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J Child Adolesc Subst Abuse. Author manuscript; available in PMC 2017 October 02.
Published in final edited form as:
J Child Adolesc Subst Abuse. 2016 ; 25(6): 613–625. doi:10.1080/1067828X.2016.1175983.
Adolescent Male Conduct-Disordered Patients in Substance Use
Disorder Treatment: Examining the “Limited Prosocial
Emotions” Specifier
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Dr Joseph T. Sakai,
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver
Dr Susan K. Mikulich-Gilbertson,
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver
Dr Susan E. Young,
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver
Dr Soo Hyun Rhee,
Department of Psychology and Neuroscience and Institute for Behavioral Genetics, University of
Colorado Boulder
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Ms Shannon K. McWilliams,
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver
Mr Robin Dunn,
Department of Orthopedics, School of Medicine, University of Colorado
Dr Stacy Salomonsen-Sautel,
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver
Dr Christian Thurstone, and
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver, Denver Health & Hospital Authority
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Dr Christian J. Hopfer
Division of Substance Dependence, Department of Psychiatry, School of Medicine, University of
Colorado Denver
Abstract
To our knowledge, this is the first study to examine the DSM-5-defined conduct disorder (CD)
with limited prosocial emotions (LPE) among adolescents in substance use disorder (SUD)
Corresponding authors: Joseph Sakai, 12469 East 17th Place, Mail stop F478, Aurora CO 80045, Joseph.sakai@ucdenver.edu.
Financial Disclosures: The other authors report no conflicts of interest.
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treatment, despite the high rates of CD in this population. We tested previously published methods
of LPE categorization in a sample of male conduct-disordered patients in SUD treatment (n=196).
CD with LPE patients did not demonstrate a distinct pattern in terms of demographics or comorbidity regardless of the categorization method utilized. In conclusion, LPE, as operationalized
here, does not identify a distinct subgroup of patients based on psychiatric comorbidity, SUD
diagnoses, or demographics.
Keywords
conduct disorder; limited prosocial emotions; psychopathy; callousness; uncaring; unemotional
Introduction
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For over a decade, our research group has studied youths with substance problems severe
enough to merit treatment entry in adolescence (e.g., Sakai, Hall, Mikulich-Gilbertson and
Crowley, 2004). These youths represent about 11% of all substance use disorder treatment
admissions and in 2010, more than 200,000 adolescents (ages 12-19) were admitted to
substance use disorder treatment in the US (Substance Abuse and Mental Health Services
Administration, 2012). Although evidence-based treatments exist for this population, they
tend to be of moderate effect size (Waldron and Turner, 2008), and various studies suggest
such youths may have chronic courses (Crowley, Mikulich, MacDonald, Young and Zerbe,
1998) and high rates of negative life outcomes (Moffitt, et al., 2011).
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In general population samples, those with drug dependence are more than eight times as
likely as others to have had conduct disorder (CD; Nock, Kazdin, Hiripi and Kessler, 2006)
and over half of adolescents with CD meet criteria for a substance use disorder (SUD; Coker
et al., 2014). Among adolescents whose externalizing behavior problems are severe enough
to merit entry into substance use disorder treatment, very high prevalence of CD is generally
seen (Dennis et al., 2004), with more than 80% of such youths having CD in some studies
(Sakai, Hall, Mikulich-Gilbertson and Crowley, 2004). While a good deal of work has
characterized SUD youths with CD in terms of their longitudinal course and associated comorbid disorders (e.g., Crowley and Riggs, 1995; Walters, 2014; Hopfer et al., 2013), recent
findings have suggested that CD is a relatively heterogeneous phenotype and that CD youth
might be meaningfully divided based on callous-unemotional traits (e.g., Frick and White,
2008). After reviewing evidence showing that callous-unemotional traits are measurable in
childhood (Frick and Ellis, 1999), stable (Frick and White, 2008), and predict worse
outcomes (Frick and White, 2008; Frick, Cornell, Barry, Bodin and Dane, 2003; Frick and
Dickens, 2006), the Diagnostic and Statistical Manual of Mental Disorders' (DSM-5) ADHD
and Disruptive Behavior Disorders Work Group developed and described methods for
categorical identification of callous-unemotional traits (Frick and Moffitt, 2012) and
included a “limited prosocial emotions” (LPE) specifier for the CD diagnosis in DSM-5
(APA, 2013). Prior work has examined LPE in samples of detained youths with high rates of
SUD and this work has failed to link psychiatric comorbidity with CD with LPE vs. CD
(Colins and Vermeiren, 2013; Colins and Andershed, 2015) but we have not found studies
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that have examined potential differences in this distinct but complementary group, SUDtreatment youths with CD with and without LPE.
