The Saudi Ministries Twitter communication strategies during the COVID-19 pandemic: A qualitative content analysis study

Raniah N Aldekhyyel; Samar Binkheder; Shahad N Aldekhyyel; Nuha Alhumaid; Marwah Hassounah; Alanoud AlMogbel; Amr A Jamal

doi:10.1016/j.puhip.2022.100257

The Saudi Ministries Twitter communication strategies during the COVID-19 pandemic: A qualitative content analysis study

Public Health Pract (Oxf). 2022 Jun:3:100257. doi: 10.1016/j.puhip.2022.100257. Epub 2022 Apr 18.

Authors

Raniah N Aldekhyyel¹, Samar Binkheder¹, Shahad N Aldekhyyel², Nuha Alhumaid², Marwah Hassounah³, Alanoud AlMogbel⁴, Amr A Jamal^{3

5}

Affiliations

¹ Medical Informatics Unit, Medical Education Department, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
² College of Public Health and Health Informatics, King Saud bin Abdulaziz for Health Sciences, Riyadh, Saudi Arabia.
³ Family & Community Medicine Department, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
⁴ Riyadh, Saudi Arabia.
⁵ Evidence-Based Health Care & Knowledge Translation Research Chair, King Saud University, Riyadh, Saudi Arabia.

Abstract

Objectives: To understand government communication strategies during the COVID-19 pandemic by examining topics related to COVID-19 posted by Saudi governmental ministries on Twitter and situating our findings within existing health behavior theoretical frameworks.

Study design: Retrospective content analysis of COVID-19 related tweets.

Methods: On November 7th, 2020, we extracted relevant tweets posted by five Saudi governmental ministries. After we extracted the data, we developed and applied a coding schema.

Results: A total of 3,950 tweets were included in our dataset. Topics fell into two groups: disease-related (49.2%) and non-disease related (50.8%). The disease-related group included seven categories: awareness (18.5%), symptom (0.6%), prevention (7.7%), disease transmission (1.9%), treatment (0.3%), testing (3.4%), and reports (16.7%). The non-disease related group included eight categories: lockdown (5.9%), online learning (12.8%), digital platforms (4.3%), empowerment (12.0%), accountability (1.1%), non-disease reports (2.1%), local and international news (10.8%), and general statements (1.9%). Based on the correlation analysis, we found that the top positively correlated categories were: "testing" and "digital platforms" (r = 0.4157), "awareness" and "prevention" (r = 0.3088), "prevention" and "disease transmission" (r = 0.3025), "awareness" and "disease transmission" (r = 0.1685), "symptom" and "testing" (r = 0.1081), "awareness" and "symptom" (r = 0.0812), "symptom" and "digital platforms" (r = 0.0645), and "disease transmission" and "digital platforms" (r = 0.0450), p-values < 0.01. Several health behavior theoretical constructs were linked to our findings.

Conclusions: Integrating behavioral theories in the development of health risk communication should be taken seriously by government communication specialists who manage social media accounts, as these theories help underlining determinants of people's behaviors.

Keywords: COVID-19; Government communication; Public health; Saudi Arabia; Twitter.