Changes in community and hospital‐based health care use during the COVID‐19 pandemic for adults with and without intellectual and developmental disabilities
Bibliographic record
Abstract
BACKGROUND: Due to the functional, cognitive and communication impairments associated with intellectual and/or developmental disabilities (IDD), adaptations to service delivery during the COVID-19 pandemic may impact people with IDD differently than others. For community and hospital-based services, this study describes the proportion of adults with and without IDD who used health care in the year pre-COVID-19 and the first year of the pandemic. METHODS: This retrospective cohort study used linked health administrative databases to identify adults aged 18-105 years with and without IDD using unique encoded identifiers. Counts and proportions of adults who used health care services were reported for the pre-COVID-19 year (16 March 2019 to 14 March 2020) and the first COVID-19 year (15 March 2020 to 15 March 2021). RESULTS: Across services, the proportion of adults who used services was lower during the first COVID-19 year compared with the year prior, except for virtual physician visits that increased markedly for people with and without IDD. While the proportion of adults who used services was higher for those with IDD compared with those without IDD for both years, differences were greatest for mental health emergency visits and hospitalisations; adults with IDD were 6.3 to 10.9 times more likely to use these services than others with no IDD during the pandemic. CONCLUSIONS: During the first COVID-19 year in Ontario, Canada, service use decreased for all service types, except for virtual physician visits. In both years, adults with IDD remained more likely to use services than other adults, with the largest differences in use of mental health hospitalisations and mental health emergency department visits.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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".