Effects of cognitive biases on the perception of health-related (mis)information and their behavioral and neural correlates, RSF 23-78-10035

Project leader: Elena Artemenko

Participants: Sergey Koltsov, Evgenia Alenina, Alexia Syromyatnikova, Mikhail Yatsenko, Maxim Lihankov, Sofya Popova

In cognitive research, an individual's orientation in the flow of informational messages and the choice of which information to trust and which not to, is traditionally considered a result of logical operations within the decision-making system. However, in reality, such decisions are almost always influenced by individual and universal systematic errors in cognitive thinking schemes known as cognitive biases. One such bias, known as confirmation bias, involves an individual's inclination to trust information that seems consistent with their beliefs. Distorted interpretation of information messages can lead to the subsequent spread of unreliable (false) information. This has become one of the primary socio-cultural threats affecting the success of socially significant public initiatives, including those related to public health, such as vaccination campaigns (both during pandemics and routine vaccination situations).

At present, although the topic of confirmation bias distortion is well-developed in social sciences overall, it is poorly studied concerning health-related information, especially in the Russian context. Moreover, oculomotor and neurophysiological markers, which could form the basis for a more objective measurement of the results of this process, remain completely unexplored. Obtaining a more objective and accurate understanding of the influence of biases on information processing would help develop more effective measures to combat trust in unreliable information and prevent its spread. This lack of knowledge forms the scientific problem addressed by this research.

The main goal of the conducted research: to assess the influence of confirmation bias cognitive distortion on trust in information messages, using health-related information as an example, and to identify oculomotor and neurophysiological markers of behavioral and neural differences in the perception of medical text corresponding or not corresponding to user beliefs, including through machine learning methods allowing for its objective measurement in the future.

Key objectives:

1. Evaluation of the impact of confirmation bias cognitive distortion on trust in informational messages within the medical field (specifically in the context of population vaccination).
2. Identification of behavioral and neural differences in the perception of medical text that aligns or contrasts with users' beliefs, including through the utilization of machine learning methods.

1. VIII International Conference "Signal Processing of Video and Audio in the Context of Neurotechnologies" (SPCN 2023), Oral Presentation: "Utilization of Machine Learning Methods in Oculomotor Data Analysis," November 7-10, 2023, St. Petersburg, Russia.
2. International Forum "COGNITIVE NEUROSCIENCE – 2023," Presentation: "Modification of the Implicit Association Test for Assessing Attitudes toward Vaccination," December 7-9, 2023, Yekaterinburg, Russia.

Project News:

The project from the Higher School of Economics in St. Petersburg on cognitive biases and health won a grant from the Russian Science Foundation (RSF)