Exploring Accelerometer Versus Self-Report Sleep Assessment in Youth With Concussion
Bibliographic record
Abstract
This study examines accelerometer-based and self-report assessment of sleep disturbance from a larger prospective cohort of youth 5 to 18 years of age with postconcussive injury. Twenty-one participants with self-reported sleep disturbance were evaluated using accelerometers. Participants completed the Pittsburgh Sleep Quality Index (PSQI) every 48 hours and also measured sleep via accelerometry. Correlations were conducted matching PSQI scores to accelerometry assessment. PSQI scores were significantly correlated only with “average number of awakenings” ( r = −0.21; P = .049). Accelerometer-measured mean (standard deviation) sleep efficiency was 79.9% (5.20%), with normal sleep defined as >85%. The mean (standard deviation) PSQI global score was 10.5 (3.78) out of 21, where scores of >5 indicate subjective insomnia. Results suggest the PSQI and accelerometers may be measuring different attributes of sleep. Both may be needed as actual sleep is important but so is perception of good sleep. These findings call for further validity testing of objective sleep assessment measures and commonly used self-report tools.
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 | 0.001 |
| 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".