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Record W4302362254 · doi:10.1016/j.jenvp.2022.101887

Climate anxiety, wellbeing and pro-environmental action: correlates of negative emotional responses to climate change in 32 countries

2022· article· en· W4302362254 on OpenAlexaff
Charles A. Ogunbode, Rouven Doran, Daniel Hanss, Maria Ojala, Katariina Salmela‐Aro, Karlijn L. van den Broek, Navjot Bhullar, Sibele D. Aquino, Tiago Azevedo Marot, Julie Aitken Schermer, Anna Włodarczyk, Su Lu, Feng Jiang, Daniela Acquadro Maran, Radha Yadav, Rahkman Ardi, Razieh Chegeni, Elahe Ghanbarian, Somayeh Zand, Reza Najafi, Joonha Park, Takashi Tsubakita, Chee‐Seng Tan, JohnBosco Chika Chukwuorji, Kehinde A. Ojewumi, Hajra Tahir, Mai Albzour, Marc Eric S. Reyes, Samuel Lins, Violeta Enea, Tatiana Volkodav, Tomáš Sollár, Ginés Navarro‐Carrillo, Jorge Torres‐Marín, Winfred Mbungu, Arin H. Ayanian, Jihane Ghorayeb, Charles Onyutha, Michael J. Lomas, Mai Helmy, Laura Martínez‐Buelvas, Aydın Bayad, Mehmet Karasu

Bibliographic record

VenueJournal of Environmental Psychology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsWestern University
Fundersnot available
KeywordsAnxietyClimate changePsychologyAction (physics)Mental healthGlobal warmingSocial psychologyEcologyPsychiatry

Abstract

fetched live from OpenAlex

This study explored the correlates of climate anxiety in a diverse range of national contexts. We analysed cross-sectional data gathered in 32 countries (N = 12,246). Our results show that climate anxiety is positively related to rate of exposure to information about climate change impacts, the amount of attention people pay to climate change information, and perceived descriptive norms about emotional responding to climate change. Climate anxiety was also positively linked to pro-environmental behaviours and negatively linked to mental wellbeing. Notably, climate anxiety had a significant inverse association with mental wellbeing in 31 out of 32 countries. In contrast, it had a significant association with pro-environmental behaviour in 24 countries, and with environmental activism in 12 countries. Our findings highlight contextual boundaries to engagement in environmental action as an antidote to climate anxiety, and the broad international significance of considering negative climate-related emotions as a plausible threat to wellbeing.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.195
GPT teacher head0.429
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations507
Published2022
Admission routes1
Has abstractyes

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