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

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Abstract

Background

During 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.

Objective

The 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.

Methods

A 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.

Results

Of 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 _{health literacy}=.149, β _{eHealth literacy}=.368; P<.001) and conventional health behaviors ( β _{health literacy}=.219, β _{eHealth literacy}=.277; P<.001).

Conclusions

The 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.

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Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China

An Lian Pan, Li Liu, Chaolong Wang … (2020)

Was there an association of public health interventions with improved control of the COVID-19 outbreak in Wuhan, China? In this cohort study that included 32 583 patients with laboratory-confirmed COVID-19 in Wuhan from December 8, 2019, through March 8, 2020, the institution of interventions including cordons sanitaire , traffic restriction, social distancing, home quarantine, centralized quarantine, and universal symptom survey was temporally associated with reduced effective reproduction number of SARS-CoV-2 (secondary transmission) and the number of confirmed cases per day across age groups, sex, and geographic regions. A series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan and may inform public health policy in other countries and regions. Coronavirus disease 2019 (COVID-19) has become a pandemic, and it is unknown whether a combination of public health interventions can improve control of the outbreak. To evaluate the association of public health interventions with the epidemiological features of the COVID-19 outbreak in Wuhan by 5 periods according to key events and interventions. In this cohort study, individual-level data on 32 583 laboratory-confirmed COVID-19 cases reported between December 8, 2019, and March 8, 2020, were extracted from the municipal Notifiable Disease Report System, including patients’ age, sex, residential location, occupation, and severity classification. Nonpharmaceutical public health interventions including cordons sanitaire , traffic restriction, social distancing, home confinement, centralized quarantine, and universal symptom survey. Rates of laboratory-confirmed COVID-19 infections (defined as the number of cases per day per million people), across age, sex, and geographic locations were calculated across 5 periods: December 8 to January 9 (no intervention), January 10 to 22 (massive human movement due to the Chinese New Year holiday), January 23 to February 1 ( cordons sanitaire , traffic restriction and home quarantine), February 2 to 16 (centralized quarantine and treatment), and February 17 to March 8 (universal symptom survey). The effective reproduction number of SARS-CoV-2 (an indicator of secondary transmission) was also calculated over the periods. Among 32 583 laboratory-confirmed COVID-19 cases, the median patient age was 56.7 years (range, 0-103; interquartile range, 43.4-66.8) and 16 817 (51.6%) were women. The daily confirmed case rate peaked in the third period and declined afterward across geographic regions and sex and age groups, except for children and adolescents, whose rate of confirmed cases continued to increase. The daily confirmed case rate over the whole period in local health care workers (130.5 per million people [95% CI, 123.9-137.2]) was higher than that in the general population (41.5 per million people [95% CI, 41.0-41.9]). The proportion of severe and critical cases decreased from 53.1% to 10.3% over the 5 periods. The severity risk increased with age: compared with those aged 20 to 39 years (proportion of severe and critical cases, 12.1%), elderly people (≥80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI, 3.31-3.95]) while younger people (<20 years) had a lower risk (proportion, 4.1%; risk ratio, 0.47 [95% CI, 0.31-0.70]). The effective reproduction number fluctuated above 3.0 before January 26, decreased to below 1.0 after February 6, and decreased further to less than 0.3 after March 1. A series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan, China. These findings may inform public health policy in other countries and regions. This population epidemiology study examines associations between phases of nonpharmaceutical public health interventions (social distancing, centralized quarantine, home confinement, and others) and rates of laboratory-confirmed COVID-19 infection in Wuhan, China, between December 2019 and early March 2020.

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How to fight an infodemic

John Zarocostas (2020)

