Normative data for two tests of face matching under ecological conditions release_g4ahgme6tjfdfo27x7st4efwvm

by Lisa Stacchi, Eva Huguenin-Elie, Roberto Caldara, meike ramon

Released as a post by Center for Open Science.

2019  

Abstract

How do humans process unfamiliar faces, and how can we reliably identify individuals that are most proficient at it? Motivated by its relevance in applied contexts, much empirical work has sought to answer these questions. Controlled laboratory tests have been developed to understand the contribution of different variables and inter-individual differences. However, such face processing tests involving stimuli derived from ideal conditions, or manipulations and tasks that are not representative of real life, may lack ecological validity. This crucial consideration is often overlooked when laboratory tests are used to predict real-life proficiency. The present study followed the rationale that traditionally used controlled tests should be paired with more realistic, and ecologically meaningful ones – in terms of the stimuli and tasks performed. Testing large and heterogenous samples, we standardized two underused tests of facial identity matching: the Yearbook Test (YBT; Bruck et al., 1991) and the Face Identity Card Sorting Test (FICST; Jenkins et al., 2011). These procedurally simple tests mimic real-life challenges in face perception, as they assess unfamiliar facial identity matching across superficial image changes, or substantial age-related change in appearance. Beyond providing normative data, we describe how performance measured by these tests relates to that observed on more commonly used tests of face recognition (CFMT+; Russell et al., 2009) and perception (EFCT; PICT; White et al., 2015). Our findings suggest that (i) the YBT and FICST are easy-to-use, preferable alternatives to pairwise face matching tasks, which are prone to speed-accuracy trade-offs; (ii) challenging and ecologically valid tests should complement highly controlled measures when aiming to identify individuals with superior face processing abilities for real-life purposes.
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