Fuławka Kamil, Hertwig Ralph, Pachur Thorsten
Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany.
School of Management, Technical University of Munich, Munich, Germany.
NPJ Vaccines. 2024 Sep 14;9(1):167. doi: 10.1038/s41541-024-00951-8.
Vaccine hesitancy was a major challenge during the COVID-19 pandemic. A common but sometimes ineffective intervention to reduce vaccine hesitancy involves providing information on vaccine effectiveness, side effects, and related probabilities. Could biased processing of this information contribute to vaccine refusal? We examined the information inspection of 1200 U.S. participants with anti-vaccination, neutral, or pro-vaccination attitudes before they stated their willingness to accept eight different COVID-19 vaccines. All participants-particularly those who were anti-vaccination-frequently ignored some of the information. This deliberate ignorance, especially toward probabilities of extreme side effects, was a stronger predictor of vaccine refusal than typically investigated demographic variables. Computational modeling suggested that vaccine refusals among anti-vaccination participants were driven by ignoring even inspected information. In the neutral and pro-vaccination groups, vaccine refusal was driven by distorted processing of side effects and their probabilities. Our findings highlight the necessity for interventions tailored to individual information-processing tendencies.
在新冠疫情期间,疫苗犹豫是一项重大挑战。一种常见但有时无效的减少疫苗犹豫的干预措施是提供有关疫苗有效性、副作用及相关概率的信息。对这些信息的有偏差处理会导致拒绝接种疫苗吗?我们调查了1200名有反疫苗、中立或支持疫苗态度的美国参与者在表明愿意接受八种不同新冠疫苗之前对信息的审视情况。所有参与者,尤其是那些反疫苗者,经常忽略一些信息。这种刻意的忽视,尤其是对极端副作用概率的忽视,比通常调查的人口统计学变量更能预测疫苗接种的拒绝情况。计算模型表明,反疫苗参与者拒绝接种疫苗是因为即使审视过的信息也被忽略。在中立和支持疫苗的群体中,拒绝接种疫苗是由对副作用及其概率的扭曲处理导致的。我们的研究结果凸显了针对个体信息处理倾向进行干预的必要性。