Social Media Use, eHealth Literacy, Disease Knowledge, and Preventive Behaviors in the COVID-19 Pandemic: Cross-Sectional Study on Chinese Netizens

Xiaojing Li, Qinliang Liu, Xiaojing Li, Qinliang Liu

Abstract

Background: Since its outbreak in January 2020, COVID-19 has quickly spread worldwide and has become a global pandemic. Social media platforms have been recognized as important tools for health-promoting practices in public health, and the use of social media is widespread among the public. However, little is known about the effects of social media use on health promotion during a pandemic such as COVID-19.

Objective: In this study, we aimed to explore the predictive role of social media use on public preventive behaviors in China during the COVID-19 pandemic and how disease knowledge and eHealth literacy moderated the relationship between social media use and preventive behaviors.

Methods: A national web-based cross-sectional survey was conducted by a proportionate probability sampling among 802 Chinese internet users ("netizens") in February 2020. Descriptive statistics, Pearson correlations, and hierarchical multiple regressions were employed to examine and explore the relationships among all the variables.

Results: Almost half the 802 study participants were male (416, 51.9%), and the average age of the participants was 32.65 years. Most of the 802 participants had high education levels (624, 77.7%), had high income >¥5000 (US $736.29) (525, 65.3%), were married (496, 61.8%), and were in good health (486, 60.6%). The average time of social media use was approximately 2 to 3 hours per day (mean 2.34 hours, SD 1.11), and the most frequently used media types were public social media (mean score 4.49/5, SD 0.78) and aggregated social media (mean score 4.07/5, SD 1.07). Social media use frequency (β=.20, P<.001) rather than time significantly predicted preventive behaviors for COVID-19. Respondents were also equipped with high levels of disease knowledge (mean score 8.15/10, SD 1.43) and eHealth literacy (mean score 3.79/5, SD 0.59). Disease knowledge (β=.11, P=.001) and eHealth literacy (β=.27, P<.001) were also significant predictors of preventive behaviors. Furthermore, eHealth literacy (P=.038) and disease knowledge (P=.03) positively moderated the relationship between social media use frequency and preventive behaviors, while eHealth literacy (β=.07) affected this relationship positively and disease knowledge (β=-.07) affected it negatively. Different social media types differed in predicting an individual's preventive behaviors for COVID-19. Aggregated social media (β=.22, P<.001) was the best predictor, followed by public social media (β=.14, P<.001) and professional social media (β=.11, P=.002). However, official social media (β=.02, P=.597) was an insignificant predictor.

Conclusions: Social media is an effective tool to promote behaviors to prevent COVID-19 among the public. Health literacy is essential for promotion of individual health and influences the extent to which the public engages in preventive behaviors during a pandemic. Our results not only enrich the theoretical paradigm of public health management and health communication but also have practical implications in pandemic control for China and other countries.

Keywords: COVID-19; disease knowledge; eHealth literacy; media use; pandemic; preventive behaviors; public health; social media.

Conflict of interest statement

Conflicts of Interest: None declared.

©Xiaojing Li, Qinliang Liu. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 09.10.2020.

Figures

Figure 1
Figure 1
Framework map of the research questions (RQ) and hypotheses (H). SM: social media.
Figure 2
Figure 2
Simple slope test of the moderating effect of eHealth literacy.
Figure 3
Figure 3
Simple slope test of the moderating effect of disease knowledge.

