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The power of the self: Anchoring information processing across contexts. | LitMetric

A stable self-representation has an intrinsically beneficial connotation for information processing: it allows the individual to flexibly adapt to different contexts, while prioritizing information that pertains to the own immediate survival. Indeed, many studies have shown how linking arbitrary information to physical or psychological aspects of the self leads to pervasive effects on our decision-making and even our perception. However, the evidence we have gained so far stems from isolated aspects of the self, and varying measures across studies and different levels of processing make results difficult to compare. The present study demonstrates that associating arbitrary information with the self rapidly leads to faster and more efficient processing of information, with stable performance benefits across different tasks (matching and categorization task) and stimulus domains. Focusing on specific processing levels, the findings first provide evidence regarding the involvement of self-relatedness in perception. Here, contrast processing interacted with self-relatedness, but only when complex stimuli were used. Second, they show that self-prioritization is flexible to decisional modulations, with processing benefits being adjusted to different social contexts. Third, the present data provides evidence that performance benefits toward newly self-associated, abstract information are equivalent to those resulting from long-term established self-associations with personally owned objects. The results highlight mechanistic differences between the prioritization of information linked to the self and information linked to close others. Overall, the present findings suggest that the self acts as a stable anchor in information processing, allowing us to filter information by its immediate relevance to facilitate optimal behavior. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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http://dx.doi.org/10.1037/xhp0001017DOI Listing

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