Running head: INTUITIVELY DETECTING DECEPTION Does intuition improve deception detection accuracy?
Chris König
Tilburg University
Supervisor: Anna van ‘t Veer
1 INTUITIVELY DETECTING DECEPTION 2 Abstract
Literature on deception detection shows that it is difficult for people to correctly
detect deception. In this paper we argue that detecting deception based on intuition
will increase the accuracy of detection. Two studies were conducted to examine
whether assessing felt emotions after seeing a liar or a truth-teller would help
participants to more accurately detect deception. Videos were shown containing either
lying or truth-telling people and a questionnaire about emotions was conducted. Next,
a veracity question was asked about the truthfulness of the subjects covered in the
videos. Both studies used a single factor design with three conditions each. The first
two conditions differed regarding the order of the questionnaire and the veracity
question; the third filler condition made use of a questionnaire, non-related to
emotions. In study 2, we used longer videos in order to give any effect on the
emotions of the observers of a lie a fair chance. No difference was found with regard
to the different conditions, indicating that emotional assessment does not increase
accuracy in detecting deception. In both studies, however, we measured the time
participants took to answer the veracity question, as indication of whether they were
responding in an automatic or more reflective way, and it appeared that participants
who used less time for making a decision were more accurate in detecting deception.
INTUITIVELY DETECTING DECEPTION 3 Does intuition improve deception detection accuracy?
Often employees get hired, because they seem skilled enough during their job
interview. Previous research has shown that people often tell lies and clearly some of
them do not meet the requirements, although their job interview suggested otherwise.
To prevent this scenario from happening it would have been useful for the interviewer
to know whether the applicant was telling the truth, but detecting deception is a rather
complex issue. This paper investigates whether awareness of your own emotions
helps to correctly detect deception and if the response time influences the accuracy.
When people need to leave an impression, for example during a job interview,
they are not strict in labeling their behavior as deception and they even think in those
situations that some kind of deception is allowable (Leary & Kowalski, 1990). A job
interview setting is a good example of a situation where people have to detect
deception, either directly or via a negative feeling that the liar gives off. Feldman,
Forrest and Happ (2002) found that applicants were more likely to tell lies when they
had to appear likable or competent, instead of when they just had to get to know each
other. In their experiment participants were made to believe that they applied for a job
and were doing a job interview. Over 60% of the participants admitted afterwards that
they told at least one lie to their partner during the experiment. Also Weiss and
Feldman (2006) found that this deception happens because people try to meet the job
requirements: the more technical the requirements, the more likely the deception.
People just try to present themselves in a better way and deceit happens easily.
Although people are not that strict with labeling their own behavior deceitful, it is
important for us to know how to label deception.
Different definitions regarding deception are spoken of in the literature. We
will use a definition named by DePaulo et al. (2003), stating: ‘Deception is a
INTUITIVELY DETECTING DECEPTION 4 deliberate attempt to mislead others’. This definition captures different aspects of
deception, which makes it more understandable and therefore better applicable. The
terms deceiving and lying will be used interchangeable in this paper, for it can be
assumed that they represent the same issue (DePaulo et al., 2003).
Detecting deception seems to be in difficult, in general. On average, people
are no better than chance at detecting lies (Bond & DePaulo, 2006). Research from
O’Sullivan and Ekman (2003) suggests, however, that it is possible for some people
to score higher on detection accuracy than others; they called these people ‘wizards of
deception detection’. These people –including CIA and FBI agents and lawyers–
scored significantly higher than chance on the test. Four years later Bond and Uysal
(2007) expressed their doubts regarding ‘lie detection wizards’ in a commentary on
Sullivan and Ekman (2003) in which they analyze that chance possibly explains the
results that Sullivan and Ekman attributed to the ‘wizards’. Thus, claims about it seem
to remain unfounded. For we can assume that it is genuinely difficult to detect
deception we will explore possible explanations why people find it difficult.
