Behavior Tracking and 3-Year Longitudinal Associations Between Physical Activity, Screen Time, and Fitness Among Young Children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: Understanding the correlates of children’s fitness as they develop is needed. The objectives of this study were to 1) examine the longitudinal associations between physical activity (PA), screen time (ST), and fitness; 2) determine if sex moderates associations; and 3) track PA and ST over 3 years. Methods: Findings are based on 649 children [baseline = 4.5 (0.5) y; follow-up = 7.8 (0.6) y] from Edmonton, Canada. Parental-reported hour per week of PA and ST were measured at baseline and 3 years later. Fitness (vertical jump, sit and reach, waist circumference, grip strength, predicted VO 2max , push-ups, and partial curl-ups) was measured using established protocols at follow-up. Sex-specific z scores or low/high fitness groups were calculated. Linear or logistic multiple regression models and Spearman correlations were conducted. Results: Baseline ST was negatively associated with follow-up grip strength [β = −0.010; 95% confidence interval (CI), −0.019 to −0.001]. Associations between baseline PA and follow-up overall fitness (β = 0.009; 95% CI, 0.002 to 0.016) were significant, whereas baseline PA and follow-up VO 2max (β = 0.014; 95% CI, 0.000 to 0.027) approached significance ( P < .06). No sex interactions were observed. Moderate and large tracking were observed for PA ( r s = .30) and ST ( r s = .53), respectively. Conclusions: PA and ST may be important modifiable correlates of overall fitness in young children.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it