Parental Influences and the Relationship to their Children’s Physical Activity Levels
Bibliographic record
Abstract
Engaging in a physically active lifestyle relates positively to current health and reduces chances of chronic diseases in the future. Given escalating health care costs, it is paramount to reduce illnesses associated with a lack of physical activity and thus critical to identify factors that influence physical activity - especially in children, with the opportunity for a lifetime impact. One of these influencing factors may be parents/guardians. The intent of this study was to examine the relationship between children's physical activity levels and parental factors including parental physical activity, support/encouragement, restrictiveness, and self-reported participation. Data was collected from 15 child-parent pairs with children ranging in age from 7 to 10 years. Daily physical activity levels were determined from pedometer data using a Piezo SC-Step Pedometer. Number of steps and moderate and vigorous physical activity were extracted from the pedometers and levels of support/encouragement, restrictiveness, and participation were quantified from parents' self-reported responses to a questionnaire created for this study. Pearson Product correlation analyses were carried out between: the children's and parent steps (r = -0.069; p = 0.597); children's steps and parent's self-reported encouragement/support (r = 0.045, p = 0.563); children's steps and parents' self-reported restrictiveness (r = -.0254, p = 0.820); and children's steps and parents' self-reported participation (r = -0.002, p = 0.503). The lack of significant relationships among these variables implies that more complex interactions occur between children and their parents regarding physical activity with children's participation influenced by other factors.
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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 | 0.009 |
| 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) | 0.002 | 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".