Legal and Criminological Psychology (2012)

© 2012 The British Psychological Society

TheBritishPsychologicalSociety

www.wileyonlinelibrary.com

Lie detection during high-stakes truths and lies

Marianna E. Carlucci1*, Nadja S. Compo2 and Laura Zimmerman3

1Psychology Department, Loyola University Maryland, Baltimore, Maryland, USA2Psychology Department, Florida International University, Miami, Florida, USA3Applied Research Associates, Alexandria, Virginia, USA

Purpose. The current study seeks to expand the deception detection literature by using

real-world pre-interrogative interviews to discern differences in how novices (students)

versus experts (police officers) make judgments about truths and lies.

Methods. Videotapes of routine traffic stops depicting either liars (incriminating

evidence was found in the car) or truth-tellers (no evidence was found in the car) were

edited so the final car search was cut out. Novices and experts watched the tapes and

made truth or lie judgments about the subject in each video.

Results. Overall accuracy of detecting truths and lies for studentswas 63%,while overall

accuracy for police was 60%. The difference between the groups was not significant.

These results were then compared with previously published rates (Bond & DePaulo,

2006). Students’ overall accuracy rates in this studywere higher than previously published

accuracy rates. However, police officers’ accuracy rates were not higher than previously

published accuracy rates.

Conclusions. Realistic stimulus materials seem to increase overall accuracy rates for

students. However, despite differences in experience, there was no difference between

novice and expert truth and lie accuracy.

There is an obvious forensic need for a reliable measure of real-world deception. If

investigators could accurately detect truths and lies, many investigative tasks would

become obsolete: Police officers would always arrest the right person, and interrogations

could solely focus on gathering facts. Unfortunately, research suggests that both experts

(e.g., police officers) and novices are notoriously unreliablewhen distinguishing between

truths and lies, performing at a rate only slightly better than chance (Granhag&Vrij, 2008).

Although investigators believe that their lie-detection skills are superior to laypeople’s

(Garrido, Masip, & Herrero, 2004) and investigators are more confident in their lie-detection decisions (Meissner &Kassin, 2002), several studies to date have shown little to

no difference between experts and novices’ lie-detection skills (DePaulo, 1994; Ekman &

O’Sullivan, 1991; Porter, Woodworth, & Birt, 2000). Arguably, real-world investigators’

*Correspondence should be addressed to Marianna E. Carlucci, Loyola University Maryland, 4501 N. Charles St., Beatty Hall208, Baltimore, MD 21210, USA (e-mail: mecarlucci@loyola.edu).

DOI:10.1111/j.2044-8333.2012.02064.x

1

poor deception detection performance is more consequential than laypeople’s because

theymustoften relyon theirdeceptiondetection skills tomakedecisions aboutwhomthey

investigate, arrest, and interrogate. Thus, the main focus of the current study was to

investigate the factors that may influence accurate truth and lie detection among lawenforcement and possible differences between these experts and novices.

Previous research suggests that poor deception performance may be related to

common misconceptions about cues to deception (see Hartwig & Bond, 2011). Studies

show that false beliefs about signs of lying are similar for both novices and experts (Vrij,

2008). For example, people believe that displaying nervous behaviour and gaze aversion

are indicative of lying. However, neither of these non-verbal cues (nervousness and gaze

aversion) is a reliable predictor of deception (DePaulo, Lindsay, Malone, Muhlenbruck, &

Charlton, 2003; Sporer& Schwandt, 2006).One possible reason for thesemisconceptionsis the way in which law enforcement officials are trained. Many law enforcement officials

are trained to detect deception using the Criminal Interrogation and Confessions

manual developed by Inbau, Reid, Buckley, and Jayne (2001) and known as the Reid

technique. The manual has been criticized for its endorsement of unreliable cues to

deception (Vrij, Mann, & Fisher, 2006). According to the manual, before interrogating a

suspect, police officers should engage in aBehavior Analysis Interview (BAI). In the BAI,

investigators follow a series of steps to determine whether a suspect is lying or telling the

truth. Specifically, the investigator engages in a series of behaviour-provoking questionswith the objective of eliciting both verbal and non-verbal suspect responses thought to be

indicative or diagnostic of truthful or deceptive behaviour. For example, an investigator

may start with an innocuous question about the suspect’s name and a question about

whether the suspect knows why he or she is there, before proceeding to more specific

questions about the crime such as, ‘Why do you think anyone would do this?’ If

investigators conclude that the suspect is deceitful at the end of the BAI, they proceed to

the interrogation. Thus, in real-world investigative settings, the decision regarding a

suspect’s truthfulness often takes place before an interrogation. By the time theinterrogation takes place, investigators already believe that the suspect is deceitful.

