Friends of the Nonverbal Communication Blog, this week we present the paper “Detecting deception using comparable truth baselines” by Bogaard, G.; Meijer, E. H.; Vrij, A. and Nahari, G. (2022), in which authors carry out a couple of experiments to know how the use of true base lines affects deception detection. 

We have already seen on several occasions throughout the different messages how the human capacity to detect lies is quite poor. Both the skill of laymen and the skill of professionals do not usually exceed the levels of luck.

Among the possible reasons that would explain the deficiency of these skills is the idea that people pay too much attention to behavioral signals, such as aversion to gaze and body movements. The reality is that there is not as much relationship as it is believed between these signs and deception.

Research has also shown that, in order to improve truth-lie detection accuracy, the observers should focus primarily on the content of people’s statements, as this has shown to be a more promising technique.

However, even verbal lie detection tools have a significant error rate, and one potential source of this error rate is individual differences in the verbal behavior of the liar; as meta-analytic research has shown.

That is, whether observers are able to detect a lie depends largely on the qualities of someone’s lying skills.

For example, fantasy-prone people are better at formulating believable lies, and people with verbal skills get away with it more often because they tend to include more detail in their false stories.

This is consistent with the finding that good liars report that they rely heavily on verbal strategies when lying.

One way to include the individual and verbal differences of liars in a lie detection procedure is through the baseline. That is, using a statement that is known to be true, or part of a statement that is also true, to compare between it and the lie.

The idea is that people are telling the truth during small talks, and any difference in behavior between this and the part of the interview that deals with the important issue being investigated is taken as a signal to pay attention to. attention and as a possible indicator of deception.

The problem is that this comparison is confusing. The topics covered in small talk are different from the ones being researched, and depending on the topic and personal relevance, people may respond differently. In addition, what is at stake contrasts substantially.

For this reason, there is the so-called “comparable truth baseline” (CTB). This baseline is used to be considered comparable to the research topic.

Previous studies have thrown up the idea that liars whose lies are accompanied by truth include more details. That is, good liars calibrate their deceptive responses against truthful information. Therefore, two contradictory ideas appear. On the one hand, if liars calibrate the amount of detail they report in their lie based on a previous truthful response, a CTB could decrease the discriminability between the lie and the truth. However, if the liars cannot gauge their responses, the use of a CTB has the potential to improve the discrimination between lying and truth.

That is why, in two different experiments, two aspects are investigated: first, if providing a CTB influences the detail of a subsequent statement provided by the same person; and second, if using a CTB statement would improve lie detection ability thanks to verbal cues.

In the first experiment 171 people participated; in the second, 138. In them, the participants were basically assigned the role of telling the truth or lying according to certain conditions, a process that is more explained in the original article, and then passing their complete statement through a tool used to evaluate the credibility of the speech , which is Reality Monitoring.

The analysis showed the existence of an interesting verbal pattern: the objective statements (the main ones and references to the research topics) of the truth tellers tend to include more temporal and auditory details than their reference statement, or their CTB, while the liars’ results showed the opposite pattern.

In the first of the experiments, no evidence appeared that the use of a CTB improves the accuracy when detecting truths and lies.

In experiment 2, those who used the CTB became worse at truth detection, but just as accurate at lie detection, compared to those who did not use the CTB.

However, authors mention that their results should be interpreted with caution, because their support is weak and it seems premature to use them as a reference. Therefore, they encourage other researchers to continue delving into this topic, plus, they leave the door open for future related experiments.

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