Sitting in Judgment: The Working Lives of Judges

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For the effect of posture on microexpression recognition, the METT scores (%) were to be analyzed using a one-way, between-subjects ANCOVA, with Posture (Open or Closed) as the between-subjects factor and trait Empathy as the covariate. The relationship between deception detection accuracy (overall, lies, and truth) and facial expression recognition are assessed using non-parametric (Spearman’s rho) correlations. Dimberg, U.; Andréasson, P.; Thunberg, M. Emotional Empathy and Facial Reactions to Facial Expressions. J. Psychophysiol. 2011, 25, 26–31. [ Google Scholar] [ CrossRef]

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Zloteanu, M.; Krumhuber, E.G.; Richardson, D.C. Acting Surprised: Comparing Perceptions of Different Dynamic Deliberate Expressions. J. Nonverbal. Behav. 2021, 45, 169–185. [ Google Scholar] [ CrossRef] Bond, C.F.; DePaulo, B.M. Accuracy of Deception Judgments. Personal. Soc. Psychol. Rev. 2006, 10, 214–234. [ Google Scholar] [ CrossRef] The significance threshold for all analyses was set at p< 0.05. The assumptions for the ANCOVAs were verified (i.e., the normality assumption, as assessed by Shapiro–Wilk’s test p< 0.05 for all variables, and the homogeneity of variance assumption was met, as assessed by Levene’s test p< 0.05 for all comparisons conducted).

Facial recognition ability was assessed using the Micro Expression Training Tool (METT; [ 50]). The METT was developed to train the recognition of microexpressions of the seven basic emotions: happiness, anger, sadness, disgust, fear, surprise, and contempt. The test module consists of 14 color portrait photographs of facial expressions of emotions (Japanese and Caucasians), two for each emotion. Users view a neutral expression followed by an emotional expression for 1/25 th of a second, to which they respond with an emotion label from the list of seven displayed on the screen. The maximum test score is 100%. The METT has been used in past studies (e.g., [ 40, 41, 42]), and is based on the Brief Affect Recognition Test, which has good validity and reliability [ 51].

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Concerning gazing behavior, adopting an open posture resulted in less attention being given to the nonverbal behavior of senders, contrasting what the literature would predict. It was found that judges placed in an open posture spent less time gazing at senders. Specifically, they focused less on the hands of senders. Potentially, open posture judges were faster and/or more efficient at extracting information from nonverbal signals and thus required less time looking at senders, or they relied less on nonverbal information for their veracity judgments. Vrij, A. Detecting Lies and Deceit: Pitfalls and Opportunities, 2nd ed.; Wiley Series in the Psychology of Crime, Policing and Law; Wiley: Chichester, UK, 2008; ISBN 978-0-470-51624-9. [ Google Scholar] People are poor at detecting if others are lying or telling the truth, usually being only slightly better than predicted by chance [ 1, 2]. They are also overconfident in their judgments [ 3] and tend to assume most statements people make are honest, commonly referred to as the truth bias [ 4]. The majority of past research attempting to improve deception detection accuracy has focused either on differences between judges (e.g., experience or training; [ 5, 6]) or between senders (e.g., demeanor or physical characteristics; [ 7, 8]). Here, we raise the possibility that simply changing the judge’s body posture might affect their ability to perceive and interpret behavioral information from a sender. Faul, F.; Erdfelder, E.; Lang, A.-G.; Buchner, A. G* Power 3: A Flexible Statistical Power Analysis Program for the Social, Behavioral, and Biomedical Sciences. Behav. Res. Methods 2007, 39, 175–191. [ Google Scholar] [ CrossRef]

We used both high-stakes and low-stakes lie videos in this study for two reasons. Stakes are the rewards to the liar for escaping detection and/or the punishment that they would receive for being caught. Stakes make controlling one’s behavior channels more difficult [ 35] and increase the likelihood of displaying unintended behavioral cues associated with lying, both in quantity and intensity [ 36, 65], which can make deception detection easier [ 66, 67]. If the posture manipulation affects the attention judges give to behavioral cues a difference in accuracy should be more pronounced for the high-stake lies. The second benefit is uncovering the stability and generalizability of the posture effect on different lie scenarios. It should be noted that the role of stakes in lie detection is a debated topic. The meta-analysis by DePaulo and colleagues [ 33] reported an effect of motivation (a close proxy to stakes) on the detectability of deception, however, the more recent meta-analysis by Hartwig and Bond [ 34] failed to replicate this finding. Ekman, P. Microexpression Training Tool, Subtle Expression Training Tool; A Human Face: Salt Lake City, UT, USA, 2002. [ Google Scholar] Hartwig, M.; Bond, C.F. Lie Detection from Multiple Cues: A Meta-Analysis. Appl. Cogn. Psychol. 2014, 28, 661–676. [ Google Scholar] [ CrossRef] Jordan, S.; Brimbal, L.; Wallace, D.B.; Kassin, S.M.; Hartwig, M.; Street, C.N.H. A Test of the Micro-Expressions Training Tool: Does It Improve Lie Detection? J. Investig. Psychol. Offender Profiling 2019, 16, 222–235. [ Google Scholar] [ CrossRef]Wilkes, C.; Kydd, R.; Sagar, M.; Broadbent, E. Upright Posture Improves Affect and Fatigue in People with Depressive Symptoms. J. Behav. Ther. Exp. Psychiatry 2017, 54, 143–149. [ Google Scholar] [ CrossRef] Hall, J.A.; Gunnery, S.D.; Horgan, T.G. Gender differences in interpersonal accuracy. In The Social Psychology of Perceiving Others Accurately; Hall, J.A., Schmid Mast, M., West, T.V., Eds.; Cambridge University Press: Cambridge, UK, 2016; pp. 309–327. ISBN 978-1-107-49907-2. [ Google Scholar]

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