Hyperactive-impulsive behavior does not moderate the association between executive function and physical activity in preschoolers
Bibliographic record
Abstract
Experimental research suggests a positive association between executive function (EF) and physical activity (PA). Observational research examining PA in everyday life does not consistently support this positive association, with findings yielding negative or no associations. Hyperactive-impulsive behavior could act as a possible moderator, explaining inconsistent findings. In this observational study, we examined the relation between EF and everyday PA as well as hyperactive-impulsive behavior as a potential moderator in a sample of 68 German preschoolers (3-5 yrs). As performance-based measured of EF and PA, participants performed a computerized EF test battery in two sessions and wore an accelerometer for 7 days. Parental questionnaires of EF, PA, and hyperactive-impulsive behavior were further implemented. Accelerometer-assessed moderate-to-vigorous PA was negatively related to EF performance, and hyperactive-impulsive behavior did not moderate this association. Neither time spent in any other PA intensity nor parental PA reports were related to EF. The present study represents the first study to investigate if hyperactive-impulsive behavior moderates the association between everyday PA and preschoolers' EF. Thus, the findings yield new insight into the relation between PA in everyday life and preschoolers' EF, as the unexpected negative relation could not be explained through hyperactive-impulsive behavior.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".