Coping and positive mental health in Canada among youth and adults: findings from a population-based nationally representative survey
Bibliographic record
Abstract
INTRODUCTION: Coping is a protective factor for positive mental health (PMH) and an asset for population health. While there is evidence demonstrating a strong association between coping and PMH, less is known about how coping patterns differ across age groups. Given that age can impact coping ability, addressing this knowledge gap is warranted. METHODS: We analyzed data from the 2019 Canadian Community Health Survey on the self-rated ability of adults and youth (N = 60 643; 12+ years) to cope with unexpected or difficult problems and day-to-day demands along with three PMH outcomes: selfrated mental health (SRMH), happiness and life satisfaction. All estimates were disaggregated by sociodemographic variables (sex, gender, household income quintile, immigration status, ethnocultural background, place of residence), stratified by five age groups, and age-specific regression analyses were conducted. RESULTS: Prevalence of high coping varied by sex, gender, income, place of residence, immigration status and ethnocultural background. High coping was significantly associated with the three PMH outcomes across all age groups. Those with high coping were 4 to 6 times more likely to report high SRMH and high levels of happiness than those with lower coping. Individuals with high coping had a life satisfaction score between 0.84 and 1.32 units greater than individuals with lower coping. CONCLUSION: The consistent, positive relationship between high coping and PMH across all age groups provides valuable information for developing public health messaging and promotion efforts for adaptive coping to enhance population mental health.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".