Audience-Centered Approach for Health Communication over Social Media during Pandemic: Persona Template Based on Delphi Technique

Abstract

Delivering a relevant health message can be achieved by understanding the audience. Persona is one of the approaches used to understand and represent the audience. It is observed that there is no general Persona template used for all contexts in the health field, but it should be adjusted to each context. The aim of this study is to reach a consensus among public health experts on a Persona template to understand the public on social media during pandemics. Three phases are applied in this study. In phase 1, we determined an initial set of items that public health experts should understand about the audience to design a relevant message from the literature. In phase 2, a modified Delphi was conducted to reach a consensus on the inclusion of these items in the Persona template by considering the communication over social media during a pandemic. Phase 3 presents the final version of the Persona template. Nine experts completed round 1, and 4 completed the round 2. Experts reached a consensus to include six items in the Persona template: sociodemographic data, preferences for receiving messages, preferred channels, risk perceptions and attitudes, current behavioral responses, and misinformation. The proposed template in this study was agreed upon by nine public health experts as a method to understand the social media audience during pandemics. The proposed template is ready to be filled out and used by health communicators and researchers to design a relevant message for the audience.

Acknowledgments

We would like to express our sincere thanks and appreciation to all experts who participated in both the Delphi study and the pilot survey, which contributed to the completion of this study.

Ethical approval

We obtained formal ethical approval from the research ethics committee at King Abdulaziz University, reference number 390-21. We also obtained written informed consent from all participants where the study aim and the survey goal were clearly explained. Moreover, experts were informed that the participation is completely voluntary, they may withdraw from the study at any time, will keep their information confidential, and their names will not be shared or published. Since this process is anonymous, the experts involved will not know each other’s identity. All methods were carried out in accordance with relevant guidelines and regulations.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data generated or analysed during this study are included in this published article.

Additional information

Notes on contributors

Bushra Alsaadi

Bushra Alsaadi received her master’s degree in Computer Information Systems at King Abdulaziz University. She worked as a lecturer at the College of Computer Science, University of Jeddah. She also worked as a research assistant at King Abdulaziz University. Her research interest focuses on health informatics and human-centered design.

Dimah Alahmadi

Dimah Alahmadi is an associate professor at King Abdulaziz University in Information Systems Department. She received her doctorate in Computer Science from the University of Manchester. She has a lot of published researches in artificial intelligence, and her research interest is in Artificial Intelligence, Natural language processing, and Recommender systems.