Achieving long-term effectiveness of nutrition counseling for indigenous older adults with type 2 Diabetes
Bibliographic record
Abstract
Background: The prevalence of diabetes has sharply increased after the age of 40 years since 2008/09. The prevalence of type 2 diabetes (T2DM) in the Indigenous population is 17.2% higher compared to the non-Indigenous population in Canada. Canadian Indigenous older adults are disproportionately affected by nutrition-related chronic diseases. The socio-cultural, biological, environmental, and lifestyle changes seen in this population group in the last half-century have contributed significantly to increased rates of T2DM and its complications. Ongoing lifestyle optimization including nutrition counselling and healthy eating patterns is essential for all patients with diabetes. Objective: The objectives of the study is to co-create a culturally safe nutrition plan. Method: We will invite the older adults from Caldwell First nation (target population) to focus group discussions to co-create the intervention following social constructivist approach. Implication: It is the intention of our study to respect and uphold traditional beliefs about Indigenous wholistic wellness – that our emotional, spiritual, physical and mental selves are not separate and that there can be no good health in one area if there remains sickness in another. A culturally sensitive nutrition counselling education material offers a promising strategy for improving the access to nutrition knowledge that may sustain a positive behavior change in older adults from Caldwell First Nation.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".