Evaluation of the Get Active Questionnaire in community-dwelling older adults
Bibliographic record
Abstract
Physical activity screening prior to starting a physical activity program is important to identify if there are any underlying health conditions. However, many older adults do not complete such assessments prior to beginning their physical activity program. This project compared the Canadian Society for Exercise Physiology's newly developed Get Active Questionnaire (GAQ) to a standardized exercise stress test in terms of screening out versus screening in false-positive GAQ tests. A convenience sample of community-dwelling adults (male n = 58, female n = 54) aged 75 ± 7 years from London, Ontario, Canada, was used. Participants completed a physical exam and physical activity screening session (i.e., stress test and GAQ) at a research laboratory that routinely conducts community-based referrals. One week after the initial visit, participants returned to the study site, completed the GAQ, and were asked questions about their perceptions of physical activity screening by a research assistant. The GAQ "screened in" participants, but it did not provide the same precision of "screening out" at-risk individuals as an exercise stress test; the GAQ reduced false-positives versus the stress test, yet there was a large proportion of high false-negative results reported. The GAQ shows promise in physical activity screening in older adults to engage in exercise safely. However, the lack of precision in physical-activity screening out of at-risk populations requires further evaluation. Questionnaires such as the GAQ should be evaluated in a larger study population at various time points to further assess the validity and reliability of physical activity screening tools.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".