An Ecological Model Analysis of COVID-19 Social Media Posts.
| Autor: | Grossman, Suzanne1, Alber, Julia M.2, Henry, Dayna S.1, Askay, David3, Glanz, Hunter4, Marts, Erika2, Ostrander, Anna2 |
|---|---|
| Předmět: |
*Social media
*Information resources *Communication *Misinformation *COVID-19 pandemic Health policy Ecological research Pearson correlation (Statistics) Health Disease prevalence Chi-squared test Descriptive statistics Stay-at-home orders Psychological adaptation Statistical sampling Technology Data analysis software Health promotion |
| Zdroj: | Journal of Consumer Health on the Internet. Jul-Sep2022, Vol. 26 Issue 3, p248-258. 11p. |
| Abstrakt: | 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. [ABSTRACT FROM AUTHOR] |
| Databáze: | Library, Information Science & Technology Abstracts |
| Externí odkaz: |
|