The spread of pseudoscience (PS) is a worrying problem worldwide. The study of pseudoscience beliefs and their associated predictors have been conducted in the context of isolated pseudoscience topics (e.g., complementary and alternative medicine). Here, we combined individual differences (IIDD) measures (e.g., personality traits, thinking styles) with measures related with the information received about PS: familiarity and disproving information (DI) in order to explore potential differences among pseudoscience topics in terms of their associated variables. These topics differed in their familiarity, their belief rating, and their associated predictors. Critically, our results not only show that DI is negatively associated with pseudoscience beliefs but that the effect of various IIDD predictors (e.g., analytic thinking) depends on whether DI had been received. This study highlights the need to control for variables related to information received about pseudoscientific claims to better understand the effect of other predictors on different pseudoscience beliefs topics.

The popularity and spread of health-related pseudoscientific practices is a worldwide problem. Despite being counteracted by competent agents of our societies, their prevalence and spread continue to grow. Current research has focused on identifying which characteristics make us more likely to hold pseudoscientific beliefs. However, how we hold these beliefs despite all the available information against them is a question that remains unanswered. Here, we aimed to assess if the development of health-related pseudoscientific beliefs could be driven by a positive bias in belief updating. Additionally, we aimed to explore whether this bias could be exacerbated, depending on source credibility. In this study, participants (N = 116) underwent a belief updating task where they offered their agreement with various health-related pseudoscientific statements before and after receiving supporting and discrediting feedback from (a) experts (doctors), (b) peers, or (c) a random number generator. Our results suggest that when receiving feedback from experts (but not from peers or random feedback), the participants preferentially integrated supporting information relative to discrediting information about health-related pseudoscience. We discuss the implications of this biased belief updating pattern on health-related pseudoscientific research and suggest new strategies for intervention focused on increasing awareness, training, and consensus among healthcare practitioners.

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