References

    1. Coronavirus disease 2019 (COVID-19) Situation Report 133. World Health Organization. 2020. Jun 01, [2019-06-01]. .
    1. Guarner J. Three Emerging Coronaviruses in Two Decades. Am J Clin Pathol. 2020 Mar 09;153(4):420–421. doi: 10.1093/ajcp/aqaa029.
    1. Al-Surimi K, Khalifa M, Bahkali S, El-Metwally A, Househ M. The Potential of Social Media and Internet-Based Data in Preventing and Fighting Infectious Diseases: From Internet to Twitter. Adv Exp Med Biol. 2017;972:131–139. doi: 10.1007/5584_2016_132.
    1. Velavan TP, Meyer CG. The COVID-19 epidemic. Trop Med Int Health. 2020 Mar;25(3):278–280. doi: 10.1111/tmi.13383. doi: 10.1111/tmi.13383.
    1. Herrera-Diestra JL, Meyers LA. Local risk perception enhances epidemic control. PLoS One. 2019 Dec 3;14(12):e0225576. doi: 10.1371/journal.pone.0225576.
    1. Kan J, Zhang H. Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks. Commun Nonlinear Sci Numer Simul. 2017 Mar;44:193–203. doi: 10.1016/j.cnsns.2016.08.007.
    1. Erraguntla M, Zapletal J, Lawley M. Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management. Health Informatics J. 2019 Dec 27;25(4):1170–1187. doi: 10.1177/1460458217747112.
    1. van Velsen L, Beaujean DJ, van Gemert-Pijnen JE, van Steenbergen JE, Timen A. Public knowledge and preventive behavior during a large-scale Salmonella outbreak: results from an online survey in the Netherlands. BMC Public Health. 2014 Jan 31;14:100. doi: 10.1186/1471-2458-14-100.
    1. Roberts H, Seymour B, Fish SA, Robinson E, Zuckerman E. Digital Health Communication and Global Public Influence: A Study of the Ebola Epidemic. J Health Commun. 2017 Aug 30;22(sup1):51–58. doi: 10.1080/10810730.2016.1209598.
    1. The 44th Statistical Report on Internet Development in China. Webpage in Chinese. China Internet Network Information Center. 2019. Aug 30, [2020-03-20]. .
    1. Costantino C, Restivo V, Ventura G, D'Angelo C, Randazzo M, Casuccio N, Palermo M, Casuccio A, Vitale F. Increased Vaccination Coverage among Adolescents and Young Adults in the District of Palermo as a Result of a Public Health Strategy to Counteract an 'Epidemic Panic'. Int J Environ Res Public Health. 2018 May 17;15(5):1014. doi: 10.3390/ijerph15051014.
    1. Wakefield MA, Loken B, Hornik RC. Use of mass media campaigns to change health behaviour. Lancet. 2010 Oct;376(9748):1261–1271. doi: 10.1016/s0140-6736(10)60809-4.
    1. Kim J, Jung M. Associations between media use and health information-seeking behavior on vaccinations in South Korea. BMC Public Health. 2017 Sep 11;17(1):700. doi: 10.1186/s12889-017-4721-x.
    1. Alexander CC, Shrestha S, Tounkara MD, Cooper S, Hunt L, Hoj TH, Dearden K, Kezakubi D, Atugonza V, West J, Crookston B, Hall C. Media Access is Associated with Knowledge of Optimal Water, Sanitation and Hygiene Practices in Tanzania. Int J Environ Res Public Health. 2019 Jun 03;16(11):1963. doi: 10.3390/ijerph16111963.
    1. Bull SS, Levine DK, Black SR, Schmiege SJ, Santelli J. Social media-delivered sexual health intervention: a cluster randomized controlled trial. Am J Prev Med. 2012 Nov;43(5):467–74. doi: 10.1016/j.amepre.2012.07.022.
    1. Gough A, Hunter RF, Ajao O, Jurek A, McKeown G, Hong J, Barrett E, Ferguson M, McElwee G, McCarthy M, Kee F. Tweet for Behavior Change: Using Social Media for the Dissemination of Public Health Messages. JMIR Public Health Surveill. 2017 Mar 23;3(1):e14. doi: 10.2196/publichealth.6313.
    1. O'Leary ST, Narwaney KJ, Wagner NM, Kraus CR, Omer SB, Glanz JM. Efficacy of a Web-Based Intervention to Increase Uptake of Maternal Vaccines: An RCT. Am J Prev Med. 2019 Oct;57(4):e125–e133. doi: 10.1016/j.amepre.2019.05.018.
    1. Vasconcelos Silva C, Jayasinghe D, Janda M. What Can Twitter Tell Us about Skin Cancer Communication and Prevention on Social Media? Dermatology. 2020 Feb 25;236(2):81–89. doi: 10.1159/000506458.