Mistakes in truth and lie detection during the BAI can lead to guilt-presumptive

questioning during the interrogation, which can result in false confessions and possibly

false imprisonment (Kassin & Sukel, 1997; Leo & Drizin, 2010).

Experienced law enforcement officers (e.g., police officers, customs officers,

interrogators, etc.) may hold false beliefs about lie detection because they are trained to

look for cues that are not supported by empirical evidence. For example, the Criminal

Interrogation and Confessionsmanual (Inbau et al., 2001) instructs experts to focus onnonverbal behaviour such as posture shifts and placing a hand over mouth (Inbau et al.,

2001). Thus far, research has indicated these are unreliable indicators of deception.

Research has linked this type of training with poor deception detection performance. For

example, Kassin and Fong (1999) found that students trained to use the Reid technique

performed worse when detecting deception than students not trained in the Reid

technique. Thus, poor truth and lie deception performance may relate to the beliefs law

enforcement officials hold about deception.

The use of inadequate stimulus materials in laboratory researchmight provide anotherexplanation for poor performance bypolice.Most lie-detection researchhas used stimulus

material in which students are asked to lie or tell the truth about feelings, opinions, and

events (DePaulo & Rosenthal, 1979; Depaulo, Stone, & Lassiter, 1985; Vrij, 1995; Vrij,

Akehurt, Soukara, & Bull, 2002). In a typical study, students are videotaped either lying or

telling the truth about a given event. Videotapes are subsequently presented to novices

2 Marianna E. Carlucci et al.

(e.g., students) and experts (e.g., law enforcement) to compare deception detection skills

between the groups. The limitation of these studies, however, is that lies provided by

students may not be accompanied by the cues to deception typically exhibited in high-

stakes situations, possibly due to the lack of urgency or consequences if caught. Similarly,truth-tellersmaynot feel the samepressure tobebelievedwhen telling the truth–given thedifference insituationaldemands.Unlike intherealworld, ‘liars’ in laboratorysettingsoften

createfictional stories about innocuouseventsand/orhavenothingat stake if ‘caught’ lying

(Mann, Vrij, & Bull, 2002). As such, experimentally generated lies may be qualitatively

different from lies told by criminals in high-stakes situations.

Similarly, there is reason to believe that displays of truths and deception may present

themselves quite differently between student liars and truth-tellers and real-world

suspects (Porter& ten Brinke, 2010). Studentsmay not display the indicators of deceptionor truthfulness revealed by suspects who aremotivated by high stakes such as their loss of

freedom. Cooper, Herve, and Yuille (2009) suggest that motivation to be believed is a

critical variable when assessing the stimulus materials used in deception research, such

that lying and telling the truth without any consequence can manifest itself in a

qualitatively different way from lying and telling the truth with grave motivation (e.g.,

losing one’s freedom; Cooper et al., 2009). In line with this reasoning, DePaulo, Lanier,

and Davis (1983) examined whether motivated liars and truth-tellers would be easier to

catch than non-motivated ones. Participants were placed in either a low- or a high-motivation condition. Those in the low-motivation conditionwere told that the studywas

a game and that there were no plans to use the truthful and deceptive statements they

were videotaping. In contrast, those in the high-motivation condition were told that they

were ‘on trial’, that a group of their peers would be critiquing their behaviour, and that

their ability to be convincing was correlated with professional success. When presented

with these tapes, participants were better at detecting truth-tellers and liars in the high-

motivation tapes compared with the low-motivation tapes. DePaulo and her colleagues

termed this phenomenon the ‘Motivational Impairment Effect’ (DePaulo & Kirkendol,1988; DePaulo, Kirkendol, Tang, &O’Brien, 1988; DePaulo et al., 1983). Thus, deception

detectionmaybe improved if bothnovices and experts are presentedwithmotivated liars.

