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Record W4417520336 · doi:10.1016/j.jenvp.2025.102894

Eco-emotions in children and adolescents: A rapid review of the qualitative literature

2025· article· en· W4417520336 on OpenAlexafffund
Judy Wu, Martin Gina, Gómez Maya, Kaufmann Julia, Hasina Samji

Bibliographic record

VenueJournal of Environmental Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsBC Centre for Disease ControlSimon Fraser University
FundersMinistry of Health, British Columbia
KeywordsAngerHappinessQualitative researchMental healthPerceptionCoping (psychology)ApathyLearned helplessnessAnxiety

Abstract

fetched live from OpenAlex

The global environmental crisis, driven by climate change and environmental degradation (CCED), profoundly impacts the mental and emotional well-being of children and adolescents. This is of concern as children and adolescents are likely to have disproportionate and long-term CCED-related mental health impacts due to their developmental stage, limited influence over environmental decision-making, and long-term exposure to CCED impacts. Recent research has increasingly sought to understand the psychological impacts of emotions related to the awareness of CCED, referred to as eco-emotions. However, much of this research has focused predominantly on fear and anxiety, commonly termed climate- and eco-anxiety. To address the gap in understanding the broader spectrum of eco-emotions experienced by children and adolescent, a rapid review of qualitative literature was conducted. This rapid review searched six electronic databases and synthesized findings from 48 qualitative and mixed methods studies. Across many studies, emotions such as worry, fear, anxiety, and anger were reported by many participants. Emotions such as sadness, grief, powerlessness, and helplessness were also reported. While the eco-emotions experienced were predominantly found to be negative, eco-emotions such as hope, optimism, and happiness were also observed, particularly among those participating in CCED-focused programming (e.g., educational initiatives, community-based environmental projects, or programs explicitly addressing eco-emotions). Apathy toward CCED was noted in some cases and was often linked to perceptions about its relevance or perceived immunity to its impacts. Some studies reported on deleterious mental health and well-being impacts related to negative eco-emotions. Methods of coping with eco-emotions were also extracted and synthesized. Children and adolescents reported the use of problem-focused and emotion-focused coping strategies, such as engagement in pro-environmental behaviours and connecting with friends and family for support. In a small number of studies, meaning-focused strategies such as positive reframing of the global environmental crisis were also noted. Findings from this review highlight the need for eco-emotions research beyond climate- and eco-anxiety and underscore the importance of tailored CCED-programming to support children and adolescents experiencing negative eco-emotions. • Children and adolescents experience a wide range of eco-emotions in response to the global environmental crisis; worry, anxiety, anger, and frustration were reported in many studies. • Expanding research beyond eco-anxiety to include emotions like anger, sadness, powerlessness, and hope may provide deeper insights into behavioral and mental health impacts of climate change and environmental degradation. • Environmentally themed programming (e.g., educational programs, climate action programs) show promise to transform negative eco-emotions into hope and empowerment and may promote resilience and proactive engagement among youth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.134
GPT teacher head0.482
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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