An Ecological Model Analysis of COVID-19 Social Media Posts. Issue 3 (3rd July 2022)

• Record Type: Journal Article
• Authors: Grossman, Suzanne; Alber, Julia M.; Henry, Dayna S.; Askay, David; Glanz, Hunter; Marts, Erika; Ostrander, Anna
• Is Part Of: Journal of consumer health on the Internet. Volume 26:Issue 3(2022)
• Page Start: 248
• Page End: 258
• Publication Date: 2022-07-03
• Subjects: Communication technology -- social ecological model -- social media; Health -- Computer network resources -- Periodicals; Internet -- Periodicals; Medical care -- Computer network resources -- Periodicals; Computer Communication Networks -- Periodicals; Consumer Participation -- Periodicals; Delivery of Health Care -- Periodicals; 025.063621
• DOI: 10.1080/15398285.2022.2081910
• Languages: English
• ISSNs: 1539-8285

Abstract

Abstract: This study examined prevention and coping content related to COVID-19 on social media. Publicly available social media posts were examined by levels of the social ecological model (SEM) and by platform (Instagram, TikTok, Twitter). Using systematic random sampling, 1579 public posts were collected from March 2020 to June 2020 using COVID-19 hashtags. Of these, 663 posts written in English about COVID-19 were included. Content was coded by platform, strategies for reducing risk, strategies for coping with stress, and SEM level(s). In total, 41.18% of the posts mentioned a strategy for reducing risk. Few posts mentioned coping strategies (5%). Slightly less than half of the posts focused on the individual level (42.1%). Both the strategies mentioned for reducing risk and SEM levels referenced in each post varied significantly by platform. Results suggest that social media may provide insight into the type of health information the public receives as well as the public's strategies for reducing risk and coping; however, there is variation among platforms.