Evolution of Sleep Duration and Screen Time Between 2018 and 2022 Among Canadian Adolescents: Evidence of Drifts Accompanying the COVID-19 Pandemic
Bibliographic record
Abstract
PURPOSE: We quantified the joint evolution of sleep duration and screen time between 2018 and 2022 in a large sample of adolescents from Quebec, Canada, to ascertain changes that occurred during the COVID-19 pandemic. METHODS: A natural experiment design was used to compare variations from year to year and in association with the pandemic outbreak. Using structural equation modeling on data collected between 2018 and 2022 among adolescents attending 63 high schools, we analyzed the joint evolution of sleep duration and screen time while adjusting for previous year values, concurrent flourishing score, sex, age, and family level of material deprivation. RESULTS: A total of 28,307 adolescents, aged on average 14.9 years, were included in the analyses. Between 2019 and 2022, sleep duration increased by 9.6 (5.7, 13.5) minutes and screen time by 129.2 (120.5, 138.0) minutes on average. In 2022, the adolescents spent almost equal amounts of time sleeping and using screens. Lower flourishing scores were associated with shorter sleep duration and lengthier screen time. Girls' screen time became similar to boys' over time. DISCUSSION: Adolescents now spend almost equal amounts of time sleeping and using screens, a situation that calls for urgent public health actions. These findings highlight the importance of tracking changes in adolescents' behaviours over time, to design and implement interventions adapted to the changing health needs of different groups.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".