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Predicting Fact-Checking Health Information Before Sharing Among People with Different Levels of Altruism: Based on the Influence of Presumed Media Influence
BACKGROUND: Pervasive health misinformation on social media affects people’s health. Fact-checking health information before it is shared is an altruistic behavior that effectively addresses health misinformation on social media. PURPOSE: Based on the influence of presumed media influence (IPMI), th...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150741/ https://www.ncbi.nlm.nih.gov/pubmed/37138700 http://dx.doi.org/10.2147/PRBM.S404911 |
Sumario: | BACKGROUND: Pervasive health misinformation on social media affects people’s health. Fact-checking health information before it is shared is an altruistic behavior that effectively addresses health misinformation on social media. PURPOSE: Based on the influence of presumed media influence (IPMI), this study serves two purposes: The first is to investigate factors that influence social media users’ decisions to fact-check health information before sharing it in accordance with the IPMI model. The second is to explore different predictive powers of the IPMI model for individuals with different levels of altruism. METHODS: This study conducted a questionnaire survey of 1045 Chinese adults. Participants were divided into either a low-altruism group (n = 545) or a high-altruism group (n = 500) at the median value of altruism. A multigroup analysis was conducted with R Lavaan package (Version 0.6–15). RESULTS: All of the hypotheses were supported, which confirms the applicability of the IPMI model in the context of fact-checking health information on social media before sharing. Notably, the IPMI model yielded different results for the low- and high-altruism groups. CONCLUSION: This study confirmed the IPMI model can be employed in the context of fact-checking health information. Paying attention to health misinformation can indirectly affect an individual’s intention to fact-check health information before they share it on social media. Furthermore, this study demonstrated the IPMI model’s varying predictive powers for individuals with different altruism levels and recommended specific strategies health-promotion officials can take to encourage others to fact-check health information. |
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