Evidence map›Paper›PMID 33822734›Full record

ArticleJournal of medical Internet research2021

Associations Between Health Literacy, eHealth Literacy, and COVID-19-Related Health Behaviors Among Chinese College Students: Cross-sectional Online Study.

Shaojie Li, Guanghui Cui, Atipatsa Chiwanda Kaminga, Sixiang Cheng, Huilan Xu

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 5 pooled it
35.6field-weighted citation impact, top 1% of its field
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

73 citing papers in PubMed, 5 syntheses or guidelines pooled it, 115 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 2 countries.

Shaojie LiDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.ORCID 0000-0003-1366-5813
Guanghui CuiSchool of Acupuncture and Tuina, Shandong University of Traditional Chinese Medicine, Jinan, China.ORCID 0000-0003-2050-6191
Atipatsa Chiwanda KamingaDepartment of Mathematics and Statistics, Mzuzu University, Luwinga, Malawi.ORCID 0000-0002-6556-4590
Sixiang ChengDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.ORCID 0000-0002-3379-4818
Huilan Xu *Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.ORCID 0000-0003-4845-2252
Central South University · CNShandong University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the COVID-19 pandemic, the internet has significantly spread information, providing people with knowledge and advice about health protection regarding COVID-19. While a previous study demonstrated that health and eHealth literacy are related to COVID-19 prevention behaviors, few studies have focused on the relationship between health literacy, eHealth literacy, and COVID-19-related health behaviors. The latter includes not only preventative behaviors but also conventional health behaviors.

objectiveThe objective of this study was to develop and verify a COVID-19-related health behavior questionnaire, explore its status and structure, and examine the associations between these behaviors and participants' health literacy and eHealth literacy.

methodsA snowball sampling method was adopted to recruit participants to complete anonymous cross-sectional questionnaire surveys online that assessed sociodemographic information, self-reported coronavirus knowledge, health literacy, eHealth literacy, and COVID-19-related health behaviors.

resultsOf 1873 college students who were recruited, 781 (41.7%) had adequate health literacy; the mean eHealth literacy score was 30.16 (SD 6.31). The COVID-19-related health behavior questionnaire presented a two-factor structure-COVID-19-specific precautionary behaviors and conventional health behaviors-with satisfactory fit indices and internal consistency (Cronbach α=.79). The mean score of COVID-19-related health behaviors was 53.77 (SD 8.03), and scores differed significantly (P<.05) with respect to residence, college year, academic major, family economic level, self-reported health status, having a family member or friend infected with coronavirus, and health literacy level. Linear regression analysis showed that health literacy and eHealth literacy were positively associated with COVID-19-specific precautionary behaviors (β

conclusionsThe COVID-19-related health behavior questionnaire was a valid and reliable measure for assessing health behaviors during the pandemic. College students with higher health literacy and eHealth literacy can more actively adopt COVID-19-related health behaviors. Additionally, compared to health literacy, eHealth literacy is more closely related to COVID-19-related health behaviors. Public intervention measures based on health and eHealth literacy are required to promote COVID-19-related health behaviors during the pandemic, which may be helpful to reduce the risk of COVID-19 infection among college students.

Indexed as

Health BehaviorHealth Knowledge, Attitudes, PracticeAdolescentAdultAsian PeopleChinaCOVID-19Cross-Sectional StudiesHealth LiteracyHumansInternetMalePandemicsSARS-CoV-2Social FactorsStudentsChinese college studentsCOVID-19COVID-19–related health behavior questionnaireeHealth literacyhealth literacy

Identifiers

PMID33822734
PMCPMC8104003
OpenAlexW3151098230

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.