The Viability of Using Rapid Judgments as a Method of Deception Detection

ABSTRACT

Rapid Judgments (RJs) are quick assessments based on indirect verbal and nonverbal cues that are known to be associated with deception. RJs are advantageous because they eliminate the need for expensive detection equipment and only require minimal training for coders with relatively accurate judgments. Results of testing on two different datasets showed that trained coders were reliably making RJs after watching both long and short interaction segments but their judgments were not more accurate than the expert interviewers. The RJs did not discriminate between truth and deception as hypothesized. This raises more questions about the conditions under which making RJs from verbal and nonverbal cues achieves accurate detection of veracity.

Acknowledgments

The authors would like to thank Daniel Bernard and Dariela Rodriguez for their assistance with the coding in this article. A previous version of this article was presented at the Hawaii International Conference for System Sciences in 2012.

Notes

^1. Although Vrij et al. (2004) use the term “rapid,” it does not imply that indirect judgments are necessarily faster than direct ones. We retain the same term for the technique as the originators. The RJ method is certainly faster than using tools like polygraph or systematic coding of nonverbal cues, but it might not be the fastest method available despite its name.

^2. It should be noted that different authors use the term “indirect” to mean different things. For example, Ten Brinke, Stimson, and Carney (2014) asked people to make direct truth-lie judgments and then asked them to associate photos of actors with words “untruthful,” “dishonest,” “invalid,” “deceitful” or “truthful,” “honest,” “valid,” “genuine” for their indirect measurement. Levine and Bond (2014) point out that these indirect judgments are no more accurate than the direct judgments. From our perspective, asking people to rate the honesty or truthfulness of the actor is still a direct measurement.

^3. The ICC is the correlation between one measurement on a target and another measurement obtained on that target and is used to establish a correlation between pairs of observations that do not have an obvious order (Fleiss, 1981). Shrout and Fleiss (1979) discuss six different versions of the ICC, most of which can be calculated using the reliability analysis function in SPSS. We used the one-way random version of the ICC with a 95% confidence interval and a test value of 0.