Gender Considerations in the Measurement of Climate Change Anxiety: A Cross-Sectional Study in British Columbia, Canada
Bibliographic record
Abstract
Globally, the impacts of climate change disproportionately impact women and gender non-binary people (non-binary). Few studies have examined gender differences in climate change anxiety (CCA). Methods: This study examines gender differences in CCA among women, men, and non-binary people living in British Columbia, Canada. Participants were recruited between May and December 2021 using online advertisements. Results: Among 1,260 participants, 21.9% (n = 138/631) of men, 49.5% (n = 257/519) of women, and 54.9% (n = 28/51) of non-binary participants, had moderate/high CCA scores. Men were less likely to report difficulty concentrating (p < 0.001), crying (p < 0.001), or responding to climate change by writing down and analyzing their thoughts (p < 0.001). Demographically adjusted models showed higher CCA among women (aOR = 2.17, 95% CI [1.65-2.85]) and non-binary participants (aOR = 2.70, 95% CI [1.43-5.13]) relative to men. When also adjusting for generalized psychological distress, the elevated effect among women remained significant (aOR = 1.52, 95% CI [1.14-2.04]), while the effect among non-binary participants was no longer significant (aOR = 1.67, 95% CI: [0.86-3.26]). Conclusions: Despite differences in generalized psychological distress, women and non-binary people likely experience a disproportionate burden of CCA. Further research is needed to understand the underlying mechanisms and potential mental health supports for individuals struggling with CCA across the gender spectrum.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".