Health Care Utilization By Immigrants With Multimorbidity: A Population Based Cross-sectional Study Of The 2015-2016 Canadian Community Health Survey (CCHS)
Bibliographic record
Abstract
Immigrants face unique healthcare barriers, which can negatively impact their health and health service use. Those with multimorbidity face a particular challenge as multimorbidity is associated with increased need for healthcare. The purpose of this study was to compare healthcare utilization, as measured by number of visits to family physicians and specialists, between immigrants and Canadian-born populations with multimorbidity, stratified by sex and for specific chronic diseases. A cross-sectional analysis using 2015-2016 Canadian Community Health Survey (CCHS) was conducted. After adjusting for relevant covariates, no statistically significant differences in visits to family physicians or specialists were observed between immigrants and Canadian-born populations with multimorbidity. However, female immigrants with multimorbidity had significantly fewer visits to family physicians than Canadian-born females, while immigrant women with mental illnesses and respiratory diseases revealed significant underutilization of family physician services. Future research should elucidate healthcare barriers to utilization, with an emphasis on immigrants with multimorbidity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".