Evidence map›Paper›PMID 41043141›Full record

ArticleJournal of medical Internet research2025

Decoding the Public's Real-Time Emotional and Cognitive Responses to the Changing Climate on Social Media: Computational Analysis Using Weibo and Meteorological Data.

Yucan Xu, Jiehu Yuan, Sijia Li, Qiuyan Liao

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Yucan XuSchool of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong, China (Hong Kong).ORCID https://orcid.org/0000-0003-0247-0404
Jiehu YuanSchool of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong, China (Hong Kong).ORCID https://orcid.org/0000-0003-3429-8514
Sijia LiDepartment of Social Work and Social Administration, Faculty of Social Sciences, University of Hong Kong, Hong Kong, China (Hong Kong).ORCID https://orcid.org/0000-0003-4952-4123
Qiuyan LiaoSchool of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong, China (Hong Kong).ORCID https://orcid.org/0000-0002-1105-6857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClimate change poses a significant threat to mental health and well-being worldwide. Existing research on the associations between climate change-related events and mental well-being primarily focuses on clinical outcomes and often measures associations at single time points. The long-term effects and variability of the changing climate on more subtle nonclinical but widespread mental well-being remain relatively unexplored. Additionally, the underlying mechanisms that link changing climate events to real-time emotional well-being and pro-environmental actions have rarely been studied. Revealing real-time nonclinical mental well-being and its underlying mechanism is crucial for the early detection of at-risk individuals. This knowledge can also inform future interventions aimed at improving the public's risk perception and empowering communities to manage related challenges effectively.

objectiveThis study aimed to understand the association between the changing climate and expressed emotional well-being by integrating multiple data sources, including social media posts about climate change on Weibo (N=76,514), 20 years of regional meteorological data (N=216,476 records), and regional vulnerability data in China.

methodsThis study proposed and tested a new mechanism that connects meteorological factors with expressed emotional well-being through three cognitive responses identified from social media posts: thinking styles, social affiliations, and somatosensory experiences. Psycholinguistic analysis, structural equation modeling (SEM), and multiple regression models were used to examine the mediation of these three conceptual factors, as well as the moderating effects of regional vulnerability and seasonal changes on the influence of climate change on the public's expressed emotional well-being and downstream pro-environmental tendencies.

resultsThe SEM results revealed that extreme hot days are associated with decreased emotional well-being when talking about climate change (total effect=-0.712, 95% CI -0.894 to -0.531, P<.001), and these effects were mediated by three proposed mediators: social affiliations (indirect effect=-0.445, 95% CI -0.537 to -0.347, P<.001), analytical-intuitive thinking style (indirect effect=-0.100, 95% CI -0.126 to -0.073, P<.001), and somatosensory experiences (indirect effect=0.022, 95% CI 0.005-0.041, P=.02). Additionally, regression analysis indicated that the association between increased temperatures and expressed emotional well-being is moderated by seasonal changes (β=-.091, 95% CI -0.159 to -0.023, P=.009) and regional population density (β=-.068, 95% CI -0.118 to -0.018, P=.007). In the crude model examining associations between weather indices and expressed pro-environmental tendencies, the results showed that extreme hot days are associated with reduced pro-environmental tendencies (odds ratio [OR]=0.802, 95% CI 0.747-0.861, P<.001). However, after controlling for expressed emotional well-being and cognitive responses, such associations were less pronounced.

conclusionsThe findings highlight the need for interventions that promote mental well-being in response to climate change and the importance of cognitive responses in developing positive coping strategies and enhancing emotional resilience. This approach could empower individuals to create a positive self-reinforcing cycle that encourages pro-environmental behaviors.

Indexed as

Climate ChangeCognitionEmotionsMeteorological ConceptsSocial MediaChinaHumansMental Healthclimate changecognitive responsesemotional well-beinginfodemiologypro-environmental behaviorspsycholinguistic analysisregional vulnerabilityWeibo

Identifiers

PMID41043141
PMCPMC12534770

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.