Unmet Healthcare and Social Services Needs of Older Canadian Adults With Developmental Disabilities
Bibliographic record
Abstract
Abstract The authors sought to create a demographic, socioeconomic, and health‐related profile of older (40+) Canadian adults with developmental disabilities (DD) residing in their communities, and to enhance current knowledge of their unmet health and social support services needs. They provide a secondary analysis of cross‐sectional data from the 2001 and 2006 Participation and Activity Limitation Surveys (PALS). The study population comprised PALS respondents who: (a) were at least 40 years of age at the time of the survey and (b) were reported having a DD. Weighted data were used to describe and compare the profiles of the study population and the comparison group (PALS respondents age 40+ with other types of disability), and to estimate the prevalence of reported unmet healthcare and social support services needs. Logistic regression analyses determined the extent to which these needs affected the target population's overall health status. The data revealed that an estimated 136,570 Canadians age 15+ reported having a DD in 2006. Of these, 66,560 (48.7%) were at least 40 years of age. An estimated 47.7% of this population rated their overall health status as either fair or poor. The prevalence of reported unmet healthcare and social services needs decreased between 2001 and 2006 for both study groups, but it was still much higher for older individuals with DD than for the comparison group in 2001 and 2006. Controlling for the effects of all the other factors, the authors found that reported unmet needs did not significantly affect respondents' overall health status. The authors concluded that compared to Canadians with other types of disability, those with DD were more likely to report unmet healthcare and social support services needs. Further research is needed to explore policies and programs which support the healthy and active aging of this population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".