According to Vrij (2008) there are two different explanations for why people
are bad at detecting lies. The first explanation that he suggests, is that people often
base their deception detection on invalid cues. Hartwig and Bond Jr. (2011)
investigated these cues and found several ones like looking away when talking to
someone, or shifting your weight continuously when sitting on a chair. The second
explanation that he mentions, is that behavioral differences between people who tell
the truth or people who lie, are very small. In other words, it is hard to notice cues that
are not even present. After the study by Vrij (2008) a meta-analysis was conducted by
Hartwig and Bond Jr. (2011) and it was found that people usually do not rely on
invalid cues, but that the limitations in deception detection are mainly caused by weak
INTUITIVELY DETECTING DECEPTION 5 cues, as the second explanation of Vrij (2008) suggested. These explanations suggest
that relying on direct detection is difficult.
It seems, however, that there is a way of assessing deception detection that
does enable people to more accurately differentiate between truths and lies. People are
more aware of truths and lies when indirectly being aware of the issue and some
research has shown that an indirect detection method might improve the accuracy of
detection. These results are supported by research of Vrij, Edward and Bull (2001).
Their research shows that police officers were better able to detect deception when
indirect detection methods were being used. When the police officers tried to
distinguish lies by directly answering the question: ‘did the participant lie?’ the
detection failed, but when they were asked to indicate lies according to secondary
features – ‘does the person think hard?’ – the detection accuracy improved
significantly. Evidence that indirectly detecting deception improves the accuracy of
deception is also found in a study of ten Brinke, Stimson and Carney (2014);
participants were asked whether some deception-related and truth-related concepts
like ‘dishonest’, ‘genuine’ and ‘truthful’ better suited the faces of people who told
truths in videos, or who told lies. They found that viewing a liar or a truth teller
automatically activates the corresponding concept, and therefore makes the indirect
judgment more accurate.
The judgments in the above study were not based on rational arguments, but
rather made subconscious. This indicates that the use of intuition influences detecting
deception. Some researchers even argue that intuitive notions about detection cues are
considerably accurate. For example, explicit cues about deception are inaccurate and
mostly based on wrong stereotypes, but intuitively people seem to be on the same line
with the characteristics of deception and rarely rely on unrelated cues (Hartwig &
INTUITIVELY DETECTING DECEPTION 6 Bond Jr., 2011). On top of this, Albrechtsen, Meissner and Susa (2009) examined
whether participants who are engaged in a secondary task during deception detection,
were more accurate than participants who did not have to engage in a secondary task,
about whether inmates provided true or false confession statements. When one makes
a decision while a secondary task is performed, the decision is made less conscious
and therefore assumingly intuitive. In another study Albrechtsen et al. (2009) ran,
participants saw only short ‘slices’ of 5 seconds of every video, in order to provoke a
more intuitive decision. Their findings in both studies indicated that intuitive
processing significantly improved the detection accuracy. It seems that people might
be more accurate in detecting deception on intuitive bases, than when they
consciously are looking for cues in order to detect possible deception.
In the current study we argue that awareness of ones emotions elicits a more
intuitive way of detecting deception. According to Albrechtsen et al. (2009) intuitive
processing is a more affective, spontaneous, unconscious way of processing, while
deliberate processing is conscious and takes more time. Elaborating on the affective
part of intuitive processing, it seems logical that emotions are an important part in
intuitive processing. According to DePaulo et al. (2003) liars come across as tense
and make a negative impression in comparison with people that tell the truth. We
argue that, when confronted with a liar that leaves a negative impression, it is possible
that you feel more distressed yourself. When this distress causes a more intuitive way
of deception detection, it might indeed improve the accuracy on the detection.
Therefore, based on the meta-analyses Hartwig and Bond Jr. (2011) conducted
and the study of Albrechtsen et al. (2009), we want to explore the proposition that
intuitively detecting deception through awareness of ones own emotions can improve
the accuracy of detection. Here we do so by using a different perspective next to the
INTUITIVELY DETECTING DECEPTION 7 secondary task method of Albrechtsen et al. (2009) We expect that by being more
aware of your own emotions, the negative impression a liar gives off will be detected
better and thus lies will be detected more accurately.
