Opportunities to Improve Diabetes Prevention and Care in Canada
Bibliographic record
Abstract
The prevalence of diabetes in Canada is expected to more than double by 2030. Additionally, the costs associated with diabetes have nearly doubled between 2000 and 2010 and will continue to rise unless improvements are made. Fortunately, more effective policies and programs can reduce both the prevalence of diabetes and the complications associated with the disease. We used responses from the Canadian Community Health Survey to assess whether Canadians with diabetes report (1) receiving from healthcare professionals the recommended tests to screen for complications, (2) performing sufficient self-care for their diabetes and, (3) for those in lower-income households, receiving less recommended care. The results show that only one in three (32%) Canadian adults with diabetes reported having received all four recommended tests during the previous year. Lower-income Canadians were more likely to report having diabetes and less likely to report receiving the four diabetes care tests. Only half of adults with diabetes reported checking their blood sugar levels daily, and only two in five reported checking their feet for injuries and ulcers. Improvements to adherence to diabetes care guidelines are needed to reduce the likelihood that Canadians, especially lower-income Canadians, will develop complications from diabetes. Bending the cost curve downward is possible through more effective policies and programs that prevent diabetes in the first place and that ensure Canadians with diabetes get both recommended care from their healthcare providers and enough support for effective self-care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".