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Antisociality, underarousal and the validity of the Concealed

Information Polygraph Test

Bruno Verschuere a,1,*, Geert Crombez a, Ernst H.W. Koster a, Armand De Clercq b

a Department of Psychology, Ghent University, Henri Dunantlaan 2, B-9000 Ghent, Belgiumb Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 S9, B-9000 Ghent, Belgium

Received 9 January 2006; accepted 17 August 2006

Available online 6 October 2006

Abstract

The Concealed Information Polygraph Test has been advocated as the preferred method for the physiological detection of deception. In this

study, we further examined the validity of the Concealed Information Test in antisocial individuals. Physiological responding to concealed

information was assessed in 48 male prisoners, and compared with responding in 31 male community volunteers. Based upon the association

between antisociality and autonomic hyporesponsivity, lower detection rates were expected in the prisoners. Participants were questioned on five

personally significant items (e.g., day of birth), instructed to deny recognition of this information, and promised a financial reward when able to

hide recognition. Prisoners showed reduced autonomic reactivity in comparison to the community volunteers. This hyporesponsivity had little

impact on the sensitivity of the Concealed Information Test. Detection efficiency in the prisoners was significantly above chance (d = 2.67;

a = 0.82; 79%), and did not differ significantly from that obtained in the community volunteers (d = 3.04; a = 0.85; 87%). The present data support

the validity of the Concealed Information Test in criminal populations.

# 2006 Elsevier B.V. All rights reserved.

Keywords: Polygraph test; Concealed Information Test; Criminal; Psychopathy; Deception; Validity

The polygraph or ‘‘lie detector’’ is frequently applied in law

enforcement worldwide and its use is still growing (Honts,

2005). Nonetheless, the most often applied polygraph test, the

Comparison Question Technique, is highly contested. Essen-

tially, the Comparison Question Technique is an interrogation

method consisting of relevant and comparison questions with

concurrent measurement of physiological responses. The

relevant questions are related to the crime under investigation

(e.g., ‘‘Did you steal your employer’s grey BMW?’’), and the

comparison questions concern general wrong-doings (e.g.,

‘‘Have you ever done anything illegal?’’). The test theory holds

that the questions that pose the largest threat to the examinee

will elicit the strongest physiological responses. For the guilty,

the relevant questions are most threatening. For the innocent,

who can confidently answer ‘‘no’’ to the relevant questions, the

arousing comparison questions pose the largest threat. The

validity of these assumptions has, however, been challenged by

several authors and remains controversial (Ben-Shakhar and

Furedy, 1990; but see Rosenfeld, 1995, 1997). When discussing

the shortcomings of the Comparison Question Technique,

critics often point at an alternative method, called the

Concealed Information Test.

The Concealed Information Test (or Guilty Knowledge Test;

Lykken, 1959) uses physiological responses to assess whether

someone can differentiate crime details from irrelevant control

information. For example, a murder suspect can be presented

with pictures of young females and asked whether he

recognizes the murder victim among them. When innocent,

the suspect is likely to show similar responses to all pictures.

When the suspect is in fact the killer, he/she is likely to

recognize the victim, resulting in differential physiological

responding to the correct picture. During the last decades, the

assumptions of the Concealed Information Test have been

tested extensively. An often used paradigm is the mock crime

procedure, in which some participants are asked to enact a

mock crime, whereas others remain innocent of this pseudo-

crime. Afterwards, all participants are interrogated about their

knowledge of specific crime details and it is investigated how

www.elsevier.com/locate/biopsycho

Biological Psychology 74 (2007) 309–318

* Corresponding author. Tel.: +32 92646443; fax: +32 92646489.

E-mail address: Bruno.Verschuere@ugent.be (B. Verschuere).1 Bruno Verschuere is a postdoctoral fellow of the Fund for Scientific

Research, Flanders, Belgium (FWO).

0301-0511/$ – see front matter # 2006 Elsevier B.V. All rights reserved.

doi:10.1016/j.biopsycho.2006.08.002

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well the Concealed Information Test discriminates ‘‘guilty’’

from ‘‘innocent’’ participants. Another paradigm to examine

the accuracy of the Concealed Information Test is the

autobiographical variant. Here, participants are presented with

personal information, such as their own phone number, and

several foils, and it is assessed whether the examinee shows

differential responding to the personal items. Laboratory

research using these and other procedures has recently been

reviewed by Ben-Shakhar and Elaad (2003; see also MacLaren,

2001, and National Research Council, 2003). These authors

calculated a statistic of accuracy that is based on signal

detection theory, the receiver operating characteristic (ROC)

curve. This statistic compares the distributions of the correct

items in innocent and guilty individuals for the mock crime

procedure or the distributions of the correct and the incorrect

items for the autobiographical variant. The area under the curve

(a) reflects the detection efficiency of the Concealed Informa-

tion Test across all possible cutoff points. The value of a lies

between 0 and 1, and 0.50 indicates that the distribution from

the correct and the incorrect items entirely overlap, and that the

test does not perform above chance. Based upon 80 laboratory

studies, a reasonably high accuracy index a of 0.815 was found.

