Psychosocial determinants of physical activity at school among Lebanese children : an application of the planned behavior theory
Bibliographic record
Abstract
Introduction:Based on an extended version the theory of planned behavior, this survey, aimed to identify the psychosocial determinants of children's physical activity at school and intention to engage in it.Methods: 276 fifth-and sixth-grade students from two schools in Lebanon completed a self-reported questionnaire assessing psychosocial and physical activity variables.Data were collected also on sociodemographic, anthropometric variables.Results: Determinants of physical activity at school were intention, perceived behavior control, selfidentity, perceived barriers and gender.Children's beliefs associated with a positive intention were the following: to feel able to engage in physical activity at school when sport equipment is provided, despite an inclement weather, despite school restrictions on the use of physical activity facilities and equipment, and despite an inappropriate playground for some kinds of play.These should be targeted in physical activity interventions. Conclusions: These findings inform the design of culturally relevant school-based interventions in Arabic countries.Interventions should specifically support girls in recognition of the negative influence of gender on physical activity.They should also promote children's self-identification as a sporty child and enhance children's confidence in their capacity to engage in physical activity at school and to overcome barriers associated with it.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".