ReviewJournal of education and health promotion2023
Models and components in disaster risk communication: A systematic literature review.
Review in Journal of education and health promotion, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Enhancing risk and crisis communication with computational methods: A systematic literature review.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Disaster Health Literacy - development and validation of a short measurement instrument in German to supplement the HLSFrontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimRisk communication is considered a major factor in disaster risk management by the concerned policymakers and researchers. However, the incoherence of variables affecting risk communication in various studies makes it difficult to plan for disaster risk communication. This study aims to identify and classify the influential components in disaster risk communication. MATERIALS AND
methodsThis systematic review was conducted in 2020. Databases included PubMed, Scopus, and Web of Science. In searching for articles, there was no limit on the date of publication and the language of the article. The research addressed both natural and man-made disasters. The Preferred reporting items for systematic review and meta-analysis protocols (PRISMA) checklist was followed throughout the research, and the quality of the papers was assessed using the mixed methods evaluation tool (MMAT).
resultsIn searching the articles, 3956 documents were obtained, of which 1025 duplicated articles were excluded. The titles and abstracts of the remaining documents (2931) were examined, of which 2822 were deleted, and the full text of 109 documents was studied for further assessment. Finally, after applying the inclusion and exclusion criteria and reviewing the full texts, 32 documents were considered to extract the data and for quality assessment. On studying the full text of the obtained documents, 115 components were found, which were classified into five groups (message, message sender, message receiver, message environment, message process) and 13 subgroups. In addition, the obtained components were classified as those proposed by the authors of the article and those obtained from disaster risk communication models.
conclusionIdentifying the effective components in the disaster risk communication gives a more comprehensive view of risk communication to the disaster managers and executives and provides the decision-makers with an important platform to be able to use the components of risk communication and increase the impact of messages and ultimately increase people's preparedness for disasters in planning operations for the risk communication.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.