Secondhand Smoke Exposure, Restless Sleep, and Sleep Duration in Adolescents
Bibliographic record
Abstract
Purpose. To examine whether secondhand smoke (SHS) exposure is associated with restless sleep and/or nighttime sleep duration among adolescents. Methods. Data were analyzed from 1,592 adolescents who completed an internet-delivered survey as part of the British Columbia Adolescent Substance Use Survey cohort study. Ordinal logistic and linear regression models were used to examine associations between frequency of SHS exposure in the past month and frequency of restless sleep and nighttime sleep duration, respectively. Results. SHS exposure was significantly positively associated with restless sleep and significantly negatively associated with sleep duration. In fully adjusted models, compared with students who reported never being exposed to SHS in the past month, students who reported a low, medium, or high frequency of SHS exposure were 1.53, 1.76, and 2.51 times as likely, respectively, to report more frequent restless sleep (OR = 1.53, 95% CI 1.08-2.16; OR = 1.76, 95% CI 1.22-2.53; OR = 2.51, 95% CI 1.59-3.98). With regard to sleep duration, as frequency of SHS exposure increased by one category, nighttime sleep duration during the week and weekend decreased by 4 minutes (B = -0.06, 95% CI = -0.01- - 0.11) and 6 minutes (B = -0.09, 95% CI = -0.03- - 0.14), respectively. Conclusions. This study suggests that frequency of SHS exposure has a significant dose-response relationship with restless sleep and sleep duration in adolescents.
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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 | 0.000 | 0.001 |
| 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".