Abstract
Previous research has shown that in real-life situations people detect lies mostly from non-behavioral information (e.g., physical evidence, third-party information, confessions…) rather than from behavioral cues. Novotny et al. (J Nonverbal Behav 42:41–52, 2018. https://doi.org/10.1007/s10919-017-0263-2) argued that while lies are detected primarily from non-behavioral information, initial suspicion of a lie can be triggered primarily from behavioral cues. They conducted two studies and claimed support for their hypotheses. However, there are a number of problematic issues with Novotny et al.’s research and conclusions. We conducted analyses based on the frequencies and percentages they reported, and used meta-analytical techniques to combine their findings concerning discovered lies with those of previous research. The results show that lies are indeed detected from non-behavioral information more often than from behavioral cues. However, contrary to Novotny et al.’s assertions, suspicion is not triggered primarily from behavioral cues—rather, there is a trend in favor of non-behavioral information. Even so, behavioral cues play a bigger role in eliciting suspicion than in lie discovery.
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Notes
Behavioral cues are visible, vocal, and verbal potential cues to deception displayed by the liar at the time the lie is told [i.e., the kinds of cues typically examined by laboratory research on deception detection; see DePaulo et al. (2003)]. Non-behavioral cues involve information about the context (i.e., information that goes beyond the liar’s behavior during the specific deceptive exchange) that can contradict the liar’s statement, such as third-party information, specific knowledge of the detector, physical evidence, or the liars’ ultimate admission that the exchange was deceptive.
The McNemar tests were run in SPSS using Marta García-Granero’s macro, which is available, along with instructions on how to use it, at http://www.how2stats.net/2011/09/two-proportions-test-related-spss.html. The confidence intervals for the difference between proportions are based on a procedure described by Newcombe (1998). The Chi square correction used was the conservative Yates' correction.
Recall that, as mentioned earlier, in Study 1 Novotny et al. (2018) reported percentages of lies discovered from each type of clue (behavioral/non-behavioral), while in Study 2 they reported the percentage of clues of each type reported by the participants. Percentages of lies vs. of clues can differ, and therefore can yield slightly different outcomes when calculating OR and RD. This problem prevented us from meta-analytically combining the OR from both studies to have a better estimate of the true effect.
We are aware that for Novotny et al.’s Study 1 we did not use OR and RD the way it is normally used. To illustrate, medical research focuses on the proportion of participants in the control group who contract (a) and who do not contract (b) a disease, as well as on the proportion of participants in the treatment group who contract (c) and who do not contract (d) the same disease. Note that in the medical research case, as well as in Novotny et al.’s Study 2, a + b = 1, and c + d = 1. But this does not happen with Novotny et al.’s Study 1 data, as some lies could be detected from both behavioral and non-behavioral information. Specifically, for the current Study 1 calculations, a + b = 1.04, and c + d = 1.11. However, if the proportion of behavioral relative to non-behavioral clues is the same in both conditions, OR is still 1 and RD is 0. Also, the maximum possible range for RD is still − 1 to 1. Finally, the deviations from 1 are minute. Therefore, we do believe that OR and RD are still informative for Study 1.
As the current article was under review, a paper by Levine and Daiku (2018) was published where the authors examined, among other issues, how customs agents discovered a lie in the past. The answers were classified as “behavioral cues”, “communication content and evidence”, and “interaction/questioning.” While the two first categories are similar to the current “behavioral” and “non-behavioral” categories, several reasons prevented us from including Levine and Daiku’s data in the meta-analysis. First, Levine and Daiku’s “communication content and evidence” also included “logical consistency” (i.e., absence of verbal contradictions), which is definitely a behavioral cue. Second, in Levine and Daiku’s study the same response could be simultaneously coded as pertaining to both the “behavioral” and the “content and evidence” categories. Third, presumably customs agents reported on professional lies; note that we used the personal-context lies (rather than the professional-context lies) of Masip and Herrero’s (2015) police officers to keep the meta-analysis uniform in terms of the kind of lies considered. Still, in line with the findings of the current meta-analysis, Levine and Daiku’s participants reported more items pertaining to the “communication content and evidence” category (98%) than to the “behavioral cues” category (43%).
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Acknowledgements
The authors are grateful to Dr. Iris Blandón-Gitlin (California State University, Fullerton, USA) and Ms. Ana I. Jiménez (University of Salamanca, Spain) for their comments on a previous draft of this manuscript.
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Masip, J., Sánchez, N. How People Really Suspect Lies: A Re-examination of Novotny et al.’s (2018) Data. J Nonverbal Behav 43, 481–492 (2019). https://doi.org/10.1007/s10919-019-00309-y
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DOI: https://doi.org/10.1007/s10919-019-00309-y