Recent studieshave focusedonusingmaterials that aremoreecologically valid to assess

differences in deception detection ability between law enforcement officials and lay

people. Researchers have attempted to motivate student liars and truth-tellers by offering

money or other incentives (DePaulo et al., 1983; Vrij, Edward, & Bull, 2001; Vrij et al.,

2002). However, these lies and truths cannot compare to ‘high-stakes’ real-world lies and

truthswhereaperson’sfreedomisthemotivatingfactor. Inaneffort touserealisticmaterial,Kassin, Meissner, and Norwick (2005) recruited inmates who had been convicted of a

crime. They asked these inmates to give a true confession (an account of the crime they

committed) and a false confession (an account of a crime they did not commit). In return,

each inmate received $20. Using this stimulus material, students and police officers were

tested on their overall deception accuracy. Results of the study showed that overall

accuracy was slightly better than chance at 54% across students and police officers, and

students outperformed police officers. While this study incorporated more realistic

stimulus materials than traditionally found, there are some remaining limitations ininterpreting the results. Inmates in this studywere already incarcerated,with little at stake,

probably altering their lying or truth-telling behaviour compared with real-world liars.

Furthermore, given how real-world investigators are trained to detect deception – namely

making a ‘lie decision’ before an interrogation, these stimulusmaterialsmayhave alsobeen

suboptimal at imitating conditions under which truth or lie decision are likely made.

High-stakes truths and lies 3

Mann, Vrij, and Bull (2004) compared deception detection performance by showing

law enforcement personnel real-life interrogations of suspects. The authors found higher

accuracy rates compared with previous research (65% across truths and lies) and argued

that the use of ecologically valid material yielded higher accuracy rates among lawenforcement.However,onepossible limitationof thesefindings is thatparticipantsviewed

videos of peoplewhowere already suspects in a crime,whichmay have changed theway

participants viewed the materials. Furthermore, suspects in these videos had time to

formulatea lieprior tothe interrogation,unlikehigh-stakesspontaneous lies thatmayoccur

when a police officer and subject interact in the field or as part of the BAI. Finally,

participants in the Mann et al. study had reason to believe that the suspect was lying

becausethepolicewereinvestigatingtheir involvement inacrime, implyingthatpolicehad

someevidenceor inclinationabout thesuspect’s guilt.This in turnmayhave influencedtheveracity judgments of officers in the study, with police officers showing a lie bias. Other

studies have found that ecologically valid materials can lead to increased truth or lie

accuracy. O’Sullivan, Frank, Hurley, and Tiwana (2009) analysed 31 deception studies.

They compared police groups across eight countries and found that police officers who

made veracity judgments of high-stakes lies were significantly more accurate (67%) than

police officers tested with low-stakes lies (55%). According to the authors, high-stakes lies

mimic situations police officers are familiar with, thereby facilitating lie detection.

The type of stimulus material used in most lie-detection studies may not allow for theproper display of behavioural cues, which may lead to an underestimate of people’s lie-

and truth-detection skills. Most theories attribute the source of deception indicators

exhibited by liars to emotional reactions, cognitive effort, and attempted behavioural

control (for a review of theories of cues to deception see Vrij, 2008). As participants in

many studies have little at stake, they are unlikely to exhibit the cues of deception or

truthfulness often found in high-stakes situations (Mann et al., 2004). This fundamental

difference in motivation may translate into different deceptive behaviours and create

differential deception detection accuracy (Vrij, 2008). Similarly, the low-accuracy rates indeception research may be due to the subtlety of cues depicted by low-stakes liars

(Hartwig & Bond, 2011). Experts in particular may benefit greatly from the inclusion of

real-world liars and truth-tellers when attempting to discriminate truth-tellers from liars.

Liars in high-stakes situations should exhibit more signs of deception compared with liars

in low-stakes situations leading to greater overall deception and truth detection accuracy.