Mean effect size in these studies was very large, with an

average Cohen’s d of 1.55. There was, however, heterogeneity

indicating that differences in effect size between studies was

not merely due to sampling error. Subsequent moderator

analysis identified several important factors explaining the

variability: motivating participants to appear innocent, using at

least five questions, and verbal denial (say ‘‘no’’) of knowledge

increase detection efficiency. Ben-Shakhar and Elaad selected

10 mock crime studies that met these conditions and found a

mean accuracy index as high as a = 0.95. Effect size of this

selection of studies was 3.12, which is about four times the size

of what Cohen (1988) labelled a large effect size (i.e., 0.80).

This led the authors to conclude that the Concealed Information

Test has an impressive potential.

Laboratory research on the Concealed Information Test has

shown that it can reach high levels of accuracy. When

considering using this polygraph test in practice, it is essential

to know whether results with undergraduates can be generalized

to examinees in criminal investigations (National Research

Council, 2003). It has long been recognized that college

students are ‘‘hardly representative of the average run of

criminal suspects’’ and that ‘‘perhaps a proportion of the latter

would not respond ‘normally’ in such a test’’ (Lykken, 1959, p.

387). A particular reason of concern is autonomic hypor-

esponsivity in criminal populations. Lykken (1957) was one of

the first to demonstrate that psychopathic prisoners, compared

to non-psychopathic prisoners, displayed reduced anticipatory

skin conductance activity to a noxious stimulus. Many studies

ever since have found further evidence for hyporesponsivity in

psychopathy (for reviews see Hare, 1978; Lorber, 2004; Raine,

1993, 1997). Recent studies further suggest that different facets

of psychopathy may have different psychophysiological

correlates. Psychopathy is typically described in terms of

affective-interpersonal features (e.g., shallow affect, superficial

charm, absence of remorse, and lack of empathy), and features

describing a persistent antisocial lifestyle (e.g., impulsivity,

juvenile delinquency, and irresponsibility). Hare’s Psychopathy

Chekclist Revised (PCL-R; Hare, 2003) embodies both facets

of psychopathy, with PCL-R Factor 1 measuring the affective-

interpersonal facet, and PCL-R Factor 2 measuring the social

deviance facet. In incarcerated populations, it was found that

PCL-R Factor 1 is related to lack of fear-potentiated startle

(Patrick et al., 1993). Benning et al. (2005) investigated the

psychophysiological correlates of the two facets of psycho-

pathy using the Psychopathic Personality Inventory (PPI;

Lilienfeld and Andrews, 1996). The PPI is a 187-item

questionnaire that embodies two factors similar to those of

the PCL-R: ‘‘Fearless-Dominance’’ (PPI-I) and ‘‘Antisocial-

Impulsivity’’ (PPI-II; Benning et al., 2005). In a large

community sample of 355 male twins, it was found that

Fearless-Dominance was associated with a specific reduction of

responding to aversive pictures (e.g., deficient fear-potentiated

startle and reduced electrodermal responding to aversive

pictures), while Antisocial-Impulsivity was associated with

overall electrodermal underarousal.

Autonomic underarousal is not restricted to psychopathy,

but appears to be a common predisposition to antisociality,

encompassing criminality, conduct disorder, antisocial per-

sonality disorder, and the social deviance component of

psychopathy. In the Pittsburgh Youth Study, skin conductance

levels at rest in 136 serious delinquent boys and 66 control boys

with a mean age around 16 years were compared. A significant

main group effect was found, with delinquent boys showing

lower skin conductance activity (Gatzke-Kopp et al., 2002).

Herpertz et al. (2003) examined skin conductance orienting to

innocuous tones in 8–13-year-old normal boys, and boys

diagnosed with either conduct disorder, ADHD, or both

disorders. Compared to both controls and boys with ADHD,

the boys with conduct disorder alone and with comorbid

ADHD displayed smaller skin conductance orienting. In a

sample of 969 community males, Patrick et al. (2006) found

that substance abuse and adolescent and adult antisocial

behavior were associated with reduced P300 amplitude in a

visual oddball task. Ortiz and Raine (2004) found a robust

association between antisocial behavior in children and low

resting heart rate.

From an applied perspective, it is of great importance to

know whether autonomic underarousal associated with anti-

sociality decreases the sensitivity of the Concealed Information

Test. There are only two studies that examined the validity of

the Concealed Information Test in criminal populations.

Lieblich et al. (1976) compared the detection efficiency of

autobiographical information in prisoners with undergraduates.

Lower detection efficiency was obtained in the prisoner sample,

although a post hoc distinction revealed that this reduced

sensitivity was restricted to the less relevant items (e.g.,

questions related to the participant’s hobby). Verschuere et al.

(2005) found an association between Antisocial-Impulsivity

(PPI-II) and reduced electrodermal responding to concealed

autobiographical information in prisoners, but found no

differences in the detection efficiency in prisoners and

undergraduates. There are two main methodological objections

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318310

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to these studies. First, neither study used an appropriate control

group. That is, undergraduates and prisoners differ in a number

of variables (e.g., gender, age, ethnic composition, level of

education, etc.) that may affect physiological responding

(Venables and Mitchell, 1996), and hinder interpretation of

group differences. Second, neither study used motivational

instructions, verbal denial, and an optimal number of questions

and alternatives. The procedure used in both studies deviates

from standard procedure, and has shown to result in lower

overall detection efficiency (Ben-Shakhar and Elaad, 2003). In

the present study, we assessed the detection efficiency of a

state-of-the art Concealed Information Test (i.e., motivational

instructions, verbal denial, and five questions with each having

five alternatives) in prisoners and community volunteers,

comparable with regard to gender, age, ethnic composition, and

level of education. Because underarousal may be most

pronounced in prisoners scoring high on the social deviance

facet of psychopathy, the Psychopathic Personality Inventory

was administered. Underarousal was expected to be most

pronounced in prisoners scoring high on Antisocial-Impulsivity

(PPI-II). In sum, we investigated the association between

antisociality and orienting to concealed information, and its

impact on the detection efficiency of the Concealed Informa-

tion Test.