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To date, the vast majority of work on callous-unemotional traits has been conducted utilizing
dimensional measures of this trait (e.g., total scores from measures such as the Inventory of
Callous Unemotional Traits; ICU; Frick and White, 2008: Lahey, 2014), but inclusion in the
DSM-5 required development and validation of methods for categorization (Frick and
Moffitt, 2012). Unfortunately, despite inclusion of a 4-criteria LPE specifier for a CD
diagnosis in DSM-5, it is not clearly settled in the research community how best to utilize
standard measures, such as the ICU, to generate LPE categorization. For example, the ICU
employs a 4-point Likert scale (0=not at all true, 1=somewhat true, 2=very true, and
3=definitely true); some work has used a “split” coding method where scores of 2 or 3 are
counted (Frick and Moffitt, 2012; Sakai, Dalwani, Gelhorn, Mikulich-Gilbertson and
Crowley, 2012), others have employed an “extreme” coding method where only scores of 3
are counted (Colins and Andershed, 2015), and some have tested both scoring approaches
(Kimonis, Fanti, Frick, Moffitt, Essau, Bijttebier and Marsee, 2015). The number of
questions from the ICU utilized to generate the LPE specifier also has varied, with groups
using as few as 4 items or as many as 9 items from the ICU to determine LPE (Frick and
Moffitt, 2012; Colins and Andershed, 2015; Kimonis, Fanti, Frick, Moffitt, Essau, Bijttebier
and Marsee, 2015). While the extreme coding method appears to provide prevalence
estimates in community samples more in line with predictions (Kimonis, Fanti, Frick,
Moffitt, Essau, Bijttebier and Marsee, 2015), the split coding method was found in one study
to “most consistently discriminate detained youth with high levels of proactive aggression
and violent delinquent behavior” (Kimonis, Fanti, Frick, Moffitt, Essau, Bijttebier and
Marsee, 2015; Kimonis, Fanti, Goldweber, Marsee, Frick and Cauffman, 2014). As yet, it is
unclear whether SUD youths with CD are reliably categorized (LPE yes vs. no) across these
various approaches (i.e., do the 4- and 9-item approaches tend to identify the same youths as
having LPE?) and whether these approaches to LPE categorization provide information that
informs us about callous-unemotional trait severity. This latter point is particularly
important, given that much of the work supporting that callous-unemotional traits are
predictive of persistent antisocial behavior problems and refractory course have utilized
dimensional measures of callous-unemotional traits (Frick and White, 2008: Lahey, 2014);
thus, the validity of an LPE categorization method leans heavily on its ability to map onto
dimensional measures of severity.
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Available evidence from community, school-based, criminal justice or clinically referred
samples support that youth with high levels of callous-unemotional traits may differ from
other youths in certain demographics (e.g., age and sex; Essau, Sasagawa and Frick, 2006),
cognitive measures, such as IQ (Frick, O'Brien, Wootton and McBurnett, 1994; Lynam,
1997; Frick, Cornell, Barry, Bodin and Dane, 2003) and severity of CD (Cale and Lilienfeld,
2002; Frick and White, 2008). Recent models suggest that youth with CD with and without
high levels of callous-unemotional traits may have very different biological underpinnings
(Blair, 2013) and that youths without high levels of callous-unemotional traits may suffer
from heightened threat sensitivity, greater levels of anxiety and reactive aggression (Blair,
Leibenluft and Pine, 2014). In contrast, youths with high levels of callous-unemotional traits
demonstrate reduced stress responsivity (Blair, Leibenluft and Pine, 2014) and lower levels
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of fear and anxiety (Frick, Ray, Thornton and Kahn, 2014). Studies examining detained
youths similarly suggest that levels of callous-unemotional or psychopathic traits are
positively related to severity of externalizing problems, such as substance abuse, anger/
irritability, violence, and hyperactivity (Vahl, Colins, Lodewijks, Markus, Doreleijers, and
Vermeiren, 2014; Skeem and Caufman, 2003). While results regarding internalizing scores
are more mixed, some data do support a negative relationship between callous-unemotional
or psychopathic traits and internalizing disorders (Colins, Bijttebier, Broekaert and
Andershed, 2014) and anxiety (Skeem and Cauffman, 2003). Given this, some groups have
begun to investigate whether CD+LPE is associated with distinct patterns of co-morbidity
(e.g., ADHD, ODD, major depression or anxiety disorders) in, for example, detained
samples (Colins and Vermeiren, 2013; Colins and Andershed, 2015), but we find no such
studies focusing on youths with CD in SUD treatment. In addition, given the theoretical
models predicting threat sensitivity and reactive aggression in youths with CD without LPE,
it may also be important to examine measures associated with extreme irritability. The
anger/irritable symptom phenotype of oppositional defiant disorder, which has predicted
differential outcomes in past studies (Stringaris and Goodman, 2009; Drabick and Gadow,
2012), might also then be hypothesized to be more common among youth with CD without
LPE.
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Although the stability of dimensional measures of callous-unemotional traits has been
previously studied in children, adolescents and young adults (see Frick and White, 2008 for
a review), the stability of callous-unemotional traits, to our knowledge, has not been
investigated in SUD populations. This specific focus on SUD populations is important
because substance intoxication can increase aggression (Hoaken and Steward, 2003). SUD is
defined, in part, by the diminished capacity to control one's use of a drug, despite serious
consequences to oneself and others (APA, 2013). Thus, it is reasonable to hypothesize that
SUD may be associated with “selfish” decision-making (Tonigan, Rynes, Toscova and
Hagler, 2013) and that length of abstinence may be negatively associated with levels of
callous-unemotional traits; however, to our knowledge, this has not been tested in the extant
literature.
