Indicators of self‐rated health in the Canadian population with diabetes
Bibliographic record
Abstract
AIMS: Self-rated health is a widely used measure of general health assessing risk factors and poor health outcomes in health surveys and clinical settings. The characteristics of self-rated health may be different in populations with specific chronic conditions, such as populations with diabetes. This study investigates the characteristics of self-rated health in a Canadian community sample of people with diabetes. METHODS: Self-rated health was obtained from 1837 adults with Type 2 diabetes participating in the Montreal Diabetes Health and Well-Being Study. Global disability and depression were assessed using the World Health Organization Disability Assessment Schedule II and the Patient Health Questionnaire, respectively. Logistic regressions studied the association between self-rated health and depression, disability, diabetes-related characteristics, socio-demographic factors, social support and lifestyle-related behaviours in both men and women. RESULTS: Participants' answers were dichotomized into excellent/very good/ good (78%) and fair/poor (22%) self-rated health. Both depression (men: odds ratio 1.9, 95% CI 1.4-2.6; women: odds ratio 1.5, 95% CI 1.2-1.9) and disability (men: odds ratio 1.7, 95% CI 1.4-1.9; women: odds ratio 1.7, 95% CI 1.5-1.9) were associated with fair/poor self-rated health. The associations remained unchanged even after controlling for diabetes characteristics. After controlling for confounding variables, chronic conditions were associated with fair/poor self-rated health in both men and women. Obesity was associated with fair/poor self-rated health in women only, while lifestyle behaviours such as being physically active and alcohol consumption were associated with good/very good/excellent self-rated health in men. CONCLUSIONS: In men and women, depression and disability are important factors that are associated with self-rated health in a large sample of individuals with Type 2 diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".