Physical activity and recreational screen time change among adolescents in Canada: Examining the impact of COVID-19 in worsening inequity
Bibliographic record
Abstract
The purpose of this study was to assess if sub-populations of adolescents in Canada (i.e., race/ethnicity, sex/gender, and socioeconomic status [SES]) experienced a larger change in physical activity and screen time between the 2019-2020 (pre-pandemic) and the 2020-2021 (mid-pandemic) school years. Longitudinally linked data from pre-pandemic and mid-pandemic school years of a prospective cohort study of secondary school students in Canada (n = 8209) were used for these analyses. Multivariable regression modelling tested the main effects of race/ethnicity, sex/gender, and SES on changes in moderate-to-vigorous physical activity (MVPA) and screen time duration as well as adherence to Canada's 24-h Movement Guidelines. Overall between groups difference were assessed using type II analysis of deviance tests. Interactions between variables of interest were subsequently tested with a series of regression models compared to the main effects model using likelihood-ratio test. Post-hoc comparisons found Male participants' MVPA time decreased less compared to their female counterparts (M [95% CI] = -16.3 [-13.5, -19.2] min/day), but also reported greater increases in screen time compared to females (23.7 [14.7, 32.8] min/day) during the same period. MVPA in White participants decreased less than Asian participants (-10.7 [-19.5, -1.9] min/day) with a similar non-significant pattern observed in Black and Latin participants. Adolescents in higher SES categories fared better on adherence to MVPA (highest vs. lowest OR = 1.41 [0.97, 2.06]) and screen time recommendations(highest vs. lowest AOR = 3.13 [0.91, 11.11]). Results support the hypothesis that existing inequitable sociodemographic differences in MVPA participation and screen time have worsened throughout the pandemic.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".