Powering Adherence to Physical Activity by Changing Self-Regulatory Skills and Beliefs: Are Kinesiologists Ready to Counsel?
Bibliographic record
Abstract
There are multiple avenues to gain health promoting and disease preventing benefits of physical activity (PA) but nonadherence makes health benefits short-lived. Gains obtained through structured exercise training and therapy quickly decay once participants leave programs. Scientific position statements underscore cognitive-behavioral strategies (CBS) as an essential intervention component to increase and maintain PA and recommend transfer of CBS knowledge to practice. Our review of reviews indicates high quality PA interventions involving CBS consistently demonstrate medium effect sizes. Kinesiologists are the human resource capacity to translate this knowledge. Building capacity to implement CBS knowledge is potentially large given North American kinesiology programs and American College of Sports Medicine and Canadian Society for Exercise Physiology certification routes. Yet CBS training of kinesiologists by universities and organizations is minimal. Immediate change in CBS training and practice is needed. Professional organizations/institutions can either be leaders in developing human resources or part of the problem should they fail to address the challenge of CBS training.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".