Development of norm for Adolescent Physical Literacy Questionnaire (APLQ) in Tehran
Bibliographic record
Abstract
Introduction: Adolescents' physical literacy and physical activity influences their lifestyle behaviors and health-related readiness into adulthood. Lack of information about the state of physical literacy has led researchers to examine the state of physical literacy in adolescents in Tehran.Martials and Methods: The method of the present study was descriptive and performed in the 12-18 years adolescent in Tehran. The sample were 836 adolescents who selected by multi-stage cluster sampling from different areas of the Tehran. Inclusion criteria included having physical health, not having certain diseases and movement problems or regular drug use. Subjects' physical literacy was assessed using the adolescents' physical literacy questionnaire (APLQ). This questionnaire with three dimensions examines adolescents' physical literacy and has an internal consistency coefficient (0.951) and retest reliability (0.981).Results: The total mean scores of physical literacies in adolescents were 90.04 ± 17.12 and the desired norm was determined with a standard deviation of high and low (107.16-72.94). However, the mean scores for girls were about 85 and for boys 92, which shows a difference between the sexes and high ages.Conclusion: The results showed that adolescents' physical literacy scores in all dimensions increase with age; Also, the scores were higher in boys than girls in all dimensions. Similar results have been reported for differences in gender and age in the Physical Literacy of Canadian children [12]. The norm presented in this study can be a basis for measuring and comparing the levels of physical literacy of adolescents in Tehran.
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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 | 0.005 | 0.007 |
| 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 | 0.001 | 0.001 |
| 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".