Bibliographic record
Abstract
Few community-based obesity reduction programs have been evaluated. After 153 community consultations, the city of Moose Jaw, Saskatchewan, Canada decided to initiate a free comprehensive program. The initiative included 71 letters of support from the Mayor, every family physician, cardiologist and internist in the city and every relevant community group including the Heart and Stroke Foundation, the Canadian Cancer Society and the Public Health Agency of Canada. The objective was to promote strong adherence while positively influencing a wide range of physical and mental health variables measured through objective assessment or validated surveys. The only inclusion criteria was that the individuals must be obese adults (BMI >30). Participants were requested to sign-up with a “buddy” who was also obese and identify three family members or friends to sign a social support contract. During the initial 12 weeks, each individual received 60 group exercise sessions, 12 group cognitive behaviour therapy sessions and 12 group dietary sessions with licensed professionals. During the second 12 week period, maintenance therapy included 12 group exercise sessions. To date, 243 people have been referred with 229 starting. Among those who started, 183 completed the program (79.9%) while 15 quit for medical reasons and 31 quit for personal reasons. Mean objective reductions included 31.0 pounds of body fat, 3.9 percent body fat, 2.9 inches from the waist, 2.3 inches from the hip, blood cholesterol by 0.5 mmol/L, systolic blood pressure by 5.9 mmHg and diastolic blood pressure by 3.2 mmHg (all p<.000). There were no changes in blood sugar levels. There was also statistically significant differences in aerobic fitness, self-report health, quality of life measured by SF-36 and depressed mood measured by CES-D (all p<.000). An independent risk factor for not completing the program was not having a family member or friend sign a social support contract (OR 2.91; 95% CI 1.01-8.34, p=.047). Education level was a confounder. Comprehensive obesity reduction programs can be effective when there is extensive consultation at the community level and social support at the individual level.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.014 |
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".