1. Method

1.1. Participants

The prisoner sample consisted of male prisoners (n = 48) of

the Ghent Prison (Belgium), a maximum security prison of

about 250 prisoners. Most of these men were imprisoned

because of (accusations of) a number of crimes. The most

severe crime of these was manslaughter/murder (n = 7), rape

(n = 9), (violent) theft (n = 20), and fraud (n = 3). Mean age

was 36 years (S.D. = 10; range: 23–60). Eighty-six percent of

the prisoners were of Belgian origin, with 14% of the

participants having a different ethnic origin. Forty-seven

percent of the prisoners were unmarried, 25% were married,

and 28% were divorced. Twenty-six percent of the prisoners did

not graduate from high school. Participants were paid s 2 (the

equivalent of one hour prison labor), and could gain an extra s4 when able to appear innocent.

The community sample consisted of male community

volunteers (n = 31). Mean age was 38 years (S.D. = 11; range:

22–60). Ten percent of this sample had a non-Belgian origin.

Fifty-eight percent of the prisoners were unmarried, 26% were

married, and 16% were divorced. Ten percent of the community

volunteers did not graduate from high school. The community

volunteers received s 7.5 for participation, and could double

this amount when able to appear innocent.

1.2. Material

The Psychopathic Personality Inventory was used to assess

psychopathic traits. Respondents indicated to what extent each

item applied to them on a 4-point scale ranging from 1 (= false)

to 4 (= true). The PPI consists of eight subscales: Machiavellian

egocentricity (30 items; measuring narcissistic interpersonal

functioning), Social Potency (24 items; measuring one’s

perceived ability to influence others), coldheartedness (21

items; measuring a propensity toward unsentimentality),

carefree nonplanfulness (20 items; measuring the impulsive

absence of forethought), fearlessness (19 items; measuring the

absence of anticipatory anxiety concerning harm and a

willingness to participate in risky activities), blame externa-

lization (18 items; measuring the tendency to blame others for

one’s problems and to rationalize one’s misbehaviour),

impulsive nonconformity (17 items; measuring a reckless lack

of concern regarding social mores), and stress immunity (11

items; measuring the absence of marked reactions to anxiety-

provoking events). Following Benning et al. (2003), the score

for fearless-dominance (PPI-I) was obtained by summing the

standardized scores on fearlessness, social potency, and stress

immunity. Standardized, instead of raw scores were used

because different subscales are based on unequal number of

items. The score for Antisocial-Impulsivity (PPI-II) was

calculated by adding the standardized scores on impulsive

nonconformity, blame externalization, Machiavellian egocen-

tricity, and carefree nonplanfulness. Note that coldheartedness

does not load on either factor and is not taken into account. The

total score was obtained by adding the standardized scores of all

eight subscales.

The PPI has good psychometric properties, with internal

consistency of individual scales ranging from 0.76 to 0.91, and

test–retest reliability ranging from 0.82 to 0.94 (Lilienfeld and

Andrews, 1996). In a sample of Dutch undergraduates

(n = 127), the Dutch translation had similar internal consis-

tency (0.92) and test–retest reliability (0.99; n = 35) for the total

score (Jelicic et al., 2004).

1.3. Procedure

The present study was approved by the ethical committee of

Ghent University. Participants were informed about the

procedure and its objectives. They signed an informed consent

form. Participants filled in a short questionnaire assessing

autobiographical information (e.g., day of birth) and asked to

name personally important individuals (e.g., parents, children,

siblings, friends, (ex-)partner(-s), . . .).2 Prior to the attachment

of the electrodes, participants were requested to wash their

hands.

Participants were informed that they were going to take part

in a lie detection experiment and they were asked to try to beat

the polygraph by hiding recognition of personal information.

Participants were seated approximately 50 cm from the screen.

The Concealed Information Test consisted of five blocks of

seven items. Each block started with one buffer item (e.g., Is

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318 311

2 It is possible that participants answer untruthful on the questionnaire. For

the prisoners 62% of the personal items used in this study were checked through

objective file information. All verified items were found correct, indicating that

the prisoners answered the questionnaire truthfully.

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your name SANDER?), followed by one personal item (e.g., Is

your name BRUNO?), four control items (e.g., Is your name

KAMIL?), and one catch item (e.g., Is your name SEVEN?).

The order of the personal, catch, and control items was

randomly determined. Personal items (first name, last name,

first name of the father, first name of the mother, birthday) were

selected from the questionnaire that was assessed earlier in the

session. Control items were selected prior to the experiment,

but checked (and if necessary changed) in order to assure that

they did not resemble any of the items from the questionnaire.