Besides awareness of ones emotion, we argue that response time in making
decisions indicates use of intuitive processing. Bolte (2003) found that people who
made decisions based on intuition, spent less time in making a correct decision, than
people who made an analytical decision. This indicates that intuitive processing takes
a shorter time to process than deliberate processing. In a study of Tinghög, et al.
(2013) time pressure was used in order to elicit intuitive processing, which suggests
that in a situation with less available time intuition is used more often. Kahneman
(2011) describes two cognitive systems of thinking, referring to system 1 as an
intuitive system, working automatically without much effort, for making quick
judgments. System 2 thinking refers to a more deliberate, slower method of thinking.
We therefore assume that less time spent on making a decision involves intuitive
processing.
Two studies will be conducted. In both studies we use videos containing
people telling the truth or a lie. A questionnaire about emotions was used to
encourage participants for a more intuitive processing style. In contrast with the
emotion questionnaire we used a questionnaire about personality traits in a second
condition for both studies, in order to make sure that intuitive processing is caused by
the questionnaire about emotions. The second study was a replication of the first
study, except for the content of the videos, which contained larger differences
between the truth and deception scenarios. To test our hypothesis that intuitive
processing achieves a higher accuracy regarding deception detection, we measured
response time for making these decisions.
INTUITIVELY DETECTING DECEPTION 8 Study 1
Method
Participants
In the current study 93 participants took part. One participant was excluded,
based on remarks made by the experiment leaders in the lab about internet failure
(“data invalid due to Qualtrics error”) leaving 92 participants (Mage = 20.66, SDage =
2.11, 77.2% female). Participants took part in our study voluntarily and they took part
in different studies in the same hour, for which they received 8 euros. Informed
consent was obtained from all the participants.
Design
The current study used a single factor between-subjects design and
participants were assigned randomly to one of three conditions. The conditions
differed in the order of questionnaires showed to the participants. In the first
condition, an emotion questionnaire was filled out, than a veracity question was asked
and afterwards a personality questionnaire. In the second condition the veracity
question was asked, after which the emotion questionnaire and the personality
questionnaire were filled out. In the third condition first the personality questionnaire
was filled out, after which the veracity question was asked. The emotion
questionnaire was filled out last.
Video materials
In the videos used, a person told a story that either contained honest or
dishonest statements. The target persons were asked to tell about three different
subjects: their studies, their part-time job and an extra-curricular experience. During
the first recording they were asked to tell the truth for each single subject. The second
time we recorded the target persons, we let them lie about the third subject. The third
INTUITIVELY DETECTING DECEPTION 9 subject was chosen, because the participants in our study would remember this the
best after watching a video; it was the most recent subject. In order to motivate the
target person, 5 euro’s were granted for being part of the video. Besides that, a
confederate pretended that the videos would be used as promotion material for a high
school. The confederate was used in order to let the target persons feel more pressure
to do as told and therefore record more believable videos. For the second video
recorded with every candidate, the deception version, they received another 5 euros,
in order to keep them motivated.
Procedure
Participants were placed behind a computer and filled out the questionnaire
made in Qualtrics. They were shown a total of four videos with a length varying
between 137 and 225 seconds each. The videos were split into two different sets, each
set consisting of two lying men and two lying women, to ensure that participants
didn’t see the same person in two different videos. Within the sets the videos were
shown in random order. The participants were not told the amount of videos they
would watch, to minimize the risk of them thinking half of the videos would contain a
lie.
Participants were randomly divided among three conditions. In all conditions
the participants watched four videos. In the first condition an emotion questionnaire
was conducted, right after the video was shown, which contained eight questions and
was used to make participants more aware of their emotions. Next, a question was
asked whether the person in the video was telling the truth (‘veracity judgment’).
Lastly, a modified version of the Ten-Item Personality Inventory (TIPI) was used.
