Evidence map›Paper›PMID 40351475›Full record

Articlenpj climate action2025

Machine learning identifies key individual and nation-level factors predicting climate-relevant beliefs and behaviors.

Boryana Todorova, David Steyrl, Matthew J Hornsey, Samuel Pearson, Cameron Brick, Florian Lange, Jay J Van Bavel, Madalina Vlasceanu, Claus Lamm, Kimberly C Doell

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in npj climate action, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Upscaling behavioral interventions requires addressing selection bias.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Boryana TodorovaDepartment of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
David SteyrlDepartment of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
Matthew J HornseyBusiness School, University of Queensland, Brisbane, Australia.
Samuel PearsonBusiness School, University of Queensland, Brisbane, Australia.
Cameron BrickDepartment of Psychology, University of Amsterdam, Amsterdam, Netherlands.
Florian LangeBehavioral Economics and Engineering Group, KU Leuven, Leuven, Belgium.
Jay J Van BavelDepartment of Psychology, New York University; New York University, New York, USA.
Madalina VlasceanuDepartment of Environmental Social Sciences, Stanford Doerr School of Sustainability, Stanford, CA 94305 USA.
Claus LammDepartment of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
Kimberly C DoellDepartment of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While numerous studies have examined factors associated with climate-friendly beliefs and behaviors, a systematic, cross-national ranking of their key correlates is lacking. We use interpretable machine learning to quantify the extent to which different climate-relevant outcomes (climate change belief, policy support, willingness to share information on social media, and a pro-environmental behavioral task) are predictable and to rank 19 individual- and nation-level predictors in terms of their importance across 55 countries (

Indexed as

Climate-change mitigationClimate-change policyEnvironmental social sciencesPsychologyPsychology and behaviour

Identifiers

PMID40351475
PMCPMC12061775

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.