The catch items were included to assure that participant’s

attention was focused on the screen. Participants were

requested to name the catch number instead of answering

‘‘no’’. Inclusion of catch items has been shown to leave

detection efficiency in guilty individuals unaffected (Elaad,

1997). All items were presented on screen for 6 s, with an inter-

stimulus interval (ISI) of 25 s.

1.4. Recording and scoring of psychophysiological signals

All stimuli were presented by a first PC using Inquist

software (2002). A Lablinc V Coulbourn recorded skin

conductance, heart rate and respiration. Psychophysiological

signals were stored on a second PC, equipped with a Scientific

Solutions Labmaster DMA card, running VPM software (Cook,

1997). The psychophysiological data were analyzed using

Psychophysiological Analysis (PSPHA; De Clercq et al., in

press), an interactive software program that we developed for

the off line analysis of psychophysiological data.

Skin conductance was measured using a constant voltage

(0.5 V) coupler, and Ag/AgCl electrodes (0.8 cm diameter)

filled with KY-jelly that were attached on the thenar and

hypothenar eminences of the left hand. Skin conductance was

digitized at 10 Hz. Using PSPHA, skin conductance responses

(SCRs) were calculated as the difference in amplitude between

SCR onset (0.5–4 s post-stimulus onset) and peak (0.5–4 s post-

SCR onset; Dawson et al., 2000). Differences in amplitude

smaller than 0.05 mS were scored as 0.

Heart rate activity was obtained by using three electrodes

placed in the standard lead II configuration: the negative

electrode was placed just below the right clavicle, the positive

electrode on the left lower rib, and the ground electrode placed

on the right lower rib. Heart rate was filtered (band pass: 8–

40 Hz) and digitized at 500 Hz. PSPHA was used to detect the

R-waves in the ECG and to calculate the distance between

them. An artifact detection and correction procedure was

applied with PSPHA using established procedures (Cheung,

1981). Prior to analysis, the interbeat intervals (IBI) were

converted to heart rate in beats per minute (bpm) per real-time

epoch (1 s). Mean bpm in the 3 s preceding stimulus onset were

compared to the mean bpm in the 15 s period after stimulus

onset.

Respiration was measured using a single strain gauge attached

around the thorax. Respiration moved the air in the elastic tube

and these variations were picked up by a pressure sensor. The

difference in pressure was converted to voltage and digitized at

250 Hz. In line with applied research on the physiological

detection of deception, we calculated respiration line length

(Timm, 1982). Respiration line length is a composite measure of

respiratory amplitude (depth of breathing) and respiratory cycle

(rate of breathing). As orienting is associated with slower and

more shallow breathing, lower respiration line length values are

expected after concealed information than after control

information. The length of the respiration line was measured

starting from stimulus onset up to 15 s later (Elaad et al., 1992).

Timm has pointed out that the length of the respiration line might

be disproportionally affected by the start of measurement. For

example, starting at the end of a slowly declining expiratory curve

or at the beginning of the rapidly ascending inspiratory curve

would produce different line lengths for the same time interval. In

order to deal with this problem, each respiration line length was

calculated as the mean of 10 respiration line lengths: from

stimulus onset to 15 s later, from 0.1 s after stimulus onset to

15.1 s after stimulus onset, from 0.2 to 15.2 s after stimulus onset,

etc. We calculated respiration line length with PSPHA using the

following formula: respiration line length ¼ SQRTðdX2 þdY2

1 Þ þ SQRTðdX2 þ dY22 Þ þ � � � þ SQRTðdX2 þ dY2

n Þ with

� dX being the difference in time (expressed in milliseconds)

between two subsequent data points.

� dY being the difference in amplitude (expressed in AD-

values) between two subsequent data points.

� n being the number of data points (after smoothing) in the

time period under investigation, i.e., 15 s.

2. Results

Due to equipment failure and/or experimenter error, data of

one (community) participant were lost for skin conductance, of

four participants (three prisoners) for heart rate, and five

(community) participants for respiration.3

2.1. Manipulation check

Data from one prisoner were excluded, because he failed

to comply with the instructions, and answered ‘‘yes’’ to all

questions. No participant had more than two catch items

incorrect. Most catch items were correctly named, with a

tendency of prisoners (M = 4.37; S.D. = 0.76) being less

accurate than the community volunteers (M = 4.68;

S.D. = 0.54), F(1, 77) = 3.68, p = .06, d = 0.47. Exclusion

of participants who had two catch items incorrect (one

community male, eight prisoners) had little effect on the

results; no participants were excluded based upon this

criterion.

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318312

3 This leads to unequal number of participants for the different measures,

which might bias comparison between the measures. If, for example, respira-

tory detection efficiency of the five lost participants was very high, this could

lead to an unfair low estimate for this measure. Therefore, we re-ran the

analyses with only participants of whom data were available for all three

measures (44 prisoners and 26 community volunteers). Because the results of

these analyses were virtually identical to those including all participants, we

only report the former (i.e., including all participants).

