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. 2022 Jun 15;13:912397. doi: 10.3389/fpsyt.2022.912397

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Copyright © 2022 Piksa, Noworyta, Piasecki, Gwiazdzinski, Gundersen, Kunst and Rygula.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Division based on the average true and fake news ratings. (A) Comparison of the average true news veracity ratings () with the average fake news veracity ratings () in groups that were differentiated based on the average low (N = 93) and high true (N = 91) news veracity ratings (). (B) Comparison of the average fake news veracity ratings () with the average true news veracity ratings () in groups that were differentiated based on the average low (N = 96) and high (N = 88) fake news veracity ratings (). The data are presented as AVG veracity ratings ± SEM.

Inline graphic — Division based on the average true and fake news ratings. (A) Comparison of the average true news veracity ratings () with the average fake news veracity ratings () in groups that were differentiated based on the average low (N = 93) and high true (N = 91) news veracity ratings (). (B) Comparison of the average fake news veracity ratings () with the average true news veracity ratings () in groups that were differentiated based on the average low (N = 96) and high (N = 88) fake news veracity ratings (). The data are presented as AVG veracity ratings ± SEM.