24-Hour Movement Behaviors and Impulsivity
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to examine individual and concurrent associations between meeting the Canadian 24-Hour Movement Guidelines for Children and Youth (9-11 hours of sleep per night, ≤2 hours of recreational screen time (ST) per day, and at least 60 minutes of moderate to vigorous physical activity per day) and dimensions of impulsivity. METHODS: Data from this cross-sectional observational study were part of the first annual curated release of the Adolescent Brain Cognitive Development Study. Participants included 4524 children between the ages of 8 and 11 years. RESULTS: In analyses, it was shown that adherence to individual movement behavior recommendations as well as combinations of adherence to movement behavior recommendations were associated with each dimension of impulsivity. Meeting all 3 movement behavior recommendations was associated with lower positive urgency (95% confidence interval [CI]: -0.12 to -0.05), negative urgency (95% CI: -0.04 to -0.08), Behavioral Inhibition System (95% CI: -0.08 to -0.01), greater perseverance (95% CI: 0.09 to 0.15), and better scores on delay-discounting (95% CI: 0.57 to 0.94). Meeting the ST and sleep recommendations was associated with less impulsive behaviors on all dimensions of impulsivity: negative urgency (95% CI: -0.20 to -0.10), positive urgency (95% CI: -0.16 to -0.08), perseverance (95% CI: 0.06 to 0.15), Behavioral Inhibition System (95% CI: -0.15 to -0.03), Behavioral Activation System (BAS) reward responsiveness (95% CI: -0.04 to -0.05), BAS drive (95% CI: -0.14 to -0.06), BAS fun-seeking (95% CI: -0.15 to -0.17), and delay-discounting task (95% CI: 0.68 to 0.97). CONCLUSIONS: Findings support efforts to determine if limiting recreational ST while promoting adequate sleep enhances the treatment and prevention of impulsivity-related disorders.
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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 | 0.002 |
| 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".