Factorial and Construct Validity of the Athletic Identity Questionnaire for Adolescents
Bibliographic record
Abstract
PURPOSE: This research describes the development of a measure of the general attribute of "athletic" in adolescents, encompassing exercise, sport, and physical activity. Based on a theoretical model supported in adults, the 40-item Athletic Identity Questionnaire (AIQ) for adolescents assesses four dimensions: appearance, competence, importance of activity, and encouragement from three sources: parents, friends, and teachers/other adults. METHODS: Structural equation modeling was used to evaluate the hypothesized four-factor model in a development sample of 408 adolescents in eighth grade (mean age 13.4 yr). A separate sample (N = 1586) was used to cross-validate the final model. Construct validity was examined by testing the model's relationship to self-reported (Modifiable Activity Questionnaire-Adolescent, Previous Day Physical Activity Recall, Youth Risk Behavior Survey) and objectively measured physical activity (MTI accelerometer in sample 3, N = 100). RESULTS: Confirmatory factor analysis supported the four-factor structure, and there was also support for a higher-order model. LISREL correlations between the AIQ factors and self-reported physical activity ranged from 0.32 to 0.61, TV watching from -0.20 to -0.50, and sport-team participation from 0.20 to 0.54. Pearson correlations between the AIQ factors and MTI vigorous physical activity ranged from 0.09 to 0.26 and MTI moderate from -0.06 to 0.22. CONCLUSIONS: Findings support the factorial and construct validity of the AIQ for adolescents.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".