The Godin-Shephard Leisure-Time Physical Activity Questionnaire: Validity Evidence Supporting its Use for Classifying Healthy Adults into Active and Insufficiently Active Categories
Bibliographic record
Abstract
This study provided validity evidence for the Godin-Shephard Leisure-Time Physical Activity Questionnaire (GSLTPAQ) to classify respondents into active and insufficiently active categories. Members of a fitness center [45 women and 55 men; mean (SD) age=45.5 (10.6) yr.] completed the questionnaire. Using only moderate and strenuous scores, those with a leisure score index≥24 were classified as active; those with a score≤23 were classified as insufficiently active. VO2max, percentage of body fat, and electronic records of fitness center attendance were the validation variables. In a visit to the fitness center, participants completed the GSLTPAQ and a certified exercise specialist performed a physical fitness evaluation. A multivariate analysis of covariance (MANCOVA) indicated the group of respondents classified as active had higher VO2max and lower percentage of body fat than the group of respondents classified as insufficiently active. An analysis of covariance (ANCOVA) indicated the group of respondents classified as active had higher electronic records of fitness center attendance than the group of respondents classified as insufficiently active. Therefore, these pieces of validity evidence support the use of the questionnaire's classification system among healthy adults.
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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 | 0.022 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".