    1. Lwin M, Lu J, Sheldenkar A, Schulz P. Strategic Uses of Facebook in Zika Outbreak Communication: Implications for the Crisis and Emergency Risk Communication Model. Int J Environ Res Public Health. 2018 Sep 10;15(9):1974. doi: 10.3390/ijerph15091974.
    1. Yang Q, Wu S. How Social Media Exposure to Health Information Influences Chinese People's Health Protective Behavior during Air Pollution: A Theory of Planned Behavior Perspective. Health Commun. 2019 Nov 24;:1–10. doi: 10.1080/10410236.2019.1692486.
    1. Bandura A. Social Cognitive Theory of Mass Communication. Media Psychology. 2001 Aug;3(3):265–299. doi: 10.1207/s1532785xmep0303_03.
    1. Lim JS, Choe M, Zhang J, Noh G. The role of wishful identification, emotional engagement, and parasocial relationships in repeated viewing of live-streaming games: A social cognitive theory perspective. Computers in Human Behavior. 2020 Jul;108:106327. doi: 10.1016/j.chb.2020.106327.
    1. Sarkar U, Le GM, Lyles CR, Ramo D, Linos E, Bibbins-Domingo K. Using Social Media to Target Cancer Prevention in Young Adults: Viewpoint. J Med Internet Res. 2018 Jun 05;20(6):e203. doi: 10.2196/jmir.8882.
    1. Hansen AH, Claudi T, Årsand E. Associations Between the Use of eHealth and Out-of-Hours Services in People With Type 1 Diabetes: Cross-Sectional Study. J Med Internet Res. 2019 Mar 21;21(3):e13465. doi: 10.2196/13465.
    1. Moon M, Shim J. Social media effects? J Commun Manag. 2019 Nov 04;23(4):281–297. doi: 10.1108/jcom-01-2019-0002.
    1. Li X, Zhang G. Perceived Credibility of Chinese Social Media: Toward an Integrated Approach. IJPOR. 2017 Feb 06;30(1):79–101. doi: 10.1093/ijpor/edw035.
    1. Lin W, Zhang X, Cao B. How Do New Media Influence Youths’ Health Literacy? Exploring the Effects of Media Channel and Content on Safer Sex Literacy. Int J Sex Health. 2018 Dec 11;30(4):354–365. doi: 10.1080/19317611.2018.1509921.
    1. Park S, Avery EJ. Effects of Media Channel, Crisis Type and Demographics on Audience Intent to Follow Instructing Information During Crisis. J Contingencies Crisis Man. 2016 Nov 10;26(1):69–78. doi: 10.1111/1468-5973.12137.
    1. Kim H, An B. A Study on the Effects of the attractiveness and credibility of Online 1 Personal Media Broadcasting B.J. on the Viewing Engagement perceived on Media Channel, Interactivity, Perceived Enjoyment, and the User’s Responses. Article in Korean. Advert Res. 2018 Sep 30;118:78–126. doi: 10.16914/ar.2018.118.78.
    1. Alhuwail D, Abdulsalam Y. Assessing Electronic Health Literacy in the State of Kuwait: Survey of Internet Users From an Arab State. J Med Internet Res. 2019 May 24;21(5):e11174. doi: 10.2196/11174.
    1. Stawarz K, Preist C, Coyle D. Use of Smartphone Apps, Social Media, and Web-Based Resources to Support Mental Health and Well-Being: Online Survey. JMIR Ment Health. 2019 Jul 12;6(7):e12546. doi: 10.2196/12546.
    1. Kickbusch IS. Health literacy: addressing the health and education divide. Health Promot Int. 2001 Sep;16(3):289–97. doi: 10.1093/heapro/16.3.289.
    1. Institute of Medicine. Board on Neuroscience and Behavioral Health. Committee on Health Literacy . In: Health Literacy: A Prescription to End Confusion. Nielsen-Bohlman L, Panzer AM, Kindig DA, editors. Washington, DC: The National Academies Press; 2004.
    1. Norman CD, Skinner HA. eHEALS: The eHealth Literacy Scale. J Med Internet Res. 2006 Nov 14;8(4):e27. doi: 10.2196/jmir.8.4.e27.
    1. Tennant B, Stellefson M, Dodd V, Chaney B, Chaney D, Paige S, Alber J. eHealth literacy and Web 2.0 health information seeking behaviors among baby boomers and older adults. J Med Internet Res. 2015 Mar 17;17(3):e70. doi: 10.2196/jmir.3992.
    1. Kim KA, Kim YJ, Choi M. Association of Electronic Health Literacy With Health-Promoting Behaviors in Patients With Type 2 Diabetes. CIN: Computers, Informatics, Nursing. 2018;36(9):438–447. doi: 10.1097/cin.0000000000000438.
    1. Stellefson M, Paige SR, Alber JM, Chaney BH, Chaney D, Apperson A, Mohan A. Association Between Health Literacy, Electronic Health Literacy, Disease-Specific Knowledge, and Health-Related Quality of Life Among Adults With Chronic Obstructive Pulmonary Disease: Cross-Sectional Study. J Med Internet Res. 2019 Jun 06;21(6):e12165. doi: 10.2196/12165.