WHO's newly launched platform aims to combat misinformation around COVID-19. John Zarocostas reports from Geneva. WHO is leading the effort to slow the spread of the 2019 coronavirus disease (COVID-19) outbreak. But a global epidemic of misinformation—spreading rapidly through social media platforms and other outlets—poses a serious problem for public health. “We’re not just fighting an epidemic; we’re fighting an infodemic”, said WHO Director-General Tedros Adhanom Ghebreyesus at the Munich Security Conference on Feb 15. Immediately after COVID-19 was declared a Public Health Emergency of International Concern, WHO's risk communication team launched a new information platform called WHO Information Network for Epidemics (EPI-WIN), with the aim of using a series of amplifiers to share tailored information with specific target groups. Sylvie Briand, director of Infectious Hazards Management at WHO's Health Emergencies Programme and architect of WHO's strategy to counter the infodemic risk, told The Lancet, “We know that every outbreak will be accompanied by a kind of tsunami of information, but also within this information you always have misinformation, rumours, etc. We know that even in the Middle Ages there was this phenomenon”. “But the difference now with social media is that this phenomenon is amplified, it goes faster and further, like the viruses that travel with people and go faster and further. So it is a new challenge, and the challenge is the [timing] because you need to be faster if you want to fill the void…What is at stake during an outbreak is making sure people will do the right thing to control the disease or to mitigate its impact. So it is not only information to make sure people are informed; it is also making sure people are informed to act appropriately.” About 20 staff and some consultants are involved in WHO's communications teams globally, at any given time. This includes social media personnel at each of WHO's six regional offices, risk communications consultants, and WHO communications officers. Aleksandra Kuzmanovic, social media manager with WHO's department of communications, told The Lancet that “fighting infodemics and misinformation is a joint effort between our technical risk communications [team] and colleagues who are working on the EPI-WIN platform, where they communicate with different…professionals providing them with advice and guidelines and also receiving information”. Kuzmanovic said, “In my role, I am in touch with Facebook, Twitter, Tencent, Pinterest, TikTok, and also my colleagues in the China office who are working closely with Chinese social media platforms…So when we see some questions or rumours spreading, we write it down, we go back to our risk communications colleagues and then they help us find evidence-based answers”. “Another thing we are doing with social media platforms, and that is something we are putting our strongest efforts in, is to ensure no matter where people live….when they’re on Facebook, Twitter, or Google, when they search for ‘coronavirus’ or ‘COVID-19’ or [a] related term, they have a box that…directs them to a reliable source: either to [the] WHO website to their ministry of health or public health institute or centre for disease control”, she said. Google, Kuzmanovic noted, has created an SOS Alert on COVID-19 for the six official UN languages, and is also expanding in some other languages. The idea is to make the first information that the public receive be from the WHO website and the social media accounts of WHO and Dr Tedros. WHO also uses social media for real-time updates. WHO is also working closely with UNICEF and other international agencies that have extensive experience in risk communications, such as the International Federation of Red Cross and Red Crescent Societies. Carlos Navarro, head of Public Health Emergencies at UNICEF, the children's agency, told The Lancet that while a lot of incorrect information is spreading through social media, a lot is also coming from traditional mass media. “Often, they pick the most extreme pictures they can find…There is overkill on the use of [personal protective equipment] and that tends to be the photos that are published everywhere, in all major newspapers and TV…that is, in fact, sending the wrong message”, Navarro said. David Heymann, professor of infectious disease epidemiology at the London School of Hygiene & Tropical Medicine, told The Lancet that the traditional media has a key role in providing evidence-based information to the general public, which will then hopefully be picked up on social media. He also observed that for both social and conventional media, it is important that the public health community help the media to “better understand what they should be looking for, because the media sometimes gets ahead of the evidence”.

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The effect of large-scale anti-contagion policies on the COVID-19 pandemic

Solomon Hsiang, Daniel L Allen, Sebastien Annan-Phan … (2020)

Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic1, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations2-4. Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported7.

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Author and article information

Contributors

Huilan Xu:

ORCID: https://orcid.org/0000-0003-4845-2252

Department of Social Medicine and Health ManagementXiangya School of Public HealthCentral South University238 Shangmayuanling LaneChangsha, 410078China86 13637480958xhl_csu@163.com

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J Med Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: May 2021

Publication date (Electronic): 6 May 2021

Publication date PMC-release: 6 May 2021

Volume: 23

Issue: 5

Electronic Location Identifier: e25600

Affiliations

[1 ] Department of Social Medicine and Health Management Xiangya School of Public Health Central South University Changsha China

[2 ] School of Acupuncture and Tuina Shandong University of Traditional Chinese Medicine Jinan China

[3 ] Department of Mathematics and Statistics Mzuzu University Luwinga Malawi

[4 ] Department of Epidemiology and Health Statistics Xiangya School of Public Health Central South University Changsha China

Author notes

Corresponding Author: Huilan Xu xhl_csu@ 123456163.com

Author information

Shaojie Li https://orcid.org/0000-0003-1366-5813

Guanghui Cui https://orcid.org/0000-0003-2050-6191

Atipatsa Chiwanda Kaminga https://orcid.org/0000-0002-6556-4590

Sixiang Cheng https://orcid.org/0000-0002-3379-4818

Huilan Xu https://orcid.org/0000-0003-4845-2252

Article

Publisher ID: v23i5e25600

DOI: 10.2196/25600

PMC ID: 8104003

PubMed ID: 33822734

SO-VID: ea9ff9bf-0576-4f52-a05f-998178e99637

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 8 November 2020

Date revision requested : 23 December 2020

Date revision received : 29 January 2021

Date accepted : 3 April 2021

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