A great deal of popular discussion of how to detect deception rests on specific, isolated factors like eye contract, but the reality is a bit more complex.
This is the case that Humintell’s Drs. David Matsumoto and Hyisung Hwang made in a 2017 study published in the Journal of Police and Criminal Psychology. In this experimental analysis, they had participants engage in a simulated investigative interview which, after being recorded, was analyzed to see which deceptive nonverbal behaviors were exhibited and, most importantly, in what combinations.
Importantly, while many previous studies have found that certain nonverbal behaviors are reliable indicators of deception, these findings have often been difficult to replicate. These studies have focused on vocal fluctuations, body language, and gestures, all of which do demonstrate underlying emotions.
However, Drs. Matsumoto and Hwang emphasize that, because of the complex emotions involved in deception, analyzing just one behavior at a time seems problematic. This is why, in the current study, they sought to see whether looking at clusters of behaviors may help solve this puzzle.
In order to do this, they recruited a series of participants who were all asked to engage in a mock crime simulation. These participants were given the opportunity to “steal” a $100 check, with some told to do so and some to refrain. Both groups were then assigned to mock interviews where they were either told to lie or confess.
With this premise set up, the exciting analysis work began. Each interview was recorded and then analyzed, frame by frame, with machine-learning informed algorithms which sought to categorize individual frames based on certain emotions, including many basic emotions like anger, disgust, fear, happiness, etc.
This allowed the researchers to calculate exactly which emotions tended to be the most common during the interview. Then, they hand coded a series of nonverbal behaviors, including head shakes, nods, and shoulder shrugs. This analysis was then combined with sophisticated assessments of vocal pitch and volume, helping create a comprehensive account of the subtle behaviors involved in the interview process.
When comparing these behaviors to whether or not the interviewee was lying, Drs. Matsumoto and Hwang found that it was clusters of non-verbal behaviors that most reliably predicted deception. Liars tended to have fewer head nods and greater changes in vocal pitch, though with a lower average.
Importantly, the types of questions, be they open-ended or more closed had significant impacts. Liars tended to have even lower pitches during open-ended questions, for example.
These findings have significant ramifications for anybody attempting to detect deception. While many of us are told to focus on individual behaviors, like eye contact or closed postures, these alone cannot fully explain the situation.
Instead, deception seems based on these clusters of behaviors which can be even more difficult to determine. This is definitely on reason why Humintell offers advanced deception detection classes which can be helpful for anyone, but especially any of you who make it your business of conducting lie detection interviews.