The Emergence of Ecological Consciousness: A Transformative Journey
Bibliographic record
Abstract
The global youth mental health crisis is increasingly intertwined with climate change, as young people experience heightened climate anxiety and ecological grief. This study examines the relationship between nature connectedness, climate worry, coping strategies, and mental health outcomes among Canadian university students. Drawing on Pihkala’s process model of eco-anxiety, we propose the Developing Ecological Consciousness Model, a three-act framework that traces young people’s journey from climate awareness to meaningful engagement. Using path analysis on two independent samples (N = 1825), we found that nature connectedness predicts increased climate worry, which in turn correlates with higher levels of depression and anxiety. However, meaning-focused coping emerged as a protective factor, mitigating these negative mental health impacts. Problem-focused coping alone was insufficient, highlighting the need for balanced strategies. The study underscores the dual role of nature connectedness—both as a source of climate distress and a foundation for resilience. These findings highlight the need for interventions that foster ecological consciousness while addressing the emotional toll of climate change, offering insights for policymakers, educators, and mental health practitioners working with youth in a warming world.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".