Thecurrent study addresses thesemethodological concernsvia the inclusionof real-world

liars and truth-tellers. Specifically,weuse real-worldpre-interrogativematerial to decrease any

potential bias about the suspect’s guilt based on an interrogative setting.Wehypothesize thatusing ecologically valid stimulus materials will result in better overall deception detection

accuracyforbothexpertsandnovicescomparedwithpastresearch.Thestudy’smaingoalwas

therefore to investigate whether lay people (students) and experts (police officers and

detectives) differ in lie and truth detection as a result of realistic stimulusmaterial.

Method

Participants

Fifty-seven student participants (18 male, 39 female) were recruited from the undergrad-

uate subject pool at a Southeastern university. The majority of participants were Hispanic

(72%), 10.5%AfricanAmerican, 10.5%Caucasian, and 7%chose ‘other’. The age rangewas

between 16 and 33 with a mean age of 20 years. Students received course credit for

participating in the study.

4 Marianna E. Carlucci et al.

Sixty-two police officers (53 male, 8 female) were recruited from several police

departments in the Southeastern area of theUnited States. Half of the samplewasHispanic

(50%), 20% African American, 23% Caucasian, and 7% preferred not to disclose ethnic

information. The age range was between 24 and 54 with a mean age of 40 years. Policeofficers, on average, had 12 years of experience interviewing witnesses and 13 years of

experience interrogating suspects.

Materials

Videos

Nine videotaped traffic stops were acquired from a police department in the Southwest

region of the United States. The videoswere selected from a pool of videos taken from the

dashboard camera of a police car that taped routine traffic stops resulting in a car search.

These videotaped traffic stops were initially used by law enforcement for training

purposes regarding traffic stops. All drivers were originally pulled over for minor trafficinfractions. All traffic stops ended in one of two ways: after the car search, the driver was

arrested because illegal drugs or illegal alienswere found in the car or the driverwas let go

after a thorough search of their vehicle yielded no results. Of the nine videotapes provided

to the researchers, 4 were selected based on their total length, sound and picture quality

(two liars and two truth-tellers). Videos that were excluded differed from all others in a

unique feature (e.g., taped at night, poor video or audio quality, no view of the suspect as

he did not leave the car). The four videotapes selected were edited to remove all

identifying information and to remove scenes showing the results of car search so thatparticipants did not observe the outcome. Each video contained only the interaction

between the law enforcement officer and the driver (always denying any wrongdoing),

displaying their verbal and non-verbal behaviour up to the search of the vehicle. The angle

in the videoswas head-on and depicted the driver’s full body. Videoswere between 1 min

and 57 s and 2 min and 30 s in length (M = 2 min and 10 s; SD = .35 s).

Truth or lie questionnaire

After each video, participants made truth or lie judgments about the subject in the video.

The first question asked, ‘Pleasemake a decision about the personwhowas pulled over in

the video you just viewed. Based on the video do you believe the person shownwas hiding

something from the police officer?’ After making this decision, participants were asked to

make a confidence rating about their decision based on a 1 (not confident at all) to 9 (very

confident) scale.

Cues checklist

To examine cues that novices and experts use when detecting deception, all participants

completed a ‘Deception Cues Checklist’ afterwatching the four videos. The checklist was

adopted from Mann et al. (2004). The checklist includes 28 items that collapse into five

subcategories: story, vocal, Inbau (gaze, posture, fidgeting, covering face, and self-

manipulation), body, and conduct cues (see table 1 for endorsements for students and

police officers). For each of these cues (e.g., stammering), participants were asked to

indicate ‘yes’ if they generally use the cue tomake lie-detection decisions in their everydaylives (e.g., at work or in their interpersonal relationships).

High-stakes truths and lies 5

Procedure

The same four video clips of police traffic stops were presented randomly to all

participants. Each clip was cut to approximately the same duration (about 2 min). Two

video clips depicted lies (subject was incriminated by subsequent car search) and two

video clips depicted truths (subject was exonerated by subsequent car search). After

viewing each video, participants made truth or lie and confidence judgments about the

target. Specifically, participants indicated whether the person in the video was hiding

something from the police officer in the video. After watching and rating all four videos,participants provided information about how they typically detect lies in their everyday

lives using a deception cue checklist based on previous research (Mann et al., 2004).

Finally, participants completed a biographical questionnaire about job experience,

training, and prior interviewing experience.

