Evidence map›Paper›PMID 37809547›Full record

ArticleHeliyon2023

Construction of influencing factors model for public information avoidance behavior in major infectious disease outbreaks based on meta-ethnography.

Yuqi Yang, Rui Hu, Yongqing Ge, Jing Yin

Abstract read
In one paragraph

Article in Heliyon, 2023. 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. Factors influencing information overload among breast cancer patients in the information explosion era: a cross-sectional study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    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.

Yuqi YangSchool of Public Administration, Sichuan University, Chengdu, Sichuan, 610065, China.
Rui HuThe Library of Hubei Minzu University, Enshi, Hubei, 445000, China.
Yongqing GeThe Library of Hubei Minzu University, Enshi, Hubei, 445000, China.
Jing YinThe Library of Hubei Minzu University, Enshi, Hubei, 445000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Major infectious disease outbreaks are highly susceptible to diffuse outbreaks due to their sudden and more widespread nature. Compared to previous outbreaks such as the Spanish flu and SARS in China, COVID-19 has greatly affected the health of citizens and the economic development of countries worldwide, and is representative of major infectious disease outbreaks in many ways. Information avoidance, a common information behaviour during major infectious disease outbreaks, can alleviate the stress caused by information overload as a strategy to reduce negative emotions and maintain optimism. However, it can also bias risk perceptions and avoid content of greater value. Therefore, a deeper understanding of public information behaviour, particularly how and why relevant information is circumvented, places a demand on researchers. Methods: A meta-ethnographic qualitative research methodology was used, and the seven steps of the methodology were strictly followed, including identifying integration themes, defining the connotations of integration themes, reading original studies, identifying relationships between studies, inter-translation between studies, synthetic translation, and presenting integration results. 26 original studies were integrated in a unified research framework, with a macro perspective that integrates consistent as well as complex and even contradictory findings and identifies dominant factors. Conclusions: Identify demographic factors, information literacy, risk perception, cognitive structure, information quality, information sources, external characteristics of information, and environmental characteristics sub-dimensions around the dimensions of 'individual', 'information' and 'environment'. The study also explored the factors under each sub-dimension. The study finally identified three dimensions, nine sub-dimensions and 26 factors, and obtained a more complete theoretical framework to construct a "model of factors influencing public information avoidance behaviour in major infectious disease epidemics", with a view to providing a theoretical basis and practical reference for relevant departments in guiding public information behaviour and health practices in major infectious disease epidemics.

Indexed as

Information avoidanceMajor infectious disease outbreaksMeta-ethnography

Identifiers

PMID37809547
PMCPMC10560013

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.