Therefore, the current study focuses on a sample of 196 male adolescent conduct-disordered
patients admitted to SUD treatment. We sought to investigate several questions:
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1.
Using 4 commonly employed approaches to LPE categorization from the ICU
(i.e. the 4- vs. 9-question and split vs. extreme coding methods), how prevalent is
LPE among youths in SUD treatment with CD?
2.
Do these 4 previously employed approaches to LPE categorization from the ICU
identify the same SUD treatment youths with CD as having LPE?
3.
Do CD patients with and without LPE (using 4 methods of classification) differ
in their demographic characteristics?
4.
Do these 2 patient groups differ in their performance on tests of cognitive
ability?
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5.
Do these 2 patient groups differ in their rates of substance use disorders or
attention deficit and disruptive behavior, anxiety and mood disorders?
6.
Does the LPE specifier (using 4 methods of classification) capture information
about severity of callous-unemotional traits from the ICU?
7.
Does length of abstinence from substance use differ between those with and
without LPE (using 4 methods of classification) or predict lower levels of
callous-unemotional traits?
Method
Participants
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After Colorado Multiple Institutional Review Board's approval, 317 adolescent patients
(ages 13-18 years) patients were recruited from two large adolescent substance treatment
programs from one metropolitan area (a university-based treatment program and a
community hospital based program). Because of a relatively modest sample of females and
known sex differences in CD with LPE (Kimonis, Fanti, Frick, Moffitt, Essau, Bijttebier,
Marsee, 2015), we restricted our sample to males only. Because LPE is meant to be applied
only to those with CD, we further restricted our sample to patients with whole-life CD
(n=196). Subjects were recruited as part of a larger genetics study. Inclusion criteria
included: (1) adolescents identified through their participation in our two clinical programs
for substance use disorders; (2) age 13-18 years old; (3) estimated full-scale IQ ≥80; (4) for
subjects 17 years of age or younger, valid written consent from parent or guardian, together
with assent from the subject, or for subjects 18 years of age, consent from the subject.
Exclusion criteria were: (1) psychosis; (2) obvious intoxication at time of interview; (3)
current risk of suicide, violence, or fire setting sufficiently great to interfere with evaluation
or to endanger evaluators (though no subject was excluded from the study based on this
criterion); and (4) insufficient English skills. Subjects were informed that their research data
would be held in strict confidence and was protected by a federal certificate of
confidentiality.
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Measures
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Subjects completed a large battery of assessments including: (1) the Wechsler Abbreviated
Scale of Intelligence, vocabulary and block design (WASI; Wechsler, 1999) and (2) the
Peabody Individual Achievement Test, Reading Recognition (Dunn and Markwardt, 1970;
Luther, 1992); (3) the Composite International Diagnostic Interview-Substance Abuse
Module (CIDI-SAM; Cottler et al., 1995); (4) the NIMH Diagnostic Interview Schedule for
Children, Version IV (DISC-IV) (Shaffer, Fisher, Lucas, Dulcan and Schwab-Stone, 2000);
and (5) the self-report Inventory of Callous-Unemotional Traits (ICU) (Frick, 2004).
From the CIDI-SAM, we used the following measures: lifetime DSM-IV abuse or
dependence on cannabis, alcohol, cocaine, amphetamines, opioids, and hallucinogens, and
lifetime nicotine dependence. From a CIDI-SAM supplemental recency question, we
constructed a length of abstinence variable by taking the most recently used non-nicotine
substance for each subject and calculating the time between last use and date of the
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interview. We also calculated total number of lifetime substance use disorder diagnoses met.
From the DISC-IV, we used the following lifetime measures: meeting DSM-IV criteria for
oppositional defiant disorder, attention-deficit/hyperactivity disorder (hyperactive-impulsive
type and inattentive type), conduct disorder diagnosis and symptom count, generalized
anxiety disorder, and major depressive disorder. From the DISC-IV, we calculated the anger/
irritable symptom phenotype of oppositional defiant disorder. Following previous procedures
(Drabick and Gadow, 2012), subjects were counted as meeting this phenotype if they had at
least 4 oppositional defiant disorder symptoms and endorsed these 3 criteria: often loses
temper, is often touchy or easily annoyed by others, and is often angry and resentful. An
anger/irritability component of oppositional defiant disorder has predicted differential
outcomes in past studies (Stringaris and Goodman, 2009; Drabick and Gadow, 2012).
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To compute the callous-unemotional trait scores, we used the ICU in the following ways. We
reverse-scored positively worded items (1, 3, 5, 8, 13, 14, 15, 16, 17, 19, 23, 24) so that each
item was scored 0-3 with higher scores indicating greater callous-unemotional traits. First, to
create a dimensional measure of callous-unemotional traits, we summed all 24 items (range
0-72) to create what we term hereafter the “Total ICU score”. Second, we similarly
calculated Callous, Uncaring, and Unemotional subscales of the ICU, grouping items as
described by others (see Table 1 in Essau et al., 2006). Finally, we created 4 measures of
LPE endorsement based on methods which have been published in the literature utilizing
either split coding (counting responses of very true or definitely true as endorsed) or extreme
coding (counting only responses of definitely true as endorsed) and utilizing either 4
questions (items 3, 5, 6, and 8) or 9 questions from the ICU to determine whether each of the
4 DSM-5 LPE criteria were met. For the 9 question approach, multiple items informed the
LPE criterion: lack of remorse or guilt utilized items 5, 13, 16; callous lack of empathy
utilized items 8, 17, 24; unconcerned about performance utilized items 3, 15; and, shallow or
deficient affect utilized item 1 (instead of item 6 utilized by the 4-question version). Note
that for the 9-question version, where more than one question was utilized for a criterion, the
criterion was endorsed if at least 1 item met the specified threshold. At least 2 out of the 4
criteria must be met for the DSM-5 LPE specifier (categorical, yes vs. no; APA, 2013).
