Evidence map›Paper›PMID 42745338›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2026

Communicating and Constructing Risk: Government and Public Interactions in Responding to Heat Risks.

Liangdong Lu, Weijian Jiang, Jia Xu

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Liangdong LuBusiness School, Hohai University, Nanjing, People's Republic of China.
Weijian JiangSchool of Management, University of Science and Technology of China, Hefei, People's Republic of China.
Jia XuBusiness School, Hohai University, Nanjing, People's Republic of China.

Funding

Humanities and Social Science Fund of Ministry of Education of China 24YJA630059National Natural Science Foundation of China 72374066,72474064
6 · The paper itself

Abstract

Extreme heat is an increasingly important public-health and governance challenge, yet less is known about how public and governmental communication construct heat risk differently and how these communication processes evolve over time. Drawing on Hilgartner's taxonomy, this study compares 49,633 public-initiated messages from the Message Board for Leaders and 3,475 posts from official governmental Weibo accounts in China. Combining topic modeling, LIWC-based text analysis, and econometric models, we examine how heat risk is constructed in public and governmental texts, how heat-related communication varies across cities and over time, and how textual features and risk-construction intensity are associated with platform-observable communication outcomes. The findings show that public messages are more problem-solving and demand-oriented, whereas government posts are more prevention- and guidance-oriented. Public and governmental communication exhibit asymmetry in both the prevalence of textual features and their associations with governmental responsiveness and public engagement. At the city-year level, risk construction and communication effectiveness exhibit short-run inconsistency but adjust toward a long-run equilibrium relationship, suggesting that heat-risk communication is an adaptive process shaped through repeated public-government platform interactions.

Indexed as

CommunicationExtreme HeatGovernmentHot TemperatureChinaHumansPublic HealthRiskRisk Assessmentgovernment–public interactionheat riskrisk communicationsocial construction of risk

Identifiers

PMID42745338
PMCPMC13578531

What OpenQuestion holds

Textmetadata
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Registered trials

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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.