    1. Yang SC, Luo YF, Chiang C. Electronic Health Literacy and Dietary Behaviors in Taiwanese College Students: Cross-Sectional Study. J Med Internet Res. 2019 Nov 26;21(11):e13140. doi: 10.2196/13140.
    1. Burns JR, Rapee RM. Adolescent mental health literacy: young people's knowledge of depression and help seeking. J Adolesc. 2006 Apr;29(2):225–39. doi: 10.1016/j.adolescence.2005.05.004.
    1. Kim S, Love F, Quistberg DA, Shea JA. Association of health literacy with self-management behavior in patients with diabetes. Diabetes Care. 2004 Dec;27(12):2980–2. doi: 10.2337/diacare.27.12.2980.
    1. Edukugho AA, Umoh JU, Diem M, Ajani G, Uba B, Okeke L, Adedire E, Adefisoye A, Edukugho C, Nguku P. Knowledge, attitudes and practices towards rabies prevention among residents of Abuja municipal area council, Federal Capital Territory, Nigeria. Pan Afr Med J. 2018;31:21. doi: 10.11604/pamj.2018.31.21.15120.
    1. Gajda M, Kowalska M. The Web-Based Randomized Controlled Intervention as the Enhancer of Cancer Prevention. Medicina (Kaunas) 2019 Aug 03;55(8):434. doi: 10.3390/medicina55080434.
    1. Cho YI, Lee SD, Arozullah AM, Crittenden KS. Effects of health literacy on health status and health service utilization amongst the elderly. Soc Sci Med. 2008 Apr;66(8):1809–16. doi: 10.1016/j.socscimed.2008.01.003.
    1. Gazmararian JA, Williams MV, Peel J, Baker DW. Health literacy and knowledge of chronic disease. Patient Education and Counseling. 2003 Nov;51(3):267–275. doi: 10.1016/s0738-3991(02)00239-2.
    1. Bains SS, Egede LE. Associations between health literacy, diabetes knowledge, self-care behaviors, and glycemic control in a low income population with type 2 diabetes. Diabetes Technol Ther. 2011 Mar;13(3):335–41. doi: 10.1089/dia.2010.0160.
    1. Questionnaire Star. Webpage in Chinese. [2020-10-06].
    1. Prevention of Coronavirus Disease 2019. Government of the Hong Kong Special Administrative Region. [2020-01-07]. .
    1. Protocol for Prevention and Control of COVID-19. Chinese Center for Disease Control and Prevention. [2020-10-07]. .
    1. Whitehead D. Using mass media within health-promoting practice: a nursing perspective. J Adv Nurs. 2000 Oct;32(4):807–16. doi: 10.1046/j.1365-2648.2000.01544.x.
    1. Huhman M, Potter LD, Wong FL, Banspach SW, Duke JC, Heitzler CD. Effects of a mass media campaign to increase physical activity among children: year-1 results of the VERB campaign. Pediatrics. 2005 Aug;116(2):e277–84. doi: 10.1542/peds.2005-0043.
    1. Hökby S, Hadlaczky G, Westerlund J, Wasserman D, Balazs J, Germanavicius A, Machín N, Meszaros G, Sarchiapone M, Värnik Airi, Varnik P, Westerlund M, Carli V. Are Mental Health Effects of Internet Use Attributable to the Web-Based Content or Perceived Consequences of Usage? A Longitudinal Study of European Adolescents. JMIR Ment Health. 2016 Jul 13;3(3):e31. doi: 10.2196/mental.5925.
    1. Cho H, Li W, Shen L, Cannon J. Mechanisms of Social Media Effects on Attitudes Toward E-Cigarette Use: Motivations, Mediators, and Moderators in a National Survey of Adolescents. J Med Internet Res. 2019 Jun 27;21(6):e14303. doi: 10.2196/14303.
    1. Acun I. The Relationship among University Students’ Trust, Self-Esteem, Satisfaction with Life and Social Media Use. Int J Instruction. 2020 Jan 03;13(1):35–52. doi: 10.29333/iji.2020.1313a.
    1. Dellarocas C, Sutanto J, Calin M, Palme E. Attention Allocation in Information-Rich Environments: The Case of News Aggregators. Management Science. 2016 Sep;62(9):2543–2562. doi: 10.1287/mnsc.2015.2237.
    1. Calzada J, Gil R. What Do News Aggregators Do? Evidence from Google News in Spain and Germany. Marketing Science. 2020 Jan;39(1):134–167. doi: 10.1287/mksc.2019.1150.