Data Analyses
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We first divided conduct-disordered patients into those meeting and not meeting the LPE
specifier using these 4 methods: 4-question split coding; 4-question extreme coding; 9question split coding; and 9-question extreme coding. To address our first two questions, we
estimated the prevalence of the LPE specifier among the 196 male conduct-disordered
patients in SUD treatment. We calculated Cohen's kappas between the four methods along
with the 95% confidence intervals, Prevalence Index and Bias Index for each comparison to
provide additional information regarding each kappa statistic (Sim and Wright, 2005;
Colins, Vermeiren, Schuyten, Broekaert and Soyez, 2008). To address questions 3-5, we
tested whether CD patients with and without LPE (as determined by each of the 4 methods)
differed in demographics (age, race, ethnicity), estimated IQ, prevalence of substance use
disorder diagnoses, attention-deficit and disruptive behavior disorders, and anxiety and
mood disorders. All continuous variables were assessed for normality and independent ttests or Mann-Whitney U tests were appropriately utilized for group comparisons.
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Categorical variables were compared using Pearson chi-square tests or Fisher's Exact tests if
greater than 20% of the cells had expected counts less than 5. To address question 6, we
tested whether those with and without LPE differed in dimensional measures of callousunemotional traits (Total ICU score, and callous, uncaring and unemotional subscales). We
also tested whether severity of callous-unemotional traits (Total ICU) was negatively
correlated with length of abstinence (Question 7) and whether those with LPE vs. those
without differed in length of abstinence (separately for each of the 4 categorization
methods).
Results
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Question 1: Using 4 commonly employed approaches to LPE categorization
from the ICU (i.e. the 4- vs. 9-question and split vs. extreme coding methods),
how prevalent is LPE among youths in SUD treatment with CD?—Using the 4question split method, the 4-question extreme method, the 9-question split method and the 9question extreme method, 50.5%, 6.1%, 83.7%, and 21.9% met the LPE categorization,
respectively.
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Question 2: Do these 4 previously employed approaches to LPE
categorization from the ICU identify the same SUD treatment youths with CD
as having LPE?—Kappas between the 4 methods of LPE categorization were calculated
but revealed only slight to fair agreement (See Table 1). Ninety five percent confidence
intervals, Prevalence Index and Bias Index were reported for each kappa. The high
Prevalence Index for the comparison between the 4-question extreme coding method and the
9-question extreme coding method, suggest that our kappa may underestimate agreement;
there are also comparisons with elevated Bias Indexes, suggesting kappas may be
overestimated in those instances (Sim and Wright, 2005).
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Question 3: Do CD patients with and without LPE (using 4 methods of
classification) differ in their demographic characteristics?—Table 2 (top 3 data
rows) shows results for demographics; no comparisons between those with and without LPE
were significant, regardless of the method used to determine LPE. Using the 4-question split
method both groups were about 16 years of age, about 60% Caucasian and about 30%
Hispanic. Using the 4-question extreme method, both group means were again about 16
years in age. About one third of those without LPE and two thirds with LPE were Caucasian
but this difference was not statistically significant. Approximately 29% and 42% of those
without and with LPE, respectively, were Hispanic. For the 9-question split method those
without and with LPE did not differ significantly in age (16.6 vs. 16.2 years), race (72% vs.
60% Caucasian), or ethnicity (22% vs. 31% Hispanic). Finally, using the 9-questions
extreme method, those without and with LPE did not differ in age (about 16 years), race
(65% vs. 54% Caucasian) or Hispanic ethnicity (about 30%).
Question 4: Do these 2 patient groups differ in their performance on tests of
cognitive ability?—Table 2 (lower rows) presents comparisons between those without
and with LPE for estimated IQ, the WASI block t-score, WASI vocabulary t-score and the
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PIAT raw score. Using the 4-question split method, CD-with-LPE compared to CD-withoutLPE patients had lower estimated IQ and vocabulary t-scores and averaged lower PIAT raw
sores. With both the 4-question extreme method and the 9-question split method, there were
no significance group differences. Using the 9-question extreme method, patients without
LPE had higher WASI vocabulary t-score than patients with LPE.
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Question 5: Do these 2 patient groups differ in their rates of substance use
disorders or attention deficit and disruptive behavior, anxiety and mood
disorders?—As shown in Table 3, no between-group differences were demonstrated for
any drug category or for the total number of SUD diagnoses for any of the 4 methods of LPE
categorization. In terms of other comorbid disorders (Table 4), groups did not differ in
prevalence of oppositional defiant disorder, the anger/irritability symptom phenotype of
oppositional defiant disorder, attention-deficit/hyperactivity disorder (hyperactive/impulsive
or inattentive subtypes), generalized anxiety disorder, or major depressive disorder. Those
with LPE did have significantly higher conduct disorder symptoms counts (except for LPE
measured by the 9-question split method).
