Longitudinal trajectories of sleep duration in the general population.
Bibliographic record
Abstract
BACKGROUND: Sleep duration has been associated with overall health status, health behaviours, and mortality. Little is known about habitual longitudinal patterns of sleep in the general population. Furthermore, evidence about whether sleep duration has declined in recent years is contradictory. DATA AND METHODS: The study was based on 8,673 adults aged 18 or older in 2002/2003 (cycle 5 of the National Population Health Survey) and used five self-reported biennial measurements of sleep duration spanning eight years. Multiple distinct trajectories of sleep duration were estimated using latent class growth modeling. RESULTS: Four modelled trajectories of sleep duration were identified: short (11.1% of the population); low-normal (49.4%); high-normal (37.0%); and long (2.4%). The short, low-normal and high-normal sleep trajectories each exhibited a slight linear decline in hours of sleep over the eight years of follow-up. Poor sleep quality was predictive of trajectory group membership and associated with a decrease in sleep duration for three of the four groups. Age and sex were also significant predictors of trajectory group membership. INTERPRETATION: Trajectory analysis is a useful descriptive tool in the investigation of sleep duration over time.
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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 | 0.003 |
| 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 | 0.000 | 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".