TikTok has become increasingly popular among young people in China and there is growing number of young people who start to pay great attention to their health through this platform. Wuhan is a significant location for this study, since it was the initial epicenter of COVID-19. However, little is known about the extent to which university students in Wuhan, China, rely on TikTok for health-related information and how this affects their preventive health actions in the post-COVID-19 era. Therefore, it is crucial to look into the direct effects of TikTok users' search for health information and their actions to protect their health, as well as the mediating functions of e-health literacy and COVID-19 risk perception. The impact of TikTok as a social media platform on the health-related behaviors of university students was examined using the Media Dependency Theory which explains how media use can have significant effects on individuals' attitudes, beliefs, and behaviors. 426 questionnaires were gathered by cluster sampling from a sample of Wuhan university students. Mplus8 was used to perform structural equation modelling, which looked at the relationships between these variables. The results showed a positive correlation between users' TikTok health information seeking and their health preventive behavior (β = 0.303, p
The agricultural sector is the backbone and single-largest sector of the Pakistani economy. Pakistan's agricultural productivity is suffering due to climate change. The study aimed at finding how social media reporting can change patterns of attitudes among farmers to cope with sudden weather changes. A correlation-experimental research design was used to find the relationships and effects of climate change on agriculture in Punjab (Pakistan) and the mediating effect of social media reporting. A purposive sampling technique was used to collect samples from 120 male farmers. Online surveys, with the help of Google Docs, were used to collect participants' responses about the type of behavior they used to adopt when getting information about climate change through social media. After determining their reliability and validity through piloting, two self-constructed questionnaires were used: (i) Measuring Farmers' Behavior Influenced by Social Media Reporting of Climate Change and (ii) Effects of Social Media Reporting of Climate Change on Agriculture. Data were analyzed using SPSS-21, and correlation analysis was done to find out the relationship between social media reporting and farmers' behavior. Linear regression was used to measure the functional relationship between social media reporting about climate change and farmers' attitudes towards adopting precautions to increase annual yield. The coefficient of social media reporting was positively and significantly related to farmers' attitudes towards the selection of crops, land management, and water storage. Based on the findings, the social media reports significantly predicted patterns of farmers' behavior towards the adaptation of advanced measures to select crops, reduce pest attacks, manage land, and store water.