Question 6: Does the LPE specifier (using 4 methods of classification)
capture information about severity of callous-unemotional traits from the
ICU?—Next, we assessed how well each of the 4 methods for LPE categorization
discriminated groups based on dimensional measures of callous-unemotional trait severity
(see Table 5). With only two exceptions (9-question split and extreme methods for the
callous subscale of the ICU), on average, those with LPE scored significantly higher on
measures of callousness compared to those without LPE, regardless of method of LPE
categorization.
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Question 7: Does length of abstinence from substance use differ between
those with and without LPE (using 4 methods of classification) or predict
lower levels of callous-unemotional traits?—Length of abstinence from substances
of abuse did not significantly differ between conduct-disordered patients with and without
LPE using the 4-question split method (p=0.19), the 4-question extreme method (p=0.54),
the 9-question split method (p=0.41) or the 9-question extreme method (p=0.25). We tested
whether length of abstinence was associated with severity of callous-unemotional trait scores
(ICU Total score) in these male patients with conduct disorder. Pearson correlation with
length of abstinence (number of days since using any non-tobacco drug) was r=-0.21 for
Total ICU, which was significant at the p<0.05 level.
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Discussion
The DSM-5 has included a “with limited prosocial emotions” specifier for the conduct
disorder diagnosis. That decision was bolstered by important work often conducted in nonclinical samples, utilizing various conduct problems definitions and dimensional measures
of callous-unemotional traits (Lahey, 2014). Now work is needed in clinical populations of
patients meeting a clinical diagnosis of conduct disorder, while utilizing the DSM-5-defined
categorical LPE specifier. Given the high rate of conduct disorder seen among adolescents
referred for SUD treatment, we sought to estimate the prevalence of CD-with-LPE in this
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clinical population and to better understand the demographic and diagnostic characteristics
of this patient sub-population.
Several concerning findings emerged from our results. First, the prevalence of LPE was
markedly affected by the method of LPE categorization chosen, with as few as 6% of our
conduct-disordered SUD patients meeting LPE while using the 4-question extreme coding
method, and as many as 84% of patients meeting LPE while using the 9-question split
coding method. Previous approaches to subtyping CD have apparently lost favor because
they identified nearly all CD youths as having the specifier (Lahey, 2014); the 9-question
split method suffers from this problem. Our kappa statistics indicated only slight to fair
agreement between the 4 methods. This suggests that who will and will not be identified as
having LPE is highly sensitive to the method of categorization employed.
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We sought to test whether the LPE specifier identified a subgroup of conduct-disordered
patients in SUD treatment with a distinct pattern of demographic or diagnostic differences.
With only a few exceptions, CD patients with LPE did not differ from CD patients without
LPE in terms of demographics, estimated IQ, or prevalence of individual SUD diagnoses, in
the number of lifetime SUD diagnoses, or the prevalence of oppositional defiant disorder
(ODD), the anger/irritability symptom phenotype of ODD, attention-deficit/hyperactivity
disorder, generalized anxiety, or major depression. This finding is consistent with a growing
body of work from detained samples, which have high rates of SUD, showing those with and
without LPE do not differ in prevalence of ADHD, ODD, substance use, mood, and anxiety
disorder prevalence (Colins and Vermeiren, 2013; Colins and Andershed, 2015; Van
Damme, Colins, and Vanderplasschen, in press). Thus, we conclude that the LPE specifier
(as operationalized 4 different ways here) does not appear to identify a distinct subgroup of
CD patients in SUD treatment in terms of demographics and co-morbid disorders.
Three of the four methods of LPE categorization identified a subgroup of conductdisordered patients who on average had higher levels of CD severity (see Table 4, CD
symptom count; except for the 9-question split method). On one hand, this finding suggests
that the LPE specifier may identify a more severely antisocial subgroup among SUD
adolescents with CD in treatment. On the other hand, Lahey (2014) has questioned whether
callous-unemotional traits might simply serve as a marker for greater CD severity. More
work is needed to test whether LPE shows predictive and discriminative validity above and
beyond measures of CD severity. Although we cannot address that question in this crosssectional study, LPE was generally related to CD severity in our sample.
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Given that much of the research literature to date has focused on dimensional measures of
callous-unemotional trait severity and has shown this is predictive of outcome (Frick and
White, 2008; Frick, Cornell, Barry, Bodin and Dane, 2003; Frick and Dickens, 2006), it is
important to test how well the DSM-5-defined LPE specifier provides information on
callous-unemotional trait severity. As noted, Table 5 suggests that those meeting the criteria
for the LPE specifier in our patient sample score significantly higher on dimensional
measures of callous-unemotional traits on average. However, when dealing with clinical
populations, differences of group averages are necessary but not sufficient. For example,
misidentifying someone who does not have high levels of callous-unemotional traits as
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meeting the LPE specifier is potentially harmful. LPE was chosen to replace the term
callous-unemotional because of concerns the latter term is potentially stigmatizing (Frick,
Ray, Thornton, and Kahn, 2014), but the two terms may be conflated among clinicians and
researchers. Prior research has shown that labels such as psychopathy can be stigmatizing
and affect legal decision making (Edens, Clark, Smith, Cox, and Kelley, 2013; Edens, Davis,
Fernandez, Smith, Guy, 2013). Thus, there is some urgency for the research community to
develop standard methods for LPE categorization and assure that LPE validly identifies an
important subtype of those with CD.
