The CDC and State Health Department Facebook Messages: An Examination of Frames and the Extended Parallel Processing Model

ABSTRACT

Public health organizations such as the Centers for Disease Control and Prevention (CDC) and state and local health departments are increasingly using social media in health education and promotion. Guided by the Extended Parallel Processing Model and framing theory, this study analyzed the Facebook messages of both the CDC and state health departments in 2017 to examine the extent to which such messages used these theories of social influence. All messages posted by the CDC in 2017 were downloaded. A multi-stage random sampling method was used to identify state-level health departments’ posts. Differences were found in the CDC and state health organizations’ Facebook messages in terms of the four EPPM variables. The CDC’s Facebook posts were more likely to include severity, susceptibility, self-efficacy, and response efficacy than those posted by state health departments. In addition, while the state health departments were more likely to use gain frames, the CDC was more likely to use both gain and loss frames simultaneously.

KEYWORDS:

• The EPPM
• framing
• efficacy
• social media
• fear appeals
• health messages

Disclosure Statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Cui Zhang Meadows

Cui Zhang Meadows is an assistant professor in the School of Communication at East Carolina University. Her research focuses on the areas of health communication and crisis communication.

Charles W. Meadows

Charles W. Meadows is an assistant professor in the School of Communication at East Carolina University. His research focuses on the areas of health communication and new media.

Lu Tang

Lu Tang is an associate professor at Department of Communication, Texas A&M University. She conducts research on health and social media from a variety of approaches, such as network analysis, machine learning, and traditional content analysis. Her recent studies examine topics such emerging infectious diseases and vaccines on Twitter.