Both the TIPI and emotion questionnaire were rated on a 7-point scale. In the second
condition after watching a video the veracity question was asked. After that the
INTUITIVELY DETECTING DECEPTION 10 emotion questionnaire and the TIPI were conducted. In the third condition
participants answered the modified TIPI first and then judged veracity. In this
condition, participants answered the same emotion items that participants in condition
1 answered right after the video, in order to keep the amount of questions in all
conditions equal. We used the third condition to ensure that any observed effects were
not caused by participants judging veracity either right after the videos or after the
eight emotion questions. We made use of a modified version of the TIPI, because the
emotion questionnaire contained eight questions. In order to cancel out unwanted
differences between conditions, eight questions were used for the TIPI as well.
Results
A paired sample t-test was conducted between truth and lie videos, regarding
the positive and negative emotions felt after seeing them, across all conditions. The
positive emotions after truth (M = 60.60, SD = 16.62) and lie (M = 61.46, SD = 15.83)
didn’t show any significant changes with t(91) = -1.05, p = .30. The negative
emotions after truth (M = 27.98, SD = 16.67) and lie (M = 26.59, SD = 15.42) did not
show significant results either with t(91) = 1.260, p = .21.
In order to achieve a score on accuracy in deception detection per participant,
we calculated a total percentage of correctly detected veracity of the target person out
of the four videos shown (e.g., 3 videos correct = 75%). We used this ‘veracity score’
for the following tests. To investigate whether participants in one of the three
conditions were better at detecting lies we ran a one-way ANOVA on the veracity
score with the three different conditions as a predictor. The conditions did not have a
significant effect, F(2, 89) = 0.91, p = .41, meaning there were no differences between
the emotion condition (M = 0.53, SD = 0.240), the veracity condition (M = 0.57, SD =
0.26) and the filler/personality condition (M = 0.49, SD = 0.19). In order to examine
INTUITIVELY DETECTING DECEPTION 11 this further, a T-test was run for every condition to investigate whether the score on
veracity had a higher accuracy than by chance (50%). For the emotion condition no
significant difference was found, (M = 0.53, SD = 0.24) t(29) = .057, p = .57, CL
effect size .15, The CL effect size indicates the chance that someone scores higher
than chance, is 15%. For the veracity condition also no significant difference was
found (M = 0.57, SD = 0.26) t(31) = 1.56, p = .13, CL effect size .14. Lastly, for the
filler condition no significant difference was found (M = 0.49, SD = 0.19), t(29) = 0.24, p = .81, CL effect size -.6. This suggests that awareness of emotions vs. no
awareness does not have an effect on the ability to detect deception.
A paired sample t-test was conducted for the amount of correctly detected lies
vs. the amount of correctly detected truths. There was a significant difference in the
scores for correctly detected lies (M = 40.32, SD = 37.78) and correctly detected
truths (M = 65.05, SD = 32.79); t(92) = -4.46, p < .001, with a CL effect size of .68.
In other words, participants had 40.3% of the lies correctly detected and 65.1% of the
truths. These results seem to suggest that people have the tendency to detect truths
better than lies, but this could also be due to participants indicating that something is a
truth more often than a lie, the so-called truth-bias. As Vrij and Baxter (1999) found
the accuracy at detecting truths is usually higher than the accuracy at detecting lies. In
the current study in 62.1% of the veracity decisions participants indicated it was a
truth, regardless of the fact it was a correct truth.
Correlations were run between the time it took to choose whether a movie
contained a truth or lie, and the amount of correctly detected truths and lies. There
was a significant negative correlation between the amount of correctly detected truths
(M= 1.30, SD = 0.66) and the time it took to make this decision (M = 8.22, SD =
5.86), r = -.23, p = .029 with a CL effect size of .874. This means that those
INTUITIVELY DETECTING DECEPTION 12 participants who took less time were more often correct than those participants who
took longer for their veracity judgment.