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Finally, we also tested whether recency of substance use was associated with levels of
callous-unemotional traits and the LPE specifier. We hypothesized that substance use
disorders, which are characterized by pursuit of a drug despite important consequences often
to one's self and one's loved ones, may induce a state where youths make more callousunemotional choices and have diminished capacity to make decisions strongly influenced by
prosocial emotions. Based on this logic, high rates of LPE could be due to substanceinduced symptoms. To explore this possibility, we tested whether callous-unemotional trait
scores decreased after longer abstinence from substances of abuse. While the correlations
were significant and in the proposed direction (e.g., -0.21), length of abstinence only
explained ∼4% or less of the variance in callous-unemotional trait severity, suggesting recent
substance use was not a major influence.
Limitations
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Our results must be interpreted while considering the study's limitations. (1) Although our
procedures are similar to prior research (Sakai, Dalwani, Gelhorn, Mikulich-Gilbertson and
Crowley, 2012; Colins and Andershed, 2015; Kimonis, Fanti, Frick, Moffitt, Essau,
Bijttebier and Marsee, 2015), our approach differs in some important ways from the manner
in which the LPE specifier may be assessed in practice. For example, clinicians often
consider both self and informant (i.e. parent, teacher, peer) sources, with any positive report
indicating endorsement; here, we assessed only self-report. However, some recent work with
detained youths using both self- and parent-report measures did not find significant
differences between those with and without LPE in ADHD, ODD, any substance use
disorder, any mood disorder and any anxiety disorder (Van Damme, Colins, and
Vanderplasschen, in press). These results are highly consistent with our findings. (2) Our
study recruited patients admitted to adolescent substance treatment. Thus, our results are not
generalizable to community or other clinical samples but may be of use when considering
similar adolescent SUD treatment populations. (3) We restricted our sample to males and our
results should not be extrapolated to females. Future studies should replicate our methods in
adolescent female patients. (4) Our study utilized a cross-sectional design, so we are unable
to comment on the LPE specifier's predictive validity. (5) We did not employ a correction for
multiple testing. However, our results predominantly show a lack of significant group
differences regardless of method of LPE categorization.
J Child Adolesc Subst Abuse. Author manuscript; available in PMC 2017 October 02.
Sakai et al.
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Conclusions
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Using these 4 previously published methods for LPE specifier categorization, we identify
individuals with LPE who, on average, score higher on callous-unemotional trait scores on
dimensional measures. But the prevalence of LPE varied widely between methods and kappa
statistics showed only slight to fair agreement between LPE categorization methods. Thus,
these 4 methods did not generally identify the same individuals as having the LPE specifier.
Male adolescent conduct-disordered patients with and without the LPE specifier were not
easily distinguished in terms of substance use disorder prevalence, attention-deficit/
hyperactivity disorder, oppositional defiant disorder, generalized anxiety disorder, or major
depression prevalence; however, CD patients with-LPE had higher conduct disorder
symptom counts. More work is needed to validate the within-individual stability of LPE
categorization across time and the predictive validity of LPE categorization using
longitudinal designs. Such work would aid in the development of consensus approaches to
LPE categorization from measures such as the ICU.
Acknowledgments
Sources of Funding: This work was supported by grants DA011015 and DA021913 from the National Institute on
Drug Abuse; Dr. Sakai's lab is supported by R01DA031761 and by the Kane Family Foundation and the Hewit
Family Foundation. Dr. Salomonsen-Sautel received support from grant T32AA007464. Dr. Hopfer receives
support from R01DA035804 and K24DA032555. Dr. Mikulich-Gilbertson's effort is supported by DA034604. The
funders had no further role in study design; in the collection, analysis and interpretation of data; in the writing of
the report; or in the decision to submit the paper for publication.
Dr. Sakai received reimbursement in 2012 for completing a policy review for the WellPoint Office of Medical
Policy & Technology Assessment (OMPTA), WellPoint, Inc., Thousand Oaks, CA. He also served as a board
member of the ARTS Foundation until June 2015.
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Table 1
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Agreement (Cohen's Kappas) between 4 methods for LPE categorization in a sample of conduct-disordered
male patients in substance use disorder treatment (n=196). We also present the 95% confidence interval,
Prevalence Index (PI) and Bias Index (BI) for each comparison.
4-question split coding
method
4-question extreme coding
method
9-question split coding
method
4-question
split coding
method
4-question extreme
coding method
9-question split coding
method
9-question extreme coding
method
1
K=0.12 (95% CI=
-0.53, 0.77); PI=0.4;
BI=0.4
K=0.31 (95% CI= 0.21,
0.41); PI=0.3; BI=0.
