Rural Ontario Complete Lifestyle Medicine Intervention Program (CLIP-ON)
Bibliographic record
Abstract
Context: Chronic illness is at a record high in society. Lifestyle medicine programs have demonstrated a positive impact in managing these diseases but are poorly implemented and unavailable in rural communities. Lifestyle medicine involves ongoing engagement with a multidisciplinary team to support health-improving lifestyle changes. Objective: To assess the feasibility of implementing a lifestyle medicine program in a rural Ontario community for patients with chronic diseases. Study Design and Analysis: A prospective, mixed design feasibility study in which participants are followed over six months by an interdisciplinary team including a health coach, lifestyle medicine physician, dietician, and kinesiologist. It includes 22 weekly group classes and monthly appointments. The first 14 weeks discuss the six pillars of lifestyle medicine followed by an 8-week structured exercise program. Feasibility is assessed by participant recruitment, retention, satisfaction, fidelity, and sustainability metrics. Qualitative feedback is collected through questionnaires and focus groups. Setting: Program was conducted in Parry Sound, ON with participants recruited from the local community. Population Studied: Adults (≥18yrs) with chronic diseases such as prediabetes, type 2 diabetes, hypertension, coronary heart disease, peripheral vascular disease, dyslipidemia, and/or concerns related to body weight (BMI≥25). Instrument: Participant and provider progress, satisfaction and feedback were elicited through questionnaires and focus groups. Outcome Measures: Participant characteristics (ie. gender, age, race, education, etc.), physical, social, emotional, spiritual and mental health information collected with well-being and lifestyle medicine tools, and anthropometric and cardiometabolic variables. Results: Cohort one of eight participants completed CLIP-ON in April 2024. Early findings confirm a 100% completion rate and 80% program satisfaction. All participants increased their physical activity with 80% progressing towards their health goals. Challenges included scheduling difficulties related to a diverse cohort and providers, difficulties with hybrid options, and participants requesting more group time for social connectedness. Conclusion: CLIP-ON has demonstrated patient and provider interest, and logistical feasibility in this rural setting. Addressing the current challenges will make CLIP-ON a model for other communities interested in implementing lifestyle medicine programs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.004 |
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".