Inequity in Mental Health Care Under Canadian Universal Health Coverage
Bibliographic record
Abstract
OBJECTIVE: Previous research has produced conflicting evidence about socioeconomic disparities in mental health care under universal health coverage in Canada. This study sought to determine equity in the delivery of ambulatory services from psychiatrists and family physicians for mental health problems in this setting. METHODS: Outpatient billing claims and neighborhood socioeconomic status were examined with cross-sectional analysis. The study area consisted of the central southern portion of the city of Toronto, Ontario, including the city's downtown core. This urban setting is an economically and culturally diverse area. A total of 1,221 homogeneous enumeration areas (local neighborhoods) were surveyed, and data were examined for the 746,141 residents of these areas who had had a health visit in 2000. Rates of mental health visits to family physicians and psychiatrists were compared across socioeconomic quintiles. Socioeconomic status was determined according to educational attainment in the enumeration area. RESULTS: Claimants from neighborhoods with the highest socioeconomic status were 1.6 times as likely as those from neighborhoods with the lowest socioeconomic status to use psychiatric care. Among persons who received care from a psychiatrist, claimants from neighborhoods with the highest socioeconomic status had significantly more psychiatric claims than those from neighborhoods with the lowest socioeconomic status. No significant gradients were found for either sex for any use of mental health care provided by family physicians. Among females, service users from the highest socioeconomic areas had more mental health visits to family physicians than those from the lowest socioeconomic areas. CONCLUSIONS: Marked socioeconomic disparities were found in the use of care from a psychiatrist. Unlimited coverage of physician-provided mental health care is insufficient to fairly distribute services to those most in need.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".