Sleep Insufficiency and Baseline Preseason Concussion-Like Symptom Reporting in Youth Athletes
Bibliographic record
Abstract
OBJECTIVE: To examine the association between insufficient sleep and baseline symptom reporting in healthy student athletes. DESIGN: Cross-sectional cohort study. SETTING: Preseason testing for student athletes. PARTICIPANTS: Student athletes (n = 19 529) aged 13 to 19 years who completed the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), including the number of hours slept the night before, and denied having developmental/health conditions, a concussion in the past 6 months, and a previous history of 2 or more concussions. INDEPENDENT VARIABLES: Total hours of sleep the night before testing (grouped by ≤5, 5.5-6.5, 7-8.5, and ≥9 hours), gender, and concussion history. MAIN OUTCOME MEASURES: Symptom burden on the Post-Concussion Symptom Scale (modified to exclude sleep-related items), cognitive composite scores, and prevalence of athletes who reported a symptom burden resembling the International Classification of Diseases, 10th Revision (ICD-10) diagnosis of postconcussional syndrome (PCS). RESULTS: Fewer hours of sleep, gender (ie, girls), and 1 previous concussion (vs 0) were each significantly associated with higher total symptom scores in a multivariable model (F = 142.01, P < 0.001, R2 = 0.04). When a gender-by-sleep interaction term was included, the relationship between sleep and symptoms was stronger for girls compared with boys. In healthy athletes who slept ≤5 hours, 46% of girls and 31% of boys met the criteria for ICD-10 PCS compared with 16% of girls and 11% of boys who slept ≥9 hours. Sleep duration was not meaningfully associated with neurocognitive performance. CONCLUSIONS: Insufficient sleep the night before testing is an important factor to consider when interpreting symptom reporting, especially for girls. It will be helpful for clinicians to take this into account when interpreting both baseline and postinjury symptom reporting.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".