An Ecological Model Analysis of COVID-19 Social Media Posts

• Published in: Journal of consumer health on the Internet Vol. 26; no. 3; pp. 248 - 258
• Main Authors: Grossman, Suzanne, Alber, Julia M., Henry, Dayna S., Askay, David, Glanz, Hunter, Marts, Erika, Ostrander, Anna
• Format: Journal Article
• Language: English
• Published: New York Routledge 03-07-2022; Taylor & Francis Ltd
• Subjects: Communication technology; Coping; Coronaviruses; COVID-19; Digital media; Mathematical models; Random sampling; Risk management; social ecological model; social media; Social networks
• ISSN: 1539-8285; 1539-8293
• DOI: 10.1080/15398285.2022.2081910

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.