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2.2. Psychopathic personality inventory

Mean (unstandarized) scores for the community volunteers

were 133 (S.D. = 18), 183 (S.D. = 24), and 367 (S.D. = 36), for

Fearless-Dominance, Antisocial-Impulsivity, and the total

score, respectively. Mean scores were elevated in the prisoners,

but not significantly so, F’s < 2.84. Mean scores in the

prisoners were 140 (S.D. = 21), 190 (S.D. = 30), and 379

(S.D. = 44), for Fearless-Dominance, Antisocial-Impulsivity,

and the total score, respectively.

2.3. Antisociality and autonomic underarousal

To assess whether prisoners displayed autonomic under-

arousal, raw scores on each physiological measure were

compared by multivariate analysis of variance (MANOVA)

with group (prisoners versus community) as a between subjects

factor and stimulus (personal versus control) as the within

subjects factor (Vasey and Thayer, 1987). Following Ben-

Shakhar and Elaad (2003), we report Cohen’s d as a measure of

effect size, with d’s of 0.20, 0.50 and 0.80 used as thresholds to

define small, medium and large effects, respectively (Cohen,

1988).

2.4. Skin conductance

The MANOVA on the magnitude of skin conductance

responding showed significant effects of Stimulus, F(1,

73) = 51.67, p < .001, d = 0.60, and Group, F(1, 73) = 14.02,

p < .001, d = 0.82, that fell under the significant Stimu-

lus � Group interaction, F(1, 73) = 6.27, p < .05, d = 0.55, see

Fig. 1A. The main effect of stimulus shows that personal items

(M = 0.85, S.D. = 1.01) elicited greater skin conductance

responses compared to control items (M = 0.37, S.D. = 0.52).

The main effect of group showed that prisoners (M = 0.36,

S.D. = 0.39) showed overall reduced skin conductance reac-

tivity compared to the community volunteers (M = 0.97,

S.D. = 0.97). Finally, the Stimulus � Group interaction indi-

cates that the difference between the personal and the control

stimuli was smaller in the prisoners (M = 0.34, S.D. = 0.43)

than in the community volunteers (M = 0.70, S.D. = 0.81).

Follow-up t-tests showed that the difference between personal

and control items was significant for both prisoners,

t(44) = 5.27, d = 0.73, and community volunteers, t(29) =

4.70, p < .001, d = 0.67.

In order to rule out that group differences were due to

artifacts in skin conductance measurement, we repeated the

analyses using an amplitude measure of skin conductance

responding (i.e., excluding 0-responses). Effects of Stimulus,

Group, and Stimulus � Group were replicated, confirming the

validity of these findings.

2.5. Heart rate

The 2 (group: prisoners versus community volunteers) � 2

(stimulus: personal versus control) MANOVA on cardiac

change showed that the main effect of stimulus was significant,

F(1, 72) = 42.25, p < .001, d = 1.16. This effect indicates that

personal items (M = �0.52, S.D. = 1.81) showed cardiac

suppression compared to the control items (M = 1.23,

S.D. = 1.14). Overall cardiac change was somewhat smaller

in the prisoner sample (M = 0.20, S.D. = 0.98) than in the

community sample (M = 0.57, S.D. = 0.93), but the main effect

of Group was non-significant, F(1, 73) = 2.41, p = .13,

d = 0.39. The Stimulus � Group interaction was also non-

significant, F < 1 (see Fig. 2).

2.6. Respiration

The MANOVA on respiratory line length showed

significant effects of Stimulus, F(1, 72) = 26.60, p < .001,

d = 0.12, and Group, F(1, 72) = 24.22, p < .001, d = 0.95,

that fell under the significant Stimulus � Group interaction,

F(1, 72) = 17.45, p < .001, d = 0.82, see Fig. 1B. The main

effect of stimulus shows that respiration line length was

shorter after personal items (M = 15 478, S.D. = 342)

compared to control items (M = 15 526, S.D. = 424). The

main effect of group showed that respiration line length for

prisoners (M = 15 370, S.D. = 183) was shorter compared to

the community volunteers (M = 15 737, S.D. = 513). Finally,

the Stimulus � Group interaction indicates that the differ-

ence between the personal and the control stimuli was

smaller in the prisoners (M = 12, S.D. = 25) than in the

community volunteers (M = 110, S.D. = 166). Follow-up t-

tests showed that the difference between personal and control

items was significant for both prisoners, t(47) = 3.29,

p < .01, d = 0.06, and community volunteers, t(26) = 3.49,

p < .01, d = 0.23.

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318 313

Fig. 1. Mean (with standard errors) magnitude of skin conductance responding

(in ms; A) and respiration line length (in arbitrary units; B) to personal and

control items in the prisoner and the community sample.

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To assess whether hyporesponsivity was more pronounced

in psychopathic prisoners, we allocated prisoners to high versus

low psychopathic groups based upon their scoring above or

below the median of the Psychopathic Personality Inventory

factor scores. Three groups were created in this way for both

Antisocial-Impulsivity (23 prisoners scoring high on Anti-

social-Impulsivity, 24 prisoners scoring low on Antisocial-

Impulsivity, and 30 community volunteers), and Fearless-

Dominance (24 prisoners scoring high on Fearless-Dominance,

23 prisoners scoring low on Fearless-Dominance, and 30

community volunteers). Overall, results confirmed the analyses

above, with effects of Group showing reduced overall

responding, and effects of Stimulus � Group showing reduced

differential responding in skin conductance magnitude and

respiration line length. Post hoc comparisons showed that

differences were due to reduced responding in prisoners versus

community volunteers, with no significant differences between

high versus low psychopathic prisoners.

