Uptake of Colorectal Cancer Screening among Ontarians with Intellectual and Developmental Disabilities
Bibliographic record
Abstract
Under-screening for cancer may contribute to a greater disease burden in individuals with intellectual and developmental disabilities (IDD) as their life expectancy increases. In 2008, the province of Ontario launched Canada's first population-based colorectal cancer screening program. Our objectives were to compare the proportions of Ontarians with and without IDD who have undergone colorectal cancer screening and to examine factors associated with screening uptake among Ontarians with IDD. Records for Ontario residents 50-64 years of age were linked across various administrative health and social services datasets to identify individuals with IDD and to select a random sample of the age-equivalent Ontario population without IDD as a comparison group. Logistic regression models were fit to examine the odds of screening uptake among individuals with IDD while controlling for age, sex, urban or rural residence, neighbourhood income quintile, expected use of health care resources, and being enrolled with or seeing a physician in a patient enrolment model (any of several primary care practice models designed to improve patient access and quality of care in Ontario), and to examine the association between these variables and colorectal cancer screening in the IDD population. The odds of having had a fecal occult blood test in the previous two years and being up-to-date with colorectal tests were 32% and 46% lower, respectively, for Ontarians with IDD compared to those without IDD. Being older, female, having a greater expected use of health care resources, and being enrolled with or seeing a physician in a primary care patient enrolment model were all significantly associated with higher odds of having been screened for colorectal cancer in the IDD population. These findings underscore the need for targeted interventions aimed at making colorectal cancer screening more equitable.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".