K=0.11 (95% CI= -0.01, 0.22);
PI=0.3; BI=0.3
1
K=0.03 (95% CI=0.01,
0.04); PI=0.1; BI=0.8
K=0.30 (95% CI= 0.14, 0.45);
PI=0.7; BI=0.2
1
K=0.10 (95% CI=0.06, 0.15);
PI=0.1; BI=0.6
9-question extreme coding
method
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1
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Table 2
4-question split method
4-question extreme method
9-question split method
Sakai et al.
Examining between-group differences in demographics, IQ and Reading using the 4 methods of LPE categorization in a sample of conduct-disordered male patients in substance use disorder
treatment (n=196)
9-question extreme method
J Child Adolesc Subst Abuse. Author manuscript; available in PMC 2017 October 02.
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
Age in years Mean (SD)
16.4 (1.09)
16.2 (1.13)
t194=1.84; p=0.07
16.3 (1.12)
15.8 (1.03)
t194=1.49; p=0.14
16.6 (1.19)
16.2 (1.09)
t194=1.84; p=0.07
16.3 (1.15)
16.3 (1.01)
t194=0.11; p=0.91
Race (Percent Caucasian vs. Other)
64.9%
59.6%
χ2=0.60; p=0.44
35.9%
66.7%
FE p=0.06
71.9%
60.4%
χ2=1.51; p=0.22
64.7%
53.5%
χ2=1.80; p=0.18
Hispanic Ethnicity Percent
28.9%
30.3%
χ2=0.05; p=0.83
28.8%
41.7%
FE p=0.34
21.9%
31.1%
χ2=1.09; p=0.30
29.4%
30.2%
χ2=0.01; p=0.92
IQ Mean (SD)
97.8 (10.76)
93.9 (10.28) (n=98)
t193=2.59; p=0.01
96.2 (10.64)
90.2 (10.01)
t193=1.92; p=0.06
97.0 (10.72)
95.6 (10.68)
t193=0.68; p=0.50
96.5 (10.26)
93.7 (11.89)
t193=1.54; p=0.12
WASI Block t-score Mean (SD)
49.7 (8.47)
47.0 (9.95)
MW Z=-1.79; p=0.07
48.6 (9.27)
45.2 (9.99)
MW Z=-1.12; p=0.26
49.2 (7.63)
48.2 (9.63)
MW Z=-0.11; p=0.92
48.5 (9.08)
47.8 (10.21)
MW Z=-0.33; p=0.74
WASI Vocab t-score Mean (SD)
47.4 (7.72)
44.8 (7.43)
t194=2.44; p=0.02
46.4 (7.61)
42.3 (8.00)
t194=1.77; p=0.08
47.0 (7.49)
45.9 (7.71)
t194=0.74; p=0.46
46.7 (7.14)
43.9 (9.09)
t194=2.13; p=0.03
PIAT Raw Score Mean (SD)
64.2 (8.57)
60.2 (10.14) (n=98)
t188.35=2.96; p=0.003
62.4 (9.61)
58.7 (8.74)
t193=1.30; p=0.19
62.0 (8.16)
62.2 (9.85)
t193=-0.08; p=0.94
7.0 (2.38)
7.3 (2.46)
t193=-0.74; p=0.46
FE = Fishers Exact Test; MW = Mann-Whitney U Test
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Table 3
4-question split method
4-question extreme method
9-question split method
Sakai et al.
Examining between-group differences in lifetime substance use disorder diagnoses using the 4 methods of LPE categorization in a sample of conduct-disordered male patients in substance use
disorder treatment (n=196)
9-question extreme method
J Child Adolesc Subst Abuse. Author manuscript; available in PMC 2017 October 02.
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
Cannabis
88.7%
88.9%
χ21 = 0.003; p=0.96
88.6%
91.7%
FE p>0.99
87.5%
89.0%
FE p=0.76
88.9%
88.4%
FE p>0.99
Tobacco (dependence)
67.0%
65.7%
χ21 =0.04; p=0.84
66.8%
58.3%
FE p=0.54
75.0%
64.6%
χ21 =1.29; p=0.26
66.7%
65.1%
χ21 =0.04; p=0.85
Alcohol
61.9%
64.6%
χ21 =0.16; p=0.69
63.0%
66.7%
FE p>0.99
59.4%
64.0%
χ21 =0.25; p=0.62
62.7%
65.1%
χ21 =0.08; p=0.78
Cocaine
24.7%
22.2%
χ21 =0.17; p=0.68
23.9%
16.7%
FE p=0.74
18.8%
14.4%
χ21 =0.47; p=0.49
24.2%
20.9%
χ21 =0.20; p=0.66
Amphetamine
21.6%
18.2%
χ21 =0.37; p=0.54
19.6%
25.0%
FE p=0.71
21.9%
19.5%
χ21 =0.09; p=0.76
20.3%
18.6%
χ21 =0.06; p=0.81
Opioid
28.9%
19.2%
χ21 =2.52; p=0.11
23.9%
25.0%
FE p>0.99
34.4%
22.0%
χ21 =2.27; p=0.13
26.8%
14.0%
χ21 =3.04; p=0.08
Hallucinogen
24.7%
19.2%
χ21 =0.88; p=0.35
21.7%
25.0%
FE p=0.73
31.3%
20.1%
χ21 =1.94; p=0.16
20.9%
25.6%
χ21 =0.43; p=0.51
# SUD dx
3.7 (2.34)
3.4 (2.05)
t194= 0.95; p=0.35
3.6 (2.18)
3.3 (2.50)
t194= 0.35; p=0.72
3.8 (2.40)
3.5 (2.16)
t194= 0.74; p=0.46
3.6 (2.21)
3.4 (2.16)
t194= 0.53; p=0.60
FE = Fisher's Exact Test
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Table 4
4-question split method
4-question extreme method
9-question split method
Sakai et al.