Results

Deception detection accuracy rates were computed across both truth and lie videos.

When collapsed, students’ mean accuracy rate across truths and lies was 63% and police

officers’ was 60%. This difference in mean accuracy between the two groups was not

statistically significant, t(114) = �.631, p = .529, Cohen’s d = �.12. Across all tapes,

both students’ and police officers’ mean accuracy was statistically different from chance,

t(56) = 3.770, p < .01 and t(58) = 3.173, p < .01, respectively.

The overall accuracy rate (correct truth-lie judgments) in the current study wascomparedwith the overall correct lie–truth judgment rate reported in themeta-analysis by

Bond and DePaulo (2006). Collapsing across students and police officers, our overall

accuracy rate (62%) was significantly higher than the one reported in the meta-analysis

(54%), t(115) = 3.237, p = .002, Cohen’s d = .30. When comparing our two groups

separately, students’ accuracy rate (63%) was significantly higher than Bond and

DePaulo’s, t(56) = 2.624, p = .011, Cohen’s d = .35, but police officers’ overall accuracy

rate (60%) was no different from the one reported in the meta-analysis, t(58) = 1.925,

p > .05, Cohen’s d = .25.Next, lie- and truth-detection accuracy was examined separately. For the two truth

tapes only, students’ mean accuracy rate was 55% and police officers’ was 42%,

a statistically significant difference, t(112) = �2.161, p < .05, Cohen’s d = �.40. For the

truth tapes, students’ mean accuracy rate was not statistically different from chance,

t(56) = 1.137, p > .05, and police officers’mean accuracy ratewasmarginally lower from

chance, t(57) = �1.934, p = .058. For the two lie tapes only, students’ mean accuracy

rate was 71% and police officers’ was 80%. This difference was not statistically significant,

t(114) = 1.603, p = .11, Cohen’s d = .30. For the lie tapes, both students’ and policeofficer’s mean accuracy rates were statistically different from chance, t(56) = 5.333,

p < .01 and t(58) = 8.126, p < .01, respectively.

Table 1. Mean endorsement cues by type for police officers and students

Police officers Students

Story cues 3.95 3.58

Vocal cues 3.53 3.23

Inbau cues 3.84 3.30

Body cues 10.46 9.32

6 Marianna E. Carlucci et al.

We then analysed participants’ answers in the deception cue checklist. In line with

Mann et al. (2004), we divided the checklist into five subcategories. Specifically, we

compared students’ and officers’ endorsements of cues for story, vocal, Inbau, body and

conduct cues. There were significant differences between the two groups in theendorsement of Inbau cues and body cues. Specifically, officers were more likely to

endorse Inbau and body cues compared with students, F(1, 117) = 7.083, p = .009,

Cohen’s d = .48 and F(1, 115) = 5.903, p = .017, Cohen’s d = .44, respectively. There

were no significant differences for any of the other deception categories between

students and officers.

We then compared participants’ confidence ratings in their deception detection

decision. Overall, students’ mean confidence rating was 6.22, while police officers’ mean

rating was 6.45. This differencewas not statistically significant, t(109) = 1.159, p = .249,Cohen’s d = .22.

Discussion

The goals of the present study were to assess truth or lie accuracy with real-world pre-

interrogative materials and to compare this accuracy between novices and experts. Wehypothesized that both students and officers would show increased accuracy compared

with what is typically found in the literature. We also expected officers to be more

accurate than students based on the assumption that their familiarity with the stimulus

materials would lead to high deception accuracy. We predicted that using video material

that included high-stakes interactions between actual suspects and officers, something

that has been missing from previous studies, would allow police officers to leverage their

field experience to more accurately judge liars relative to students with no law

enforcement experience. In contrast to most prior studies, in which liar motivation hasbeen an issue, the present study depicted both truth-tellers and liars who had to be

convincing under pressure or face consequences (e.g., arrest).