2.8. Antisociality and detection efficiency of the concealed

information test

Detection efficiency was evaluated based upon within-subject

within-block Z scores. Within-subject within-block standardiza-

tion has been shown to reduce individual differences and effects

of habituation, thereby maximizing detection efficiency (Ben-

Shakhar, 1985; Ben-Shakhar and Dolev, 1996). Thus, Z scores

were computed relative to the participant’s mean and standard

deviation of each block. Only blocks containing at least one

measurable responsewere taken into the analyses. For respiration

line length and cardiac change, Z scores were multiplied by �1

because concealed information is associated with lower values in

these measures (e.g., cardiac and respiratory suppression).

Several statistics were calculated to evaluate detection efficiency.

First, using MANOVA we evaluated whether the personal items

elicited stronger responses than the control items did, and

whether the strength of responding differed in both samples.

Thus, a 2 (group: prisoners versus community) by 2 (stimulus:

personal versus control) MANOVAwas used for each dependent

measure. Second, we calculated detection efficiency using the

approach introduced by Ben-Shakhar et al. (1970), and recently

recommended by the National Research Council (2003). Using

SPSS 12.0, a receiver operating characteristic (ROC) curve with

corresponding 95% confidence interval (CI) was calculated for

each measure in each sample. This statistic informs us to what

extent the distributions of the personal and the control items

differ. Third, it is also interesting to look at percentage correct

classification. For this purpose, we used Lykken’s (1959) scoring

procedure, which has been applied in many studies on the

Concealed Information Test (see Ben-Shakhar and Elaad, 2003).

In this procedure, physiological responses to all alternatives of

each question are rank ordered. A score of 2 is assigned if the

personal item elicited the largest response, 1 if it elicited the

second largest response, and 0 for any other response. Responses

are summed across n questions, providing a detection score

ranging between 0 and 2n. The cutoff was set at n, with

participants scoring below this cutoff classified as ‘‘concealed

information undetected’’, and participants scoring at least n

classified as ‘‘concealed information detected’’. Using five

questions, cutoff was set at five in the present study. When data

were missing for a question, the cutoff was lowered to the number

of valid questions. A x2-test was used to compare the percentage

correct in the prisoner and the community sample. A binomial

test was used to test the significance of the classification rates

against .50.

2.9. Skin conductance

The 2 (group: prisoners versus community volunteers) � 2

(stimulus: personal versus control) repeated measures MANOVA

revealed a main effect of stimulus, confirming that personal items

elicited greater skin conductance responses compared to control

items, F(1, 72) = 133.12, p < .001, d = 2.38 (see Table 1). No

effect with group as a factor reached significance, F’s < 1.

Inspection of the ROCs indicates that skin conductance

performed above the 0.50 chance level in prisoners (a = 0.85)

and community volunteers (a = 0.80), with no significant

differences between groups. The individual classification rates

show that concealed information was detected in 36 out of 44

(82%), p < .001, prisoners and of 25 out of 30 (83%), p < .001,

community volunteers. These individual classification rates were

not significantly different, x2 < 1.

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318314

Fig. 2. Mean second-by-second change in heart rate (in bpm) to personal and

control stimuli in the prisoner (A) and the community sample (B).

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2.10. Heart rate

The 2 (group: prisoners versus community volunteers) � 2

(stimulus: personal versus control) repeated measures MAN-

OVA was used to analyze mean change in heart rate. There was

a significant main effect of stimulus, F(1, 72) = 62.24,

p < .001, d = 1.58, confirming that cardiac change after

personal and control items differed significantly (see

Table 1). No effects with group as a factor reached significance,

F’s < 1. The ROC analysis showed that the detection efficiency

of the cardiac measure was significant above chance, with no

differences between groups (prisoner sample: a = 0.66;

community sample: a = 0.68). The individual classification

rates showed that personal items were detected in 25 out of 44

(57%), p > .05, prisoners and 16 out of 30 (53%), p > .05,

community volunteers. Classification rates were not signifi-

cantly different between groups, x2 < 1.

2.11. Respiration

The 2 (group: prisoners versus community volunteers) � 2

(stimulus: personal versus control) repeated measures MANOVA

showed that respiration line length was shorter after personal

items than after control items, F(1, 71) = 43.44, p < .001,

d = 1.29 (see Table 1). No effect with group as a factor was

significant, F’s < 1.9. Inspection of the confidence intervals

shows that significant detection was obtained in both samples.

Detection efficiency of respiration line length was significantly

higher in the community sample (a = 0.71) than in the prisoner

sample (a = 0.64). The individual classification rates showed that

personal items were detected in 22 out of 47 (47%), p > .05,

prisoners and15outof26 (58%),p > .05, communityvolunteers.

These classification rates did not differ significantly, x2 < 1.

2.12. Comparing and combining physiological response

measures

As can be seen in Table 1, all analyses showed that skin

conductance differentiated better between personal and control

items than the respiratory and the cardiac measure. Effect size

for skin conductance (d = 2.38) was substantially larger than

for the other measures (HR: d = 1.66, RLL: d = 1.08). The

ROCs also confirmed the superiority of skin conductance, with

the confidence intervals demonstrating that skin conductance

(a = 0.83; 95% CI = 0.80–0.86) performed significantly better

than both cardiac change (a = 0.67; 95% CI = 0.64–0.71) and

respiratory line length (a = 0.66; 95% CI = 0.63–0.70).

