In late December 2019, the COVID-19 pandemic started to spread from Hubei province in China. Currently there are many affected countries worldwide, including Saudi Arabia. This study aimed to assess the use of social media as a source for COVID-19 awareness in Saudi Arabia. An online survey was conducted between 9 and 13 May 2020 and a total of 3,204 subjects participated in the survey. We used snowball sampling techniques through an online structured questionnaire. The data were cleaned, coded and analysed using the Statistical Package for the Social Sciences SPSS version 25.0. A chi-square test was used to find the associations between variables. Of all participants, 75.4% had a high level of awareness of the COVID-19 pandemic. Saudi participants above 18 years old and medical practitioners showed a high level of awareness. All participants from all regions of Saudi Arabia showed a high level of awareness except for those from the northern region. The most common source of information was the official government social media, and 44.1% reported the use of Twitter. Our findings show that social media have a positive impact on the circulation of information about the COVID-19 pandemic in Saudi Arabia.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFDistress and coping mechanisms among people with diabetes: cross-sectional assessment from an NCD screening clinic of a tertiary care hospital in North India.
Diabetol Metab Syndr
January 2025
Department of Endocrinology, Bharti Hospital, Karnal, Haryana, India.
Background: Of the numerous complications encountered by people with diabetes (PWD), the effect on mental health is concerning. Within mental health, diabetes distress (DD) occurs when a patient has unfavourable emotional stress while managing their condition, which can be managed by coping strategies but are less studied together in Indian settings. So, the present study aimed to determine the proportion of DD and associated factors and coping skills among the PWD.
View Article and Find Full Text PDFNon-thermal atmospheric plasma treatments enhance the growth, photosynthesis, metabolite accumulation, and nutritional value of geranium (Pelargonium graveolens L'Herit) leaves.
BMC Plant Biol
January 2025
Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University, P.O. Box 15551, Al Ain, Abu Dhabi, United Arab Emirates.
This study investigated the effects of non-thermal atmospheric plasma (NTAP) treatment on the growth, chemical composition, and biological activity of geranium (Pelargonium graveolens L'Herit) leaves. NTAP was applied at a frequency of 13.56 MHz, exposure time of 15 s, discharge temperature of 25 °C, and power levels (T1 = 50, T2 = 80, and T3 = 120 W).
View Article and Find Full Text PDFApplication of artificial intelligence in nursing practice: a qualitative study of Jordanian nurses' perspectives.
BMC Nurs
January 2025
Nursing Department, Hamad Medical Corporation, Doha, P.O. Box 3050, Qatar.
Background: Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.
View Article and Find Full Text PDFPredicting land use and land cover changes for sustainable land management using CA-Markov modelling and GIS techniques.
Sci Rep
January 2025
Department of Wildlife Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, 39762-9690, USA.
This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is crucial for mitigating adverse environmental impacts and promoting sustainable development. The main goal is to evaluate historical LULC changes from 1994 to 2024 and forecast future trends for 2034 and 2044 utilizing the CA-Markov hybrid model combined with GIS methodologies.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!