Evidence map›Paper›PMID 41167246›Full record

ArticleInteractive journal of medical research2025

Factors Predicting Information Overload During the COVID-19 Pandemic in the Digital Age: Longitudinal Study.

Hiroko Okada, Tsuyoshi Okuhara, Takahiro Kiuchi

Abstract read
In one paragraph

Article in Interactive journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Hiroko OkadaDepartment of Health Communication, Schoolf of Public Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0001-7877-9753
Tsuyoshi OkuharaDepartment of Health Communication, Schoolf of Public Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-6251-3587
Takahiro KiuchiDepartment of Health Communication, Schoolf of Public Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0001-5934-0681

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe human capacity to process information is limited. During the COVID-19 pandemic, people were exposed to a large amount of uncertain and complex health information. This situation made some people experience perceived information overload, which made them unable to adopt appropriate preventive behaviors.

objectiveThis study aimed to examine the individual characteristics, abilities, and attention to informational media that predict the perception of information overload during a pandemic.

methodsWe conducted a longitudinal study with 2 time points, August 2020 and August 2021, among residents of Japan under a COVID-19 emergency declaration. The sample had the same proportions for sex, age, and prefecture as the general Japanese population. We used a web-based survey to measure sociodemographic characteristics, health literacy (HL), attention to 6 different types of information channels, and participants' perception of information overload. Hierarchical multiple regression analysis was conducted with information overload as the objective variable.

resultsA total of 784 participants responded to the survey at both time points, with a follow-up rate of 78.4% (784/1000). Hierarchical multiple regression analysis showed that younger age (β=-0.084, 95% CI -0.142 to -0.013), male sex (β=-0.163, 95% CI -0.008 to -0.003), lower HL (β=-0.084, 95% CI -0.114 to -0.011), paying less attention to television news (β=-0.118, 95% CI -0.038 to -0.001), and paying greater attention to social media (β=0.089, 95% CI 0.000-0.027) significantly predicted information overload 1 year after exposure to information during the pandemic.

conclusionsPublic health communicators should aim to provide concise and understandable information in consideration of a target population that is vulnerable to information overload during a pandemic. A high level of attention to social media may increase the perception of information overload. By contrast, HL may reduce the cognitive load in information processing. Providing an environment during normal periods that allows people to develop the skills to critically interpret health information will help them to prepare for future infodemics.

Indexed as

coronavirusCOVID-19data overloaddigital agehealth communicationhuman capacityinfectiousinfobesityinformation ageinformational mediainformation anxietyinformation overloadinfoxicationJapanlongitudinal studypandemicpulmonaryrespiratorySARS-CoV-2social media

Identifiers

PMID41167246
PMCPMC12616190

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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.