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17-10-2016 | Original Article | Uitgave 6/2017

Psychological Research 6/2017

Orthogonal-compatibility effects confound automatic imitation: implications for measuring self–other distinction

Tijdschrift:
Psychological Research > Uitgave 6/2017
Auteurs:
Daniel Joel Shaw, Kristína Czekóová, Michaela Porubanová
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Electronic supplementary material

The online version of this article (doi:10.​1007/​s00426-016-0814-x) contains supplementary material, which is available to authorized users.

Abstract

Accurate distinction between self and other representations is fundamental to a range of social cognitive capacities, and understanding individual differences in this ability is an important aim for psychological research. This demands accurate measures of self–other distinction (SOD). The present study examined an experimental paradigm employed frequently to measure SOD in the action domain; specifically, we evaluated the rotated finger-action stimuli used increasingly to measure automatic imitation (AI). To assess the suitability of these stimuli, we compared AI elicited by different action stimuli to the performance on a perspective-taking task believed to measure SOD in the perception domain. In two separate experiments we reveal three important findings: firstly, we demonstrate a strong confounding influence of orthogonal-compatibility effects on AI elicited by certain rotated stimuli. Second, we demonstrate the potential for this confounding influence to mask important relationships between AI and other measures of SOD; we observed a relationship between AI and perspective-taking performance only when the former was measured in isolation of orthogonality compatibility. Thirdly, we observed a relationship between these two performance measures only in a sub-group of individuals exhibiting a pure form of AI. Furthermore, this relationship revealed a self-bias in SOD—reduced AI was associated with increased egocentric misattributions in perspective taking. Together, our findings identify an important methodological consideration for measures of AI and extend previous research by showing an egocentric style of SOD across action and perception domains.

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