Diabetic retinopathy awareness and eye care behaviour of indigenous women in Saskatoon, Canada
Bibliographic record
Abstract
Diabetes is a public health challenge in Canada with a disproportionate number of Indigenous people, especially women, living with diabetes. Diabetic retinopathy is a diabetes ocular complication and a common cause of blindness in Canadian adults. Many individuals living with diabetes do not have regular diabetic eye screening. This study sought to determine the diabetic retinopathy awareness and eye care behaviour of Indigenous women with diabetes or at risk of diabetes. This was a quantitative study among 78 Indigenous women (First Nations and Métis) in Saskatoon, Canada. Data on diabetic retinopathy awareness and eye care behaviour were collected via a knowledge, attitude, and practice survey. Participants had high diabetic retinopathy practice mean scores (32.16) than knowledge (30.16) and attitude scores (22.56). Sub-group analysis showed a significant difference in knowledge scores between age, education, and diabetes status, and differences in practice scores between age and education. Although our regression analysis indicated an association between education and knowledge scores (p = 0.024), and diabetes status and attitude scores (p = 0.044), the associations are not conclusive. Indigenous peoples with or at risk of diabetes may benefit from targeted interventions on diabetes and eye care, which could improve eye care awareness and behaviour.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".