Vaccination is a vital component in the battle against outbreaks of infectious diseases. Recognizing parents’ reluctance to vaccinate their children is even more critical now, given the ongoing threat of a COVID-19 pandemic. Conspiracy theories, vaccination safety concerns, parental efficacy and risk perception, and a lack of confidence in science all influence intention. To investigate how these variables interact with vaccination behavior against COVID-19, we developed a model with psychosocial factors serving as the predictor and mistrust in science and vaccine knowledge serving as the mediator. In order to validate the model, the parents’ intentions regarding their children’s vaccination with COVID-19 were used. The study included 454 Pakistani parents who completed an online questionnaire assessing their intention to vaccinate their children. We analyzed the data using structural equation modeling (SEM). A significant level of vaccine hesitation is due to belief in vaccine conspiracy theories, and vaccine safety concerns were investigated. A surprising correlation exists between risk perception and vaccination intentions, followed by parental self-efficacy. It is significant to note that vaccine knowledge mediated conspiracy beliefs, risk perceptions, and intentions fully but partially mediated parental self-efficacy. Conspiracy theories were mediated by a mistrust in science, while perceptions of risk and vaccine safety were partially mediated. The findings of this research were used to develop sensible policy reforms and public health campaigns to encourage vaccination against both common infections such as measles, human papillomaviruses, or pertussis, and novel diseases such as COVID-19.
Climate change misinformation leads to significant adverse impacts and has become a global concern. Identifying misinformation and investigating its characteristics are of great importance to counteract misinformation. Therefore, this study aims to characterize the semantic features (frames and authority references) of climate change misinformation in the context of Chinese social media. Posts concerning climate change were collected from Weibo between January 2010 and December 2020. First, veracity, frames, and authority references were manually labeled. Then, we applied logistic regression to examine the relationship between information veracity and semantic features. The results revealed that posts concerning environmental and health impact and science and technology were more likely to be misinformation. Moreover, posts referencing non-specific authority sources are more likely to be misinformed than posts making no references to any authority references. This study provides a theoretical understanding of the semantic characteristics of climate change misinformation and practical suggestions for combating them.
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