Estimating the effects of trait knowledge on social perception. Issue 5 (May 2022) - Wildman, Andrew; Ramsey, Richard
Research in social cognition has predominantly investigated perceptual and inferential processes separately; however, real-world social interactions usually involve integration between person inferences (e.g., generous, selfish) and the perception of physical appearance (e.g., thin, tall). Therefore, in the current work, we investigated the integration of different person-relevant signals, by estimating the extent to which bias in one social information processing system influences another. Following an initial stimulus-validation experiment (Experiment 1, N = 55), two further pre-registered experiments (Experiments 2, N = 55 and 3; N = 123) employed a priming paradigm to measure the effects of extraversion-diagnostic information on subsequent health and body-size judgements of a target body. The results were consistent across both priming experiments and supported our predictions: compared to trait-neutral control statements, extraversion-diagnostic statements increased judgements of health and decreased those of body size. As such, we show that trait-based knowledge does not only influence mappings towards similar types of person judgements, such as health judgements. Rather, even a brief re-configuration of trait-space alters mappings towards non-trait judgements, which are based on body size and shape. The results complement prior neuroimaging findings that showed functional interactions between the body-selective brain regions in the ventral visual stream and the theory of mind network when forming impressions of others. Therefore, we provide a functional signature of how distinct information processing units exchange signals and integrate information to form impressions. Overall, the current study underscores the value of behavioural work in complementing neuroscience research when investigating the role and properties of functional integration during impression formation. In addition, it stresses the potential limitations of an over-reliance on studying separate systems in isolation.