Short-term variations in summer temperatures and mental health-related emergency department visits in Ontario, Canada
Bibliographic record
Abstract
Background: The acute effects of summer temperatures on mental health are not yet fully understood, particularly with respect to potential effect modifiers. Methods: We conducted a time-stratified case-crossover study to examine the association between daily variations in summer ambient and apparent temperatures and the risk of emergency department (ED) visits for mental health outcomes Ontario, Canada, from 2004 and 2019. Conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) per 5 °C increase in ambient or apparent temperature, adjusting for potential time-varying confounders including PM 2.5 , O 3 , and NO 2 . We also examined potential effect modification by social and material deprivation, as well as characteristics of the built environment. Results: Three-day mean ambient temperature was associated with an increased risk of ED visits for all mental health outcomes combined (OR = 1.022; 95% CI: 1.017, 1.027). This association persisted after adjustment for outdoor air pollutants (OR = 1.019; 95% CI: 1.014, 1.025). Three-day mean ambient temperatures were most strongly associated with disorders due to psychoactive substance use (OR = 1.043; 95% CI: 1.032, 1.054). Social deprivation modified the strength of observed associations (interaction P -value = 0.001), with 3-day mean ambient temperature associated with an increased risk of ED visits for mental health outcomes among those most socially deprived (OR = 1.032; 95% CI: 1.015, 1.049), but not among those least socially deprived (OR = 0.995; 95% CI: 0.962, 1.029). Conclusions: Our findings suggest that the risk of ED visits for mental health outcomes is greater at higher summer temperatures, especially for disorders due to psychoactive substance use and among those most socially deprived.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".