Association of youth climate change worry with present and past mental health symptoms: a longitudinal population-based study
Bibliographic record
Abstract
Abstract Young people are worried about climate change but the association with current and past mental health symptoms is rarely examined in longitudinal population-based samples. Drawing on a population-based birth cohort from the Canadian province of Quebec ( n = 1325), this study used a cross-over design to (1) test the association between climate change worry at age 23-years and concurrent mental health symptoms assessed on standardised instruments, and (2) test the association between adolescent (15 and 17 years) symptoms of anxiety, depression, inattention-hyperactivity, and aggression-opposition and climate worry at age 23-years. Participant sex, cognitive ability, socioeconomic status, and parental mental health were adjusted for. Descriptive statistics showed that most participants were worried about climate change: 190 (14.3%) were extremely worried, 383 (28.9%) were very worried, 553 (41.7%) were somewhat worried, and 199 (15.0%) were not at all worried. In analysis 1, worry about climate change was associated with significantly higher concurrent anxiety, depression, and self-harm symptoms, even after adjustment for adolescent symptoms. In analysis 2, anxious adolescents were significantly more likely to be extremely worried about climate change six years later (RRR = 1.51, 95%CI = 1.10–2.07), while aggressive-oppositional adolescents were significantly less likely to be somewhat worried (RRR = 0.79, 95%CI = 0.63–0.0.99), very worried (RRR = 0.61, 95%CI = 0.48–0.78), or extremely worried (RRR = 0.51, 95%CI = 0.37–0.72). Taken together, participants who were worried about climate change had more concurrent mental health symptoms but were also more likely to have prior symptoms. Adolescents with higher anxiety were more likely to worry about climate change in early adulthood, while those with higher aggression-opposition were less likely to worry. Future studies should track climate worry longitudinally alongside symptoms using prospective follow-up studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".