Discussion
Study 1 showed a significant negative correlation between the time it took to
decide whether there was a truth and whether this decision was correct, in other
words: the shorter participants took for their decision, the more veracity decisions
were correct; this result was not found for making a correct decision regarding a lie.
However, we did not observe a difference in emotions felt by participants after
watching a target person. This might be due to the lack of intensity in the emotion
questionnaire, not causing participants to be more aware of their emotions. Next, no
effect on lie detection was found considering the different conditions regarding
emotional awareness versus no emotional awareness.
It is possible that the duration of the videos was too short to achieve any
difference in emotional state. We thus set out to examine this in our second study by
changing the contents of the videos used to show the participants, by making the lies
and truths in the videos longer, instead of limiting it to only the last part of the video.
Study 2
Method
Participants
In this second study 89 participants took part. Four (4.5%) of the participants
were excluded, based on remarks made by the experiment leaders in the lab (one
knew the people that acted in the movies, one was in a hurry and tried to leave earlier,
one didn’t use headset, one used mobile phone during experiment) leaving 85
participants (Mage = 20.88, SDage = 2.44, 71.8% female). Again, informed consent was
obtained from all the participants.
INTUITIVELY DETECTING DECEPTION 13 Design
The design of this second study is the same as in the first study: A single
factor between-subjects design with three conditions to which the participants are
assigned randomly.
Video materials
In this study other videos have been used. During the making of these videos,
target persons had to tell about their personality, in other words, they gave an
impression of themselves. They were told that another participant, a confederate, had
to judge in which movie they told the truth and in which movie they were lying. The
confederate was there to create a more serious environment in order to create movies
that were more realistic. In these videos, in contrast with study 1, the videos contained
truths or lies for the full length of the video.
Procedure
The procedure of our second study is the same as the first study. The
conditions remain the same; except for the fact that other videos are used, as
described above.
Results
As in study 1, a paired sample t-test was conducted between videos containing
truth and videos containing lies, regarding the positive and negative emotions felt
after seeing them. The positive emotions after a truth video (M = 63.25, SD = 14.50)
and a lie video (M = 61.99, SD = 16.23) were not significantly different with t(84) =
1.36, p = .18. No significant results were found for negative emotions after truth (M =
25.89, SD = 17.43) and lie (M = 25.32, SD = 16.22); t(84) = 0.54, p = .59.
A one-way ANOVA was conducted on the veracity score, with the three
different conditions (emotion, veracity, filler) as predictor, F(2, 82) = 1.35, p = 0.26.
INTUITIVELY DETECTING DECEPTION 14 Next, a one-sample t-test was performed for all conditions. The emotion condition did
not show any significant result for veracity (M = 0.51, SD = 0.21), t(29) = 0.22, p =
.83. The veracity condition did not show any significant result for veracity (M = 0.57,
SD = 0.28), t(26) = 1.35, p = 0.19. Lastly, in the filler condition we did find a
significance difference between the veracity score (M = 0.61, SD = 0.20) and chance,
t(27) = 2.87, p = .01, CL effect size .71, which means that in this filler condition
people were supposedly better than chance at detecting lies. These results suggest that
the awareness of emotions, as seen in the first two conditions, do not have an effect
on the ability to detect deception.
A paired sample t-test was conducted for the amount of correctly detected lies
versus the amount of correctly detected truths. There was a significant difference in
the scores for correctly detected lies (M = 0.81, SD = 0.70), which is 40%, and
correctly detected truths (M = 1.44, SD = 0.63), which is 72%; t(84) = -6.13, p < 0.01,
with a CL effect size of .75, which adds to the suggestion made in the previous study
regarding a truth-bias that people tend to correctly detect more truths than lies.
Again correlations were run for the time people took to determine a lie or truth
versus the amount of correctly determined lies and truths; between the time it took to
determine a truth (M = 7.95, SD = 4.25) and whether the truth was correct (M = 1.42,
SD = 0.64) there was no significant correlation r = -.13, p = .23. Between the time it
took to determine a lie (M = 7.31, SD = 3.04) and whether the lie was correctly
detected (M = 0.83, SD = 0.71) there was no significant result r = .10, p = .34.
