Prevention and Reduction of Obesity through Active Living (PROACTIVE): rationale, design and methods
Bibliographic record
Abstract
The Prevention and Reduction of Obesity through Active Living (PROACTIVE) is a randomised controlled trial to evaluate the effectiveness of a behaviourally based physical activity and diet composition programme to prevent and reduce obesity and related comorbidities in a primary healthcare setting. 491 abdominally obese men and women 25-75 years of age who were patients of primary care physicians were randomly assigned to either a usual care group (N = 242) or a behavioural intervention group (N = 249). Those in usual care received general advice from the physician regarding the merits of physical activity and a healthy diet as a strategy for obesity reduction. Those in the behavioural intervention group received an individually designed counselling programme from a specially trained health educator, with respect to physical activity, diet and obesity reduction. The study was designed to provide 95% power in both men and women to detect a 2% (2 cm) difference in waist circumference and 80% power to identify a 15% reduction in the prevalence of the metabolic syndrome, the two primary outcomes. PROACTIVE is the first behavioural intervention study to assess the effects of physical activity and diet on abdominal obesity and associated metabolic risk factors in a primary healthcare setting, include a generalised sample of men and women and examine long-term (24 months) effects. PROACTIVE has the potential to provide the basis for changing clinical practice (primary care) with respect to the prevention and reduction of obesity and related health risks. The purpose of this report is to present and discuss the rationale, design and methods of PROACTIVE.
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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 | 0.048 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".