Is life satisfaction associated with future mental health service use? An observational population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: To investigate the prospective association between life satisfaction and future mental health service use in: (1) hospital/emergency department, and (2) outpatient settings. DESIGN AND SETTING: Population-based cohort study of adults from Ontario, Canada. Baseline data were captured through pooled cycles of the Canadian Community Health Survey (CCHS 2005-2014) and linked to health administrative data for up to 5 years of follow-up. PARTICIPANTS: 131 809 Ontarians aged 18 years and older. MAIN OUTCOME MEASURE: The number of mental health-related visits in (1) hospitals/emergency department and (2) outpatient settings within 5 years of follow-up. RESULTS: Poisson regression models were used to estimate rate ratios in each setting, adjusting for sociodemographic measures, history of mental health-related visits, and health behaviours. In the hospital/emergency setting, compared to those most satisfied with life, those with the poorest satisfaction exhibited a rate ratio of 3.71 (95% CI 2.14 to 6.45) for future visits. In the outpatient setting, this same comparison group exhibited a rate ratio of 1.83 (95% CI 1.42 to 2.37). When the joint effects of household income were considered, compared with the highest income and most satisfied individuals, the least satisfied and lowest income individuals exhibited the highest rate ratio in the hospital/emergency setting at 11.25 (95% CI 5.32 to 23.80) whereas in the outpatient setting, the least satisfied and highest income individuals exhibited the highest rate ratio at 3.33 (95% CI 1.65 to 6.70). CONCLUSION: The findings suggest that life satisfaction is a risk factor for future mental health visits. This study contributes to an evidence base connecting positive well-being with health system outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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, 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".