Mental health service use and suicide risk after a dementia diagnosis: a population-based retrospective matched cohort study
Bibliographic record
Abstract
Objectives To compare deaths due to suicide and mental health and addiction (MHA)-related health services utilization between adults with and without a new dementia diagnosis.Method This matched cohort study assessed all Ontarians aged 40–105 y with a new diagnosis of dementia between January 2013 and December 2018. Those without dementia were compared to those with dementia utilizing a 2:1 age-, sex- and region-match ratio. Dementia diagnoses were identified via a validated algorithm. Death by suicide, and MHA-related outpatient physician visits, emergency department (ED) visits, and hospitalizations within six months of diagnosis date or matched index date were compared between individuals with vs. without dementia.Results Our cohort included 504,709 individuals (33.4% with dementia). In the six months after diagnosis/matched index date, 24.3% of individuals with dementia had 1+ MHA-related outpatient visit compared to 7.8% in those without dementia. The adjusted rate of outpatient mental health visits was 2.52 times higher (95% confidence interval (CI): 2.50 − 2.55) in those with vs. without dementia. The risk of suicide was low and did not differ between groups.Conclusion Our findings suggest that a recent dementia diagnosis is associated with increased use of MHA-related health service use, particularly outpatient services.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".