The Relationship Between Parental Physical Activity and Screen Time Behaviors and the Behaviors of their Young Children
Bibliographic record
Abstract
The main purpose of this study was to examine the relationships between parental and children's physical activity and screen time behaviors in a large sample of children in the early years. The results are based on 738 children aged 0-5 years and their parents from the Kingston, Canada area. Parents completed a questionnaire from May to September 2011 that assessed sociodemographic characteristics, their physical activity and screen time, and their child's physical activity and screen time. Logistic regression models, adjusted for potential confounders, were conducted. Parents in the lowest quartile of physical activity were 2.77 (95% confidence interval (CI): 1.68-4.57) times more likely to have a child in the lowest quartile of physical activity compared with parents in the highest quartile of physical activity. Relationships were stronger in two parent homes compared with single-parent homes. Parents in the second (odds ratio = 2.27, 95% CI: 1.36-3.78), third (2.30, 1.32-3.99), and fourth (7.47, 4.53-12.33) screen time quartiles were significantly more likely to have a child in the highest quartile of screen time compared with parents in quartile one. To optimize healthy growth and development in the early years, future family-centered interventions targeting both physical activity and screen time appear important.
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 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".