    1. Repnikova M, Fang K. Digital Media Experiments in China: “Revolutionizing” Persuasion under Xi Jinping. The China Quarterly. 2019 Apr 8;239:679–701. doi: 10.1017/s0305741019000316.
    1. Deng J. Janus: How exceptionalism based on regaining influence and doing new media help a Chinese mobile news app negotiate censorship for better journalism. Communication and the Public. 2018 Apr 09;3(2):113–133. doi: 10.1177/2057047318770466.
    1. Jang K, Baek YM. When Information from Public Health Officials is Untrustworthy: The Use of Online News, Interpersonal Networks, and Social Media during the MERS Outbreak in South Korea. Health Commun. 2019 Aug;34(9):991–998. doi: 10.1080/10410236.2018.1449552.
    1. Calder K, D'Aeth L, Turner S, Begg A, Veer E, Scott J, Fox C. Evaluation of the All Right? Campaign's Facebook intervention post-disaster in Canterbury, New Zealand. Health Promot Int. 2020 Feb 01;35(1):111–122. doi: 10.1093/heapro/day106.
    1. Kalichman SC, Benotsch E, Suarez T, Catz S, Miller J, Rompa D. Health literacy and health-related knowledge among persons living with HIV/AIDS. American Journal of Preventive Medicine. 2000 May;18(4):325–331. doi: 10.1016/s0749-3797(00)00121-5.
    1. Jorm AF. Mental health literacy. Public knowledge and beliefs about mental disorders. Br J Psychiatry. 2000 Nov;177:396–401. doi: 10.1192/bjp.177.5.396.
    1. Morris NS, Field TS, Wagner JL, Cutrona SL, Roblin DW, Gaglio B, Williams AE, Han PJK, Costanza ME, Mazor KM. The association between health literacy and cancer-related attitudes, behaviors, and knowledge. J Health Commun. 2013 Dec 04;18 Suppl 1(sup1):223–41. doi: 10.1080/10810730.2013.825667.
    1. Mueller J, Davies A, Jay C, Harper S, Blackhall F, Summers Y, Harle A, Todd C. Developing and testing a web-based intervention to encourage early help-seeking in people with symptoms associated with lung cancer. Br J Health Psychol. 2019 Feb;24(1):31–65. doi: 10.1111/bjhp.12325.
    1. Alsahafi A, Cheng A. Knowledge, Attitudes and Behaviours of Healthcare Workers in the Kingdom of Saudi Arabia to MERS Coronavirus and Other Emerging Infectious Diseases. Int J Environ Res Public Health. 2016 Dec 06;13(12):1214. doi: 10.3390/ijerph13121214.
    1. Ashida S, Goodman M, Pandya C, Koehly L, Lachance C, Stafford J, Kaphingst K. Age differences in genetic knowledge, health literacy and causal beliefs for health conditions. Public Health Genomics. 2011;14(4-5):307–16. doi: 10.1159/000316234.
    1. Lindau ST, Tomori C, Lyons T, Langseth L, Bennett CL, Garcia P. The association of health literacy with cervical cancer prevention knowledge and health behaviors in a multiethnic cohort of women. Am J Obstet Gynecol. 2002 May;186(5):938–43. doi: 10.1067/mob.2002.122091.
    1. El Khoury G, Salameh P. Influenza Vaccination: A Cross-Sectional Survey of Knowledge, Attitude and Practices among the Lebanese Adult Population. Int J Environ Res Public Health. 2015 Dec 05;12(12):15486–97. doi: 10.3390/ijerph121215000.
    1. Huesch MD, Galstyan A, Ong MK, Doctor JN. Using Social Media, Online Social Networks, and Internet Search as Platforms for Public Health Interventions: A Pilot Study. Health Serv Res. 2016 Jun 10;51 Suppl 2:1273–90. doi: 10.1111/1475-6773.12496.
    1. Mouchtouri V, Papagiannis D, Katsioulis A, Rachiotis G, Dafopoulos K, Hadjichristodoulou C. Knowledge, Attitudes, and Practices about the Prevention of Mosquito Bites and Zika Virus Disease in Pregnant Women in Greece. Int J Environ Res Public Health. 2017 Mar 31;14(4):367. doi: 10.3390/ijerph14040367.
    1. Bujnowska-Fedak MM, Węgierek P. The Impact of Online Health Information on Patient Health Behaviours and Making Decisions Concerning Health. Int J Environ Res Public Health. 2020 Jan 31;17(3):880. doi: 10.3390/ijerph17030880.
    1. Yaya S, Bishwajit G, Ekholuenetale M, Shah V, Kadio B, Udenigwe O. Knowledge of prevention, cause, symptom and practices of malaria among women in Burkina Faso. PLoS One. 2017;12(7):e0180508. doi: 10.1371/journal.pone.0180508.

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