Development of a Multidisciplinary Clinic for the Treatment of Obesity in a Canadian University Family Medicine Group (U-FMG)
Bibliographic record
Abstract
Context In 2018, 63.1% of Canadians were at greater risk of chronic diseases due to their BMI, including type 2 diabetes, atherosclerosis, and hypertension. The prevalence of obesity (BMI > 30) among adults was 26.8%, and the prevalence of overweight adults (BMI > 25) was 36.3%. Pathways offered by Quebec’s public system are heterogeneous, often providing limited services, especially in a preventive setting. Objective To implement and evaluate a novel multidisciplinary trajectory aimed at improving the treatment of obesity thus preventing multiple health-related complications. Population Studied Patients with obesity enrolled in the Méta-Santé clinic. Setting The North of Lanaudière University Family Medicine Group (U-FMG) Intervention Upon referral from their family doctor, patients attend a group course on nutrition and metabolic health. They complete a commitment form and questionnaire before meeting with a nurse practitioner, clinical nurse, nutritionist, and doctor. Follow-up frequency, ranging from weekly to monthly for up to 12 months, is tailored to individual needs. Patients may also be referred to social workers, psychologists, physiotherapists, kinesiologists, and pharmacists based on individual needs. Study Design and Analysis The clinic was developed with the collaboration of patient partners and clinicians, using a patient-centered and evidence-based approach. Quantitative analysis was conducted using the notes from healthcare professionals for each visit at the Méta-Santé clinic. Outcome Measures Data includes the number of patients, duration of participation, number of visits, distribution of patients per professional, and BMI at entry. Results The clinic has 41 current patients, and 59 have completed their participation. Average participation duration is 235 days, with a mean BMI of 41 at entry. Of 158 participants, 98% met with the nutritionist, 93% with the clinical nurse, 63% with the nurse practitioner, 25% with the doctor or resident, and 6% with the social worker. Conclusion Implementing a multidisciplinary pathway within Family Medicine Groups in Quebec is feasible for improving obesity treatment. The next step is to expand this trajectory to other family medicine practices across Quebec, facilitating program scaling. Future evaluations will include bioelectrical impedance analysis (BIA) to monitor changes in body composition and a longitudinal survey to assess the maintenance of healthy lifestyle habits.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".