Examining between-group differences in attention and disruptive behavior, mood and anxiety diagnoses using the 4 methods of LPE categorization in a sample of conduct-disordered male
patients in substance use disorder treatment (n=196)
9-question extreme method
J Child Adolesc Subst Abuse. Author manuscript; available in PMC 2017 October 02.
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
CD, LPE(-)
CD, LPE(+)
ODD (lifetime)
34.0%
46.5%
χ21 ==3.15; p=0.08
39.7%
50.0%
FE p=0.55
25.0%
43.3%
χ21 =3.72; p=0.054
39.2%
44.2%
χ21 =0.35; p=0.56
ODD Anger/Irritable Criterion?
16.5%
20.2%
χ21 =0.45; p=0.50
17.9%
25.0%
FE p=0.46
15.6%
18.9%
χ21 =0.19; p=0.66
17.6%
20.9%
χ21 =0.24; p=0.62
ADHD Hyperactive/Impulsive (lifetime)
22.7%
18.6%
χ21 =0.50; p=0.48
20.9%
16.7%
FE p>0.99
25.0%
19.8%
χ21 =0.45; p=0.50
20.3%
22.0%
χ21 =0.06; p=0.81
ADHD Inattentive (lifetime)
27.8%
22.2%
χ21 =0.82; p=0.36
24.5%
33.3%
FE p=0.50
28.1%
24.4%
χ21 =0.20; p=0.66
23.5%
30.2%
χ21 =0.80; p=0.37
CD Symptom Count (lifetime)
5.8 (2.49)
7.0 (2.39)
t194=-3.55; p<0.001
6.3 (2.47)
8.8 (1.96)
t194=-3.41; p=0.001
5.7 (2.52)
6.6 (2.49)
t194=-1.73; p=0.09
6.2 (2.53)
7.1 (2.35)
t194=-2.01; p=0.05
Generalized Anxiety Disorder (lifetime)
10.3%
14.1%
χ21 =0.67; p=0.41
12.0%
16.7%
FE p=0.65
21.9%
10.4%
FE p=0.08
13.7%
7.0%
χ21 =1.42; p=0.23
Major Depressive Disorder (lifetime)
21.6%
14.1%
χ21 =1.88; p=0.17
18.5%
8.3%
FE p=0.70
25.0%
16.5%
χ21 =1.33; p=0.25
19.0%
14.0%
χ21 =0.57; p=0.44
FE = Fisher's Exact Test
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Table 5
4-question split method
J Child Adolesc Subst Abuse. Author manuscript; available in PMC 2017 October 02.
CD, LPE(-)
CD, LPE(+)
ICU Total Score Mean (SD)
25.4 (7.35)
34.5 (7.15)
ICU Callous Subscale Mean (SD)
7.7 (3.90)
11.1 (4.83)
ICU Uncaring Subscale Mean (SD)
10.2 (4.57)
ICU Unemotional Subscale Mean (SD)
7.5 (2.89)
4-question extreme method
CD, LPE(-)
CD, LPE(+)
t194=-8.78; p<0.001
29.2 (8.11)
42.3 (5.12)
MW Z=-4.97; p<0.001
9.2 (4.54)
13.0 (5.64)
14.0 (3.75)
t185.41=-6.43; p<0.001
11.8 (4.47)
9.4 (2.57)
t194=-4.89; p<0.001
8.2 (2.75)
9-question split method
CD, LPE(-)
CD, LPE(+)
t194=-5.50; p<0.001
20.1 (6.37)
31.9 (7.52)
MW Z=-2.44; p=0.02
8.1 (4.54)
9.7 (4.69)
16.8 (3.98)
t194=-3.74; p<0.001
6.0 (2.26)
12.5 (1.88)
t194=-5.29; p<0.001
6.0 (3.19)
Sakai et al.
Testing 4 methods for LPE categorization against callous-unemotional trait severity based on ICU total score (testing whether categorization identifies groups that differ significantly in measures of severity)
and cut points (calculating sensitivity and specificity against 1, 1.5 and 2 standard deviations above the mean for ICU total score) using a sample of conduct-disordered male patients in substance use disorder
treatment (n=196).
9-question extreme method
CD, LPE(-)
CD, LPE(+)
t194=-8.35; p<0.001
27.9 (7.76)
37.3 (7.12)
t194=-7.15; p<0.001
MW Z=-1.74; p=0.08
9.1 (4.45)
10.6 (5.35)
MW Z=-1.63; p=0.10
13.3 (3.93)
t73.23=-14.53; p<0.001
10.7 (4.09)
17.0 (2.29)
t123.59=-13.20; p<0.001
9.0 (2.57)
t194=-5.75; p<0.001
8.2 (2.75)
9.7 (3.10)
t194=-3.11; p=0.002
MW = Mann Whitney U Test
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