With the expansion of health information sources to include user-generated and decentralized outlets, the public has access to more diverse platforms/outlets to aid in health decision-making. Unfortunately, the abundance of information sources also makes individuals vulnerable for exposure to false and potentially threatening health information. The extensive reach, design, and personalized nature of health messages can persuade people to adopt and/or reinforce inaccurate beliefs about health topics and lead to resistance to positive health actions. Furthermore, as technological progress allows for more dynamic health care interactions, it also increases the challenges in identifying and resisting the impact of false/inaccurate health information.
This Research Topic welcomes contributions from a range of conceptual and methodological approaches to spotlight and tackle health misinformation, a concern that poses greater risk than ever in thwarting the effectiveness of both large-scale public health campaigns, and smaller, community-led initiatives aimed at reducing health disparities. Ultimately, the Research Topic hopes to provide a comprehensive understanding of the prevalence, nature, and impact of health misinformation and of what strategies may best be applied to mitigate its negative influence on health behaviors.
Possible topics include, but are not limited to, the following:
• conceptualizations/theoretical models of health misinformation
• effects studies examining the impact of health misinformation
• research examining the impact of corrective messaging to combat health misinformation
• research on health misinformation across platforms/channels of communication
• the impact of health misinformation on diverse populations
• individual/psychosocial differences in susceptibility to health misinformation
• research on methodological approaches for identifying online health misinformation (e.g., machine learning and content analysis)
• cross-cultural analyses of health misinformation
• political/partisan components of health misinformation
• content-related studies and/or effects investigations.
We welcome contributions from a range of specializations, including:
• health communication
• risk communication
• information seeking
• public health
• political communication
• political science
• psychology
• computer science.
With the expansion of health information sources to include user-generated and decentralized outlets, the public has access to more diverse platforms/outlets to aid in health decision-making. Unfortunately, the abundance of information sources also makes individuals vulnerable for exposure to false and potentially threatening health information. The extensive reach, design, and personalized nature of health messages can persuade people to adopt and/or reinforce inaccurate beliefs about health topics and lead to resistance to positive health actions. Furthermore, as technological progress allows for more dynamic health care interactions, it also increases the challenges in identifying and resisting the impact of false/inaccurate health information.
This Research Topic welcomes contributions from a range of conceptual and methodological approaches to spotlight and tackle health misinformation, a concern that poses greater risk than ever in thwarting the effectiveness of both large-scale public health campaigns, and smaller, community-led initiatives aimed at reducing health disparities. Ultimately, the Research Topic hopes to provide a comprehensive understanding of the prevalence, nature, and impact of health misinformation and of what strategies may best be applied to mitigate its negative influence on health behaviors.
Possible topics include, but are not limited to, the following:
• conceptualizations/theoretical models of health misinformation
• effects studies examining the impact of health misinformation
• research examining the impact of corrective messaging to combat health misinformation
• research on health misinformation across platforms/channels of communication
• the impact of health misinformation on diverse populations
• individual/psychosocial differences in susceptibility to health misinformation
• research on methodological approaches for identifying online health misinformation (e.g., machine learning and content analysis)
• cross-cultural analyses of health misinformation
• political/partisan components of health misinformation
• content-related studies and/or effects investigations.
We welcome contributions from a range of specializations, including:
• health communication
• risk communication
• information seeking
• public health
• political communication
• political science
• psychology
• computer science.