Trends in objectively measured and perceived mental health and use of mental health services: a population-based study in Ontario, 2002–2014
Bibliographic record
Abstract
BACKGROUND: Mental illness is widely perceived to be more of a public health concern now than in the past; however, it is unclear whether this perception is due to an increase in the prevalence of mental illness, an increase in help-seeking behaviours or both. We examined temporal trends in use of mental health services as well as objectively measured and perceived mental health. METHODS: We conducted a repeat cross-sectional study of Ontario residents who participated in Statistics Canada’s Canadian Community Health Survey (2002–2014). We assessed temporal trends in objectively measured past-year major depressive episode (based on criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, and International Classification of Diseases, 10th Revision) and past-month psychological distress (Kessler Psychological Distress Scale–6 score ≥ 8) and perceived, self-rated mental health. We also examined use of mental health services, including service use among those with a need for mental health care. RESULTS: A total of 260 090 survey participants were included. The age- and sex-standardized prevalence of a major depressive episode (4.8%, 95% confidence interval [CI] 4.2%–5.3% in 2002 v. 4.9%, 95% CI 4.2%–5.7% in 2012; p = 0.9) and psychological distress (7.0%, 95% CI 6.3%–7.6% in 2002 v. 6.5%, 95% CI 5.7%–7.5% in 2012; p = 0.4) did not change significantly over time. However, self-rated fair or poor mental health status increased from 4.9% in 2003–2005 to 6.5% in 2011–2014 (ptrend < 0.001), as did the use of mental health services (7.2% to 12.8%, ptrend < 0.001). The percentage of individuals who had subjective or objectively measured mental health problems and did not access mental health services decreased significantly over time. INTERPRETATION: Given the stable prevalence of objectively measured psychiatric symptoms, the increase in use of mental health services appears to be, at least partly, explained by an increase in perceived poor mental health and help-seeking behaviours.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".