Taylor Swift does not boost face recognition in reaction time-based Concealed Information Test: investigating target-familiarity effects
-
Published:2024-09-04
Issue:
Volume:
Page:
-
ISSN:0340-0727
-
Container-title:Psychological Research
-
language:en
-
Short-container-title:Psychological Research
Author:
Kohn Lukic Laure Z., Möck Nele, Verschuere BrunoORCID, Sauerland MelanieORCID
Abstract
AbstractEyewitness identifications from lineups are prone to error. More indirect identification procedures, such as the reaction-time based Concealed Information Test (RT-CIT) could be a viable alternative to lineups. The RT-CIT uses response times to assess facial familiarity. Theory and initial evidence with autobiographical stimuli suggests that the accuracy of RT-CIT can be augmented when participants’ reliance on familiarity-based responding increases. We tested this assumption in two pre-registered experiments with 173 participants. Participants witnessed a mock crime. In the subsequent RT-CIT protocol, participants reacted to probe faces from the mock crime video, to irrelevant faces, and to target faces that required a unique response. Targets were either unknown people or were well-known celebrities (e.g., Taylor Swift). As expected, reaction times were longer to probes than to irrelevants in all conditions, indicating a CIT effect. Contrasting our pre-registered predictions, the CIT effect was not larger in the familiar condition (Experiment 1: unfamiliar targets: d = 0.77 vs. celebrity targets: d = 0.24; Experiment 2: unfamiliar targets: d = 1.09 vs. celebrity targets: d = 0.79). This suggests that familiar targets did not increase the validity of the RT-CIT in diagnosing concealed face recognition. A potential lack of saliency of the familiar targets might explain these unexpected findings. Of note, we did find medium to large effect sizes overall, speaking to the potential of diagnosing face recognition with the RT-CIT.
Publisher
Springer Science and Business Media LLC
Reference31 articles.
1. Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T. H., Huber, J., Johannesson, M., Kirchler, M., Nave, G., Nosek, B. A., Pfeiffer, T., Altmejd, A., Buttrick, N., Chan, T., Chen, Y., Forsell, E., Gampa, A., Heikensten, E., Hummer, L., Imai, T., & Wu, H. (2018). Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour, 2(9), 637–644. https://doi.org/10.1038/s41562-018-0399-z. 2. Campbell, J. I. D., & Thompson, V. A. (2012). MorePower 6.0 for ANOVA with relational confidence intervals and bayesian analysis. Behavior Research, 4, 1255–1265. https://doi.org/10.3758/s13428-012-0186-0. 3. Deffenbacher, K. A., Bornstein, B. H., McGorty, E. K., & Penrod, S. D. (2008). Forgetting the once-seen face: Estimating the strength of an eyewitness’s memory representation. Journal of Experimental Psychology: Applied, 14(2), 139–150. https://doi.org/10.1037/1076-898X.14.2.139. 4. Douglass, A. B., & Steblay, N. (2006). Memory distortion in eyewitnesses: A meta-analysis of the post-identification feedback effect. Applied Cognitive Psychology, 20(7), 859–869. https://doi.org/10.1002/acp.1237. 5. Faul, F., Erdfelder, E., Lang, A., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146.
|
|