MULTIPLE CHRONIC CONDITIONS IN RELATION TO DISABILITY AND SOCIAL PARTICIPATION: DATA FROM THE CLSA
Bibliographic record
Abstract
While much is known about the effect of individual chronic conditions (CCs) on people’s ability to undertake their everyday activities, less is known about effect of having multiple CCs. We will present data from over 20,000 Canadian men and women on population patterns of self-reported CCs and how different combinations of CCs impact disability and social participation. Preliminary data suggest that although the proportion of people with 2+ CCs increases with age (22% in 45–54 vs. 52% in 75–89 year olds) and tends to be higher in females than males (36% vs. 30%), the difference between genders narrows with age. As well, combinations of chronic conditions with the same disease count differentially impact activities of daily living and social participation in men compared to women, and in middle-aged compared to older adults. Understanding these differences could help to increase the efficiency and quality of clinical care and improve public health.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".