Discussion
In the second study other videos were used with longer lies and truths. No
significant results were found regarding the emotions felt after watching a video. We
did find that participants scored higher than chance at detection accuracy in the filler
INTUITIVELY DETECTING DECEPTION 15 condition, which will be discussed later. Another finding was that people were again
better at detecting truths, than at detecting lies. A meta-analysis can be useful to
combine the findings from both studies and increase their power.
Meta-analysis
Both studies did not show significant results regarding the main question
whether intuitively detecting deception through awareness of ones own emotions can
improve the accuracy of detection. To enhance the power of finding an effect if an
effect truly exists, it is useful to conduct a meta-analysis of both studies.
We combined the data of study 1 and study 2 and with this combined data a
correlation has been run for the time it took to detect a truth (M = 7.97, SD = 4.94)
and detect it correctly (M = 1.37, SD = 0.64), resulting in a significant negative
correlation, r(177) = -.20, p = .01. Also correlations were run for the time it took to
detect a lie (M = 7.66, SD = 3.64) and detect it correctly (M = 0.81, SD = 0.73),
resulting in a significant correlation, r(177) = .05, p = .49.
A paired sample t-test was conducted with the combined data between videos
containing truth and videos containing lies, regarding the positive and negative
emotions felt after seeing them. The positive emotions after a truth video (M = 61.51,
SD = 15.90) and a lie video (M = 61.35, SD = 16.04) were not significantly different
with t(181) = 0.27, p = .79. No significant results were found for negative emotions
after truth (M = 27.13, SD = 17.00) and lie (M = 26.17, SD = 15.79); t(181) = 1.27, p
= .21. If we combine the effect sizes d from study 1 and study 2, namely for both the
positive emotions after truths and lies for study 1 (d = 0.05) and study 2 (d = 0,08)
and negative emotions after truth and lies in study 1 (d = 0.09) and study 2 (d = 0,03),
this results in an overall effect size of d = 0,07 for the positive emotions and a overall
effect size of d = 0,06 for the negative emotions. Based on the standard interpretation
INTUITIVELY DETECTING DECEPTION 16 offered by Cohen, the effect sizes are small and thus a difference between emotions
after seeing a truth or a lie is not proven yet.
On the veracity score a one-way ANOVA was conducted for all the
conditions, based on the combined data set. With F(2, 174) = .85, p = .43 no
significant result was found between the conditions. Again, a one-sample t-test was
performed between the veracity score and chance for all conditions. The emotion
condition did not show any significant result for veracity (M = 0.52, SD = 0.22), t(59)
= 0.57, p = .57. The veracity did show a significant result between veracity (M = 0.57,
SD = 0.26) and chance, t(60) = 2.07, p = .04, indicating that people that directly
answered the veracity question after watching a video, were more accurate on
correctly answering this question. Lastly, in the filler condition we did find a
significance difference between the veracity score (M = 0.55, SD = 0.21) and chance,
t(60) = 1.66, p = .10,
Lastly, a paired sample T-test was conducted on the amount of correctly
detected truths (M = 1.37, SD = 0.64) in comparison with the amount of correctly
detected lies (M = 0.81, SD = 0.73); t(176) = -7.29, p < .01 with an CL effect size of
.66. Truths were significantly detected correctly more often, as was also found in both
studies separately.
General Discussion
Previous research has shown that people are often no better than
chance at detecting deception (Bond & DePaulo, 2006; Hartwig & Bond, 2011). The
goal of the current study was to investigate whether intuitively detecting deception
through awareness of ones own emotions can improve the accuracy of detection. We
did not find that the participants were more aware of their emotions and they did not
feel more negative after watching a liar. In study 1, videos containing people that
INTUITIVELY DETECTING DECEPTION 17 either told the truth or a lie were used in combination with emotion questions in order
to determine if more emotional awareness increased detection accuracy. Participants
did not feel more negative after watching someone lie in a video and it appears that
intuition was not necessarily enhanced by first responding to emotion items. It could
be said that being aware of your emotions creates a more intuitive mindset, however,
results did not confirm that people were more accurate at detecting lies via emotional
contagion, because we did not see significant differences between the conditions.
