The Impact of Biases on Health Disinformation Research

Carmen Peñafiel-Saiz (), Lázaro Echegaray-Eizaguirre and Amaia Perez- de-Arriluzea-Madariaga
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Carmen Peñafiel-Saiz: Journalism Department, Campus of Leioa, University of the Basque Country, 48940 Leioa, Spain
Lázaro Echegaray-Eizaguirre: Sociology and Market Research Area, Camarabilbao University Business School, 48011 Bilbao, Spain
Amaia Perez- de-Arriluzea-Madariaga: LAMS Programme, Faculty of Arts of the Araba Campus, University of the Basque Country, 01006 Vitoria-Gasteiz, Spain

Societies, 2024, vol. 14, issue 5, 1-17

Abstract: This work analyses the treatment of elements such as biases and their relationship with disinformation in international academic production. The first step in this process was to carry out a search for papers published in academic journals indexed in the main indexing platforms. This was followed by a bibliometric analysis involving an analysis of the production and impact of the selected publications, using social media techniques and a semantic content analysis based on abstracts. The data obtained from Web of Science, Scopus, and Dimensions, relating to health, biases, and fake news as well as post-truth, show how these works have multiplied in the last decade. The question relating to this research is as follows: How have cognitive biases been treated in national and international academic journals? This question is answered with respect to the scientific or research method. The results, which date from 2000 to 2024, show a considerable academic dedication to exploring the relationship between biases and health disinformation. In all these communities we have observed a relationship between production with the field of medicine as a general theme and social media. Furthermore, this connection is always tied to other subjects, such as an aversion to vaccines in Community 10; disinformation about COVID-19 on social media in Community 5; COVID-19 and conspiracy theories in Community 6; and content for the dissemination of health-related subjects on YouTube and the disinformation spread about them. The community analysis carried out shows a common factor in all the analysed communities—that of cognitive bias.

Keywords: health communication; misinformation; disinformation; types of bias; health investigation; communication; social network analysis (search for similar items in EconPapers)
JEL-codes: A13 A14 P P0 P1 P2 P3 P4 P5 Z1 (search for similar items in EconPapers)
Date: 2024
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