Regarding the first goal of the study, we expected performance across all participants

to exceed the average published accuracy rate of 54% (Bond & DePaulo, 2006; Kassin

et al., 2005). Interestingly, only students performed better (63%) than the previously

found typical accuracy rate. Police officers’ overall truth- or lie-detection rate (60%) was

not significantly different from the one reported in Bond and DePaulo. Our findings (i.e.,

the overall accuracy of students) cautiously suggest that motivation can play an importantrole in the display of behavioural lie and truth-telling cues andhoweasily those cues canbe

detected.Many researchers have commented on the importance of liarmotivation and our

findings support the notion of diverse stimulus sampling in deception research. The

differencemay be in how liarmotivationmanifests itself physically (DePaulo&Kirkendol,

1988;DePaulo et al., 1983; Vrij, 2008). Itmay be that the suspects in our tapeswerehighly

motivated to be convincing and thus displayed behavioural cues that aid in detecting

deception and truthfulness. Subjects in our videos did not have time to construct a lie or

outline a strategy, they simply had to be convincing on the spot about their involvement inillegal activities or face arrest, which may have also contributed to their display of

behavioural cues.

Breaking down the overall accuracy rate into truth- and lie-detection accuracy revealed

that police officers displayed a lie bias. That is, although police officers showed a high

likelihood of detecting lies correctly (80%), theywere alsomarginally below chancewhen

detecting truths (42%), suggesting that police officers were more sceptical overall. Police

officers’ lie bias has been well documented in other studies (for a summary, see Bond &

High-stakes truths and lies 7

DePaulo, 2006) and is likely due to the nature of their occupation. The lie bias may have

been further exacerbated in this study due to the dashboard perspective presented to

police officers.

One possible explanation for the differences between students and officers is theirdifferential endorsement of deception cues. Researchers have noted that law enforcement

professionals may make lie- and truth-detection errors because they focus on the non-

diagnostic cues of deception they are taught in training (Vrij, 2008). Law enforcement

training often includes information about cues they should look for when detecting

deception,especiallyduringtheinitialBAI(e.g.,posturechanges,gazeaversion;Inbauet al.,

2001). However, there is evidence that those who pay attention to these cues are worse at

deception detection than those who do not (Kassin & Fong, 1999; Mann et al., 2004).

Taken together, the present results suggest that real-world stimulus material has thepotential to increase overall lie- and truth-detection accuracy beyond what has been

typically found in the literature – in line with Mann et al. (2004) and O’Sullivan et al.

(2009). Interestingly, however, this increase does not translate into improved overall

accuracy rates for experts, as the police officers in this study displayed a pattern more in

line with overall increased scepticism than diagnosticity. Students may have performed

better because they probably did not receive the same trainingmaterials as police officers,

thus the inclusion of real-world stimulus materials aided their judgments. The police

officers in our study may have endorsed non-diagnostic cues to deception, reducing theiraccuracy rate relative to the student sample. Future research should investigate the

influence of training on lie bias in deception judgments. Additional research should also

focus on the interaction between experience and the use of realistic stimuli to identify

how highly motivated liars influence naıve and experienced judgers.

Limitations

Like most deception studies, this one has its own set of limitations. One commonlimitation is the amount of stimulus material (Mann et al., 2004) available to researchers.

We had a limited number of usable video clips that could be counterbalanced and that

allowed us to test both truth and lie detection, which limits the generalizability of the

current set of results. Second, although the police officer in the video searched each

vehicle and that is howwe determined whether subjects in the tapes were lying or telling

the truth, we cannot determine with absolute certainty that the truth-tellers were not

hiding something. A cursory search of the car does not completely exonerate the subjects

in the truth-teller videos. In addition, it is possible that the ‘liars’were not aware that illegalsubstances were in the car or that the people they were transporting were illegal aliens.

Finally, the novice and expert group also differed in age (in addition to expertise), and

therefore the difference in agemayhave contributed to the difference between the groups

(in addition to expertise; see Meissner & Kassin, 2002). Unfortunately, the research team

had limited control over the age distribution of the student population sampled and no

control over the participating investigator pool. Nevertheless, the results should

encourage researchers who are interested in how experts make deception decisions to

include more materials that mimic high-stakes lies.

Acknowledgements

The authors thank the American Psychology-Law Society for funding this study through

Grants-In-Aid.

8 Marianna E. Carlucci et al.

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Received 6 November 2011; revised version received 13 June 2012

10 Marianna E. Carlucci et al.