Wu Yuxuan
School of History and Culture, Shandong University, Jinan, Shandong, 250100, People's Republic of China.
Psychol Res Behav Manag. 2023 Apr 27;16:1495-1508. doi: 10.2147/PRBM.S404911. eCollection 2023.
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.
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.
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).
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.
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.
社交媒体上普遍存在的健康错误信息会影响人们的健康。在分享健康信息之前进行事实核查是一种利他行为,能够有效应对社交媒体上的健康错误信息。
基于假定媒体影响(IPMI)的影响,本研究有两个目的:一是根据IPMI模型调查影响社交媒体用户在分享健康信息之前进行事实核查决策的因素。二是探索IPMI模型对不同利他水平个体的不同预测能力。
本研究对1045名中国成年人进行了问卷调查。参与者以利他主义的中位数分为低利他主义组(n = 545)或高利他主义组(n = 500)。使用R语言Lavaan软件包(版本0.6 - 15)进行多组分析。
所有假设均得到支持,这证实了IPMI模型在社交媒体上分享健康信息前进行事实核查背景下的适用性。值得注意的是,IPMI模型在低利他主义组和高利他主义组中产生了不同的结果。
本研究证实IPMI模型可用于健康信息事实核查的背景中。关注健康错误信息会间接影响个体在社交媒体上分享健康信息之前进行事实核查的意图。此外,本研究展示了IPMI模型对不同利他水平个体的不同预测能力,并推荐了健康促进官员可以采取的具体策略,以鼓励其他人对健康信息进行事实核查。