Association Between 24‐h Movement Behavior, Physical Fitness, and Inhibitory Control in School Adolescents: A Complex Network Analysis
Bibliographic record
Abstract
PURPOSE: To investigate the interrelationships between 24-h movement behaviors, health-related physical fitness, and inhibitory control performance in adolescents. METHODS: This cross-sectional study included 216 Brazilian adolescents (aged 16.7 ± 1.2 years) from a federal public school. Movement behaviors-moderate-to-vigorous physical activity (MVPA), smartphone screen time, sleep duration, and excessive daytime sleepiness-were assessed using the Global School-based Student Health Survey, digital well-being tools, and the Pediatric Daytime Sleepiness Scale. Aerobic capacity was measured using the PACER test, muscular strength by the FitnessGram push-up test, and body composition through body mass index. Inhibitory control was assessed using the Flanker task (E-Prime v3.0). Separate network analyses were performed for congruent and incongruent reaction times (RT). RESULTS: Physically active adolescents had faster RTs than their insufficiently active peers, with physical activity negatively associated with RT in both the congruent (-0.116) and incongruent (-0.125) networks. Aerobic capacity (e.g., expected influence: 0.879-0.902) and muscular strength (expected influence: 1.360-1.384) appeared as central components in both network structures. However, no associations were found between sleep duration, screen time, or excessive daytime sleepiness and inhibitory control. CONCLUSIONS: Adherence to MVPA guidelines was directly associated with improved inhibitory control performance among adolescents. Health-related physical fitness, particularly aerobic capacity and muscular strength, was indirectly associated with inhibitory control. Other movement behaviors were not associated with cognitive performance in this sample.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".