In study 1 people spent less time to correctly detect truths, than when they did
that incorrectly. Intuitive processing seems to take less time than deliberate
processing, because no conscious decisions have to be made and the process works
more automatic, as Evans (2003) and Kahneman (2011) discussed. If this shorter time
indicates participants made more use of intuitive processing, we can say that intuition
influences the accuracy in detecting truths. Results shown that people, however, did
not spent less time to correctly detect lies, which is corresponding with the truth-bias:
The tendency that people detect more truths than lies (Vrij & Baxter, 1999;
Albrechtsen et al., 2009).
In study 2 the same method was used, except for the videos. Although we
changed the truthfulness of the videos for the last subject each target person told
about, the truths and lies might not have been that obvious. Therefore, the second
study contained videos with more extended lies in comparison with the first video.
Even though the second study used more extensive lies and truths, it seems that the
lies did not influence the emotions experienced by the participants, because they did
not feel more negative after watching the videos.
In the meta-analysis we found that people who answered the veracity question
directly after watching a video, were significantly more accurate in detecting
INTUITIVELY DETECTING DECEPTION 18 deception. These results were not found in study 1 and study 2 separately, indicating
that the effect was small. That significant results were found for the filler condition of
study one and for the veracity condition and the filler condition of the meta-analysis,
regarding the accuracy of deception detection, contradicts with the prediction that the
emotion condition would improve the accuracy. A possible explanation for the fact
that detecting deception was easier in the filler condition, is that the veracity question
was asked not directly after the video, but a few minutes later. Reinhard, Greifeneder
and Scharmach (2013) found that people were better at correctly detecting deception
if they did not detect it immediately, but waited to do so.
The fact that in both studies the usage of an emotion questionnaire did not
have a significant influence on the detection accuracy might indicate that the problem
was not in the movies but in the questionnaire itself, because only eight questions
were asked, which might not have been enough for participants to be aware of their
emotions. Instead of using an emotion questionnaire, other methods can be used in
order to make participants aware of their emotions. It might be possible to change the
current understanding about deception detection, if emotions do have impact on it.
For example, music can be used to let participants experience a certain emotion and
therefore make them more aware of the negative feeling caused by a liar.
The fact that there was no negative feeling perceived by the participants, could
also be caused because the videos were not realistic enough. We did try to make the
scenario realistic and this is why a confederate helped during the recordings of the
videos. Afterwards we asked the persons that acted in the videos in a questionnaire
whether they found the confederate convincing, which was the case for all the acting
persons. For future research, however, a more convincing scenario could be created, if
more materials are available.
INTUITIVELY DETECTING DECEPTION 19 In the current study we did not find evidence that intuitively detecting
deception by being more aware of ones emotions improves the accuracy of detecting
deception. More research needs to be done in order to gain a better understanding of
the impact of intuition on detection accuracy. We suggest that other methods for
eliciting intuition need to be explored, in order to investigate the best way of creating
intuitive processing, for example, Tinghög, et al. (2013) used time pressure in order to
elicit intuitive processing, while other studies like Albrechtsen et al. (2009) use
secondary tasks to cause intuitive processing. We hope that future research provides
the answers to the questions whether emotions have an impact on deception detection
and whether they improve the accuracy of detection.
INTUITIVELY DETECTING DECEPTION 20 References
Albrechtsen, J. S., Meissner, C. A., & Susa, K. J. (2009). Can intuition improve
deception detection performance?. Journal of Experimental Social
Psychology, 45(4), 1052-1055.
Bolte, A. (2003). Emotion and intuition. Psychological Science (Wiley-Blackwell),
14(5), 416.
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