Prevalence of intellectual and developmental disabilities among first generation adult newcomers, and the health and health service use of this group: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Attention to research and planning are increasingly being devoted to newcomer health, but the needs of newcomers with disabilities remain largely unknown. This information is difficult to determine since population-level data are rarely available on newcomers or on people with intellectual and developmental disabilities (IDD), although in Ontario, Canada these databases are accessible. This study compared the prevalence of IDD among first generation adult newcomers to adult non-newcomers in Ontario, and assessed how having IDD affected the health profile and health service use of newcomers. METHODS: This population-based retrospective cohort study of adults aged 19-65 in 2010 used linked health and social services administrative data. Prevalence of IDD among newcomers (n = 1,649,633) and non-newcomers (n = 6,880,196) was compared. Among newcomers, those with IDD (n = 2,830) and without IDD (n = 1,646,803) were compared in terms of health conditions, and community and hospital service use. RESULTS: Prevalence of IDD was lower in newcomers than non-newcomers (171.6 versus 898.3 per 100,000 adults, p<0.0001). Among newcomers, those with IDD were more likely than those without IDD to have comorbid physical health disorders, non-psychotic, psychotic and substance use disorders. Newcomers with IDD were also more likely to have psychiatry visits, and frequent emergency department visits and hospitalizations. CONCLUSION: First generation adult newcomers have lower rates of IDD than non-newcomers. How much of this difference is attributable to admission policies that exclude people expected to be high health service users versus how much is attributable to our methodological approach is unknown. Finding more medical and psychiatric comorbidity, and more health service use among newcomers with IDD compared to newcomers without IDD is consistent with patterns observed in adults with IDD more generally. To inform polices that support newcomers with IDD future research should investigate reasons for the prevalence finding, barriers and facilitators to timely health care access, and pathways to care.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".