Percentage correct was also higher for skin conductance (61

out of 74 participants or 82%) than for cardiac change (41 out of

74 participants or 55%) and respiration line length (37 out of 73

participants or 51%).

In applied settings, physiological responses are combined in

order to achieve optimal detection efficiency. We assessed the

detection efficiency of the combined measure by calculating

the weighted mean of the three measures. Because previous

research has shown that skin conductance is most efficient in

detection concealed information (see e.g., Gamer et al., 2006),

this measure was assigned double weight (2� SCR, 1� RLL,

1� HR). This combined measure was highly efficient

(d = 2.54; 84% correct classifications; a = 0.83, 95%

CI = 0.81–0.86). The combined measure did not, however,

increase detection efficiency compared to skin conductance

(see Table 1).

We compared the detection efficiency of the combined

measure in both samples by running a 2 (group: prisoners

versus community volunteers) � 2 (stimulus: personal versus

control) repeated measures MANOVA. Only the main effect

of stimulus was significant, F(1, 75) = 200.04, p < .001,

d = 2.86, with no significant effects with group as a factor,

F’s < 1. Comparison of the ROC curves indicates that

detection efficiency of the combined measure in the

community sample (a = 0.85) did not significantly differ

from that obtained in the prisoner sample (a = 0.82). The

individual classification rates showed that personal items

were correctly detected in 37 out of 47 (79%), p < .001,

prisoners and 26 out of 30 (87%), p < .001, community

volunteers. These classification rates did not differ signifi-

cantly, x2 < 1.

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318 315

Table 1

Means (and standard deviations) of the physiological responses to personal and control items in the community and the prisoner sample; area under the ROC-curve

with corresponding 95% confidence interval

Mean Z score

(S.D.) personal items

Mean Z score

(S.D.) control items

Effect Size

Cohen’s d

Area under the ROC curve

(with 95% confidence interval)

Percentage correct

classification

Skin conductance

Community 0.88 (0.51) �0.22 (0.12) 2.97 0.80 (0.76–0.85) 83

Prisoners 0.85 (0.69) �0.21 (0.19) 2.09 0.85 (0.81–0.88) 82

Cardiac change

Community 0.45 (0.49) �0.11 (0.12) 1.57 0.68 (0.64–0.73) 53

Prisoners 0.40 (0.43) �0.11 (0.11) 1.66 0.66 (0.62–0.70) 57

Respiration line length

Community 0.53 (0.46) �0.13 (0.11) 1.97 0.71 (0.66–0.76) 58

Prisoners 0.35 (0.58) �0.09 (0.14) 1.04 0.64 (0.60–0.68) 47

Combined measure

Community 0.66 (0.37) �0.16 (0.09) 3.04 0.85 (0.81–0.89) 87

Prisoners 0.61 (0.39) �0.15 (0.10) 2.67 0.82 (0.79–0.86) 79

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2.13. Psychopathic traits and detection efficiency of the

concealed information test

We reran the MANOVAs with the prisoner group subdivided

into high versus low scores on the Psychopathic Personality

Inventory factors. No significant group differences emerged from

these analyses. Following Verschuere et al. (2005), Pearson’s r

between Psychopathic Personality Inventory factor scores and

the concealed information effect measurewas calculated for each

physiological index (the mean standardized response to the

concealed information minus the mean standardized response to

the control information). Correlations were all small, jrj < .21,

and none reached significance. Following Waid et al. (1979), the

Psychopathic Personality Inventory scores of the detected versus

undetected participants were compared with univariate ANOVAs

for each physiological measure. These analyses also failed to

reveal any significant effects, F’s < 1.6.

3. Discussion

The effect of antisociality on autonomic responding in the

Concealed Information Test was investigated. In line with our

review of the literature, we found that prisoners displayed

autonomic hyporesponsivity. Differential responding to personal

versus control items was significantly reduced in measures of

skin conductance and respiration as indicated by the statistically

significant Stimulus � Group interaction effects. Our results

further support the idea that antisociality is associated with

autonomic underarousal. It has been theorized (see e.g., Eysenck,

1964; Raine, 1993, 1997) that criminals are in a chronically lower

state of arousal, seeking stimulation to optimize their arousal

level. As such, underarousal theory can explain why delinquent

adolescents are more impulsive, more danger seeking and more

likely to reject conventional values (Krueger et al., 1994). This

hyporeactivity appeared to be a common characteristic of the

prisoner group, rather than specific for the psychopathic

prisoners. Krueger et al. (2005) theorized that criminality may

evolve from a stable propensity to act in an unconstrained way.

This global ‘‘externalizing’’ factor is thought to underlie

criminality, conduct disorder, antisocial personality disorder,

and substance abuse. There is accumulating evidence for a broad

externalizing vulnerability factor. Krueger et al. (2005), for

example, showed through statistical modelling that the

systematic co-occurrence of externalizing syndromes can best

be explained by a coherent underlying externalizing factor.

