Bibliographic record
Abstract
The objective of this project was to evaluate the effectiveness and efficacy of a community-based exercise prescription and counseling intervention delivery by family physicians to their older patients. STEP is a stratified, cluster randomized clinical trial where the physicians are the units of randomization and patients are the units of measurement. Forty-eight family physicians stratified for rural/urban location from four provinces in Canada (Alberta (12), Ontario (12), Quebec (12) and Nova Scotia (12) were selected and randomized to either an intervention or a control group. Ten healthy older men and women, aged 55–85 years, were recruited from each participating physician's practice. The intervention was the combination of an exercise prescription derived from the step test (training heart rate and relative cardiorespiratory fitness level); and a behaviour change activity counseling model (trantheoretical model). The control condition was usual care exercise prescription. Data collection occurred at baseline and every 3 months for 12 months. The primary outcome measures was maximal oxygen consumption (VO2max). Secondary outcome measures included clinical (heart rate, blood pressure, BMI), energy expenditure (7-day physical activity recall) and psychosocial measures related to physical activity (self-efficacy, quality of life, stage of change, and exercise benefits and barriers). We anticipate that by providing family physicians with the skills in exercise prescription and counseling will improve the adoption of physical activity, physical function and health among their older patients. Supported by Medical Research Council of Canada and Pfizer Canada Inc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.226 | 0.073 |
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".