleep interventions may be helpful in pediatric concussion 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".