Evidence map›Paper›PMID 38317121›Full record

ArticleBMC public health2024

Clearing the air: evaluating institutions' social media health messaging on wildfire and smoke risks in the US Pacific Northwest.

Catherine E Slavik, Daniel A Chapman, Alex Segrè Cohen, Nahla Bendefaa, Ellen Peters

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Wildfire and Smoke Risk Communication: A Systematic Literature Review from a Health Equity Focus.International journal of environmental research and public health · 2025
    Pooled it
  2. Article
  3. Article
  4. Perceptions of and Responses to Wildfire Smoke Among New York State Residents: A Cross-Sectional Study.International journal of environmental research and public health · 2025
    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

5 authors.

Catherine E SlavikSchool of Journalism and Communication, University of Oregon, 1715 Franklin Boulevard, Eugene, OR, 97403, USA. cslavik@uoregon.edu.
Daniel A ChapmanSchool of Journalism and Communication, University of Oregon, 1715 Franklin Boulevard, Eugene, OR, 97403, USA.
Alex Segrè CohenSchool of Journalism and Communication, University of Oregon, 1715 Franklin Boulevard, Eugene, OR, 97403, USA.
Nahla BendefaaSchool of Journalism and Communication, University of Oregon, 1715 Franklin Boulevard, Eugene, OR, 97403, USA.
Ellen PetersSchool of Journalism and Communication, University of Oregon, 1715 Franklin Boulevard, Eugene, OR, 97403, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWildfire smoke contributes substantially to the global disease burden and is a major cause of air pollution in the US states of Oregon and Washington. Climate change is expected to bring more wildfires to this region. Social media is a popular platform for health promotion and a need exists for effective communication about smoke risks and mitigation measures to educate citizens and safeguard public health.

methodsUsing a sample of 1,287 Tweets from 2022, we aimed to analyze temporal Tweeting patterns in relation to potential smoke exposure and evaluate and compare institutions' use of social media communication best practices which include (i) encouraging adoption of smoke-protective actions; (ii) leveraging numeric, verbal, and Air Quality Index risk information; and (iii) promoting community-building. Tweets were characterized using keyword searches and the Linguistic Inquiry and Word Count (LIWC) software. Descriptive and inferential statistics were carried out.

results44% of Tweets in our sample were authored between January-August 2022, prior to peak wildfire smoke levels, whereas 54% of Tweets were authored during the two-month peak in smoke (September-October). Institutional accounts used Twitter (or X) to encourage the adoption of smoke-related protective actions (82% of Tweets), more than they used it to disseminate wildfire smoke risk information (25%) or promote community-building (47%). Only 10% of Tweets discussed populations vulnerable to wildfire smoke health effects, and 14% mentioned smoke mitigation measures. Tweets from Washington-based accounts used significantly more verbal and numeric risk information to discuss wildfire smoke than Oregon-based accounts (p = 0.042 and p = 0.003, respectively); however, Tweets from Oregon-based accounts on average contained a higher percentage of words associated with community-building language (p < 0.001).

conclusionsThis research provides practical recommendations for public health practitioners and researchers communicating wildfire smoke risks on social media. As exposures to wildfire smoke rise due to climate change, reducing the environmental disease burden requires health officials to leverage popular communication platforms, distribute necessary health-related messaging rapidly, and get the message right. Timely, evidence-based, and theory-driven messaging is critical for educating and empowering individuals to make informed decisions about protecting themselves from harmful exposures. Thus, proactive and sustained communications about wildfire smoke should be prioritized even during wildfire "off-seasons."

Indexed as

Air PollutionSocial MediaWildfiresHumansPublic HealthWashingtonEnvironmental healthProtection motivation theoryPublic healthRisk communicationSocial mediaWildfire smoke

Identifiers

PMID38317121
PMCPMC10840270

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.