Trends and socioeconomic inequalities in acute mental health service use in Canada, 2004–2019: a nationally representative retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Acute mental health service use (AMHSU), that is, hospitalisations and emergency department (ED) visits for mental health, have been rising in the Canadian province of Ontario and globally; however, national-level estimates are not available. We examine trends and socioeconomic inequalities in AMHSU in the Canadian adult population between 2004 and 2019. METHODS: Using the Canadian Community Health Survey linked to tax and health administrative datasets, we reported prevalence rates of AMHSU using negative binomial regression models. Income-based absolute inequalities in AMHSU were reported using the Slope Index of Inequality. RESULTS: Over the study period, hospitalisations for mood disorders decreased from 144.8 (95% CI: 116.0-173.7) to 67.5 (95% CI: 54.5-80.4) per 100 000, while those for substance-related disorders (SRD) increased. Rates of ED visits increased for all conditions, with the largest increase for anxiety disorders, from 252.3 (95% CI: 210.9-293.6) to 434.1 (95% CI: 382.2-486.1) per 100 000. Females had higher rates of hospitalisations and ED visits for all conditions except SRD. We found pronounced income-based inequalities in both hospitalisations and ED visits for mental health, comparing those at the top versus bottom of the income distribution. Absolute inequalities for hospitalisations widened for SRD, from -93.6 (95% CI: -131.1 to -56.1) to -135.2 (95% CI: -203.4 to -67.1) per 100 000, and decreased for mood disorders, from -309.5 (95% CI: -443.8 to -175.3) to -126.0 (95% CI: -182.0 to -69.9) per 100 000. Additionally, absolute inequalities increased for ED visits across all mental health conditions. CONCLUSION: Interventions aimed at improving access to preventive services could mitigate observed inequalities in AMHSU.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".