Evidence map›Paper›PMID 38680934›Full record

ArticleFrontiers in public health2024

Wildfires and social media discourse: exploring mental health and emotional wellbeing through Twitter.

Yury E García, Miryam Elizabeth Villa-Pérez, Kuang Li, Xiao Hui Tai, Luis A Trejo, Maria L Daza-Torres, J Cricelio Montesinos-López, Miriam Nuño

Abstract read
In one paragraph

Article in Frontiers in 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.

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
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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

8 authors.

Yury E GarcíaDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.
Miryam Elizabeth Villa-PérezSchool of Engineering and Sciences, Tecnologico de Monterrey, Atizapán de Zaragoza, Mexico.
Kuang LiDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.
Xiao Hui TaiDepartment of Statistics, University of California, Davis, Davis, CA, United States.
Luis A TrejoSchool of Engineering and Sciences, Tecnologico de Monterrey, Atizapán de Zaragoza, Mexico.
Maria L Daza-TorresDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.
J Cricelio Montesinos-LópezDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.
Miriam NuñoDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.

Funding

UC Davis Clinical and Translational Science CenterUL1TR001860 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KENYON, NICHOLAS J., LYLES, COURTNEY REES · 2016 to 2025
$47.3M
NCATS NIH HHS UL1 TR001860
6 · The paper itself

Abstract

Introduction: The rise in global temperatures due to climate change has escalated the frequency and intensity of wildfires worldwide. Beyond their direct impact on physical health, these wildfires can significantly impact mental health. Conventional mental health studies predominantly rely on surveys, often constrained by limited sample sizes, high costs, and time constraints. As a result, there is an increasing interest in accessing social media data to study the effects of wildfires on mental health. Methods: In this study, we focused on Twitter users affected by the California Tubbs Fire in 2017 to extract data signals related to emotional well-being and mental health. Our analysis aimed to investigate tweets posted during the Tubbs Fire disaster to gain deeper insights into their impact on individuals. Data were collected from October 8 to October 31, 2017, encompassing the peak activity period. Various analytical methods were employed to explore word usage, sentiment, temporal patterns of word occurrence, and emerging topics associated with the unfolding crisis. Results: The findings show increased user engagement on wildfire-related Tweets, particularly during nighttime and early morning, especially at the onset of wildfire incidents. Subsequent exploration of emotional categories using Linguistic Inquiry and Word Count (LIWC) revealed a substantial presence of negative emotions at 43.0%, juxtaposed with simultaneous positivity in 23.1% of tweets. This dual emotional expression suggests a nuanced and complex landscape, unveiling concerns and community support within conversations. Stress concerns were notably expressed in 36.3% of the tweets. The main discussion topics were air quality, emotional exhaustion, and criticism of the president's response to the wildfire emergency. Discussion: Social media data, particularly the data collected from Twitter during wildfires, provides an opportunity to evaluate the psychological impact on affected communities immediately. This data can be used by public health authorities to launch targeted media campaigns in areas and hours where users are more active. Such campaigns can raise awareness about mental health during disasters and connect individuals with relevant resources. The effectiveness of these campaigns can be enhanced by tailoring outreach efforts based on prevalent issues highlighted by users. This ensures that individuals receive prompt support and mitigates the psychological impacts of wildfire disasters.

Indexed as

Mental HealthSocial MediaWildfiresCaliforniaEmotionsHumansLIWCmental healthsentiment analysistopic modelingTubbs Firewildfirewildfire emotional impactX (a.k.a Twitter)

Identifiers

PMID38680934
PMCPMC11046489

What OpenQuestion holds

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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.