Family, twin, and adoption studies further support this idea,

linking conduct disorder, antisocial personality disorder, sub-

stance abuse and an unconstrained personality style to a common

highly heritable factor. Our findings further support the idea that

this externalizing factor is associated with reduced physiological

responding (see also Patrick et al., 2006).

3.1. Antisociality and detection efficiency of the concealed

information test

When compared to community volunteers, autonomic

hyporesponsivity was observed in our prisoner sample. It has

been argued that hyporesponsivity would lower the sensitivity

of the Concealed Information Test, and that hyporeactive

‘‘guilty’’ participants could escape detection (Raskin and Hare,

1978). We used several statistics (MANOVA, Receiver

Operating Curve, and Percentage Correct Classifications) to

investigate whether the observed hyporesponsivity lowered

detection efficiency. It appeared that hyporeactivity did not

deteriorate detection efficiency: Accuracy of the Concealed

Information Test was high in the prisoners, and did not differ

from that obtained in the community volunteers. In applied

settings, assessing the presence of concealed information is

based upon a combination of several physiological responses.

The detection efficiency of the combined measure in the

prisoners (d = 2.67; a = 0.82; 79%) was similar to that obtained

in the community sample (d = 3.04; a = 0.85; 87%). Moreover,

psychopathic traits – Antisocial Impulsivity in particular – did

not moderate detection efficiency. These results indicate that

although responding was decreased in the prisoners, concealed

information was still discernable from the control items,

leaving detection efficiency of the Concealed Information Test

intact.

3.2. Validity of the concealed information test

Consistent with numerous previous reports, skin conduc-

tance was the best index of concealed information in our study

(across groups: a = 0.83). Adding the cardiac and the

respiration measure did not significantly improve detection

efficiency (across groups: a = 0.83). Combining measures in

this study did not increase detection efficiency, because the

cardiac and the respiratory measure had low detection

efficiency. The lower detection efficiency of the cardiac

measure is consistent with previous research. Gamer et al.

(2006), for example, recently reported similar diagnostic

utility of the cardiac measure (a = 0.67) as we did here (across

groups: a = 0.67). The respiratory measure in the present study,

however, was also of lower diagnostic utility (across groups:

a = 0.67), in contrast to previous studies that found respiration

to be as efficient as skin conductance (e.g., Ben-Shakhar and

Dolev, 1996). However, it is in line with other studies that

failed to find strong effects with the respiratory measure (e.g.,

Ben-Shakhar et al., 1999). It remains unclear why respiration

did not produce larger effects in our and other studies. Our

findings strongly suggest that skin conductance should be

given most weight in the scoring of the Concealed Information

Test.

By creating optimal conditions (motivational instructions,

verbal denial, a limited set of highly relevant items, within

subject within block standardization) we achieved a detection

efficiency level at the upper bound. The selection of high

quality mock crime studies in the meta-analysis by Ben-

Shakhar and Elaad (2003) accomplished very high accuracy

indices. Although the effect size that we found (d = 2.54) is

comparable to that obtained by Ben-Shakhar and Elaad (95%

CI d = [2.27–3.98]), the area under the curve seems lower

(a = 0.83 versus a = 0.95). Our design did not, however, include

an ‘‘innocent’’ condition, and our conclusions, therefore, regard

B. Verschuere et al. / Biological Psychology 74 (2007) 309–318316

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the detection efficiency in ‘‘guilty’’ individuals. It is well

known that the Concealed Information Test is better in

detecting ‘‘innocent’’ individuals (specificity) than in detecting

‘‘guilty’’ individuals (sensitivity). MacLaren (2001), for

example, found a lower accuracy in guilty individuals (76%)

than in innocent participants (83%) in his review of 22 studies.

Ben-Shakhar and Elaad (2003) also found sensitivity (83%) to

be lower than specificity (96%) in their selection of high quality

mock crime studies (Ben-Shakhar, personal communication,

May 2004). The sensitivity level obtained in the present study

(83%) is indeed at the higher bound, and comparable to that

obtained in other well constructed tests.

3.3. Limitations and conclusions

The present study is not without limitations. First, the

ecological validity of our design may be improved. We used

monetary incentive to motivate participants to try to appear

innocent. Although this manipulation has been commonly

used in polygraph research, threatening with punishment

would probably come closer to field conditions. The use of

autobiographical information may also limit the ecological

validity of our study. Although difficult to implement,

replication of our study using a mock crime procedure is

warranted. Second, Raine (1993) has suggested that under-

arousal is restricted to offenders with schizotypical tenden-

cies. Because we did not assess schizotypical traits, we could

not test this possibility. Finally, we did not include an

‘‘innocent’’ condition, limiting our estimate of detection

efficiency to the sensitivity of the Concealed Information

Test. Underarousal is, however, only theorized to deteriorate

the sensitivity, not the specificity of the test. Despite these

limitations, the present study suggests that the autonomic

underarousal associated with antisociality does not deterio-

rate the detection efficiency of the Concealed Information

Test and that good accuracy can be obtained in criminal

populations.

Acknowledgments

The authors wish to thank Celine Lasat for collecting the

data of the community sample. Parts of these data have been

presented on the XVth European Meeting of Psychology and

Law (Vilnius, Lituania) and on the Second Meeting on

Experimental Psychopathology (Leuven, Belgium).

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