Subtypes of Antisocial Behavior – supplemental materials 1
Supplemental Materials
Early Starting, Aggressive, and/or Callous-Unemotional? Examining the Overlap and
Predictive Utility of Antisocial Behavior Subtypes
by L. W. Hyde et al., 2015, Journal of Abnormal Psychology
http://dx.doi.org/10.1037/abn0000029
Supplemental Methods and Results:
Alternate measures of antisocial behavior subtypes
We originally used the K-SADS to create the aggression and rule breaking measures to partition
the types of measures used for each construct (i.e., to avoid having the age of onset trajectories using the
same questionnaire as the aggression and rule breaking measures which could create collinearity issues)
and to make the “best” possible version of each variable as used most often in the literature (i.e., a
specific measure of CU traits, trajectories used to inform age of onset, and symptoms of conduct disorder
used to make separate aggression and rule breaking dimensions). Making “ideal” measures of each
construct was important since they were each being “pitted” against each other. However, it is important
to explore the possibility that measurement, particularly having child and parent report via an interviewer
on the K-SADS could drive some of the predictive power of the aggression and rule breaking scales. Thus
to address this potential weakness we have considered 3 other approaches in addition to the approach we
described in the main manuscript:
First, we have created aggression and rule breaking measures from the Self-Report of
Delinquency measure, using similar confirmatory factor analytic procedures and present results with these
scales in Table S2. Note that one unfortunate weakness of this approach is that this measure has high
overlap/colinearity with age of onset, which is also assessed using the Self-Report of Delinquency. Not
surprisingly, the use of Self-Report of Delinquency scores to create measures of aggression and rule
breaking diminish the predictive power of these constructs. Interestingly, this approach equally
diminishes the predictive power of the age of onset variables, suggesting that when both variables are
assessed with the same measure and are overlapping, there is little unique variance for each to predict and
that it is less than ideal to use the same measure to inform both constructs.
Second, we explored the use of the K-SADS to examine age of onset (rather than trajectories) to
avoid the confound inherent within trajectory groups that tap both age of onset and severity. However,
using this approach for the measurement of age of onset in this dataset/sample was difficult. Although the
traditional K-SADS does assess age of onset, as this was a longitudinal study with components of the KSADS given every other year since age 10, the retrospective question of age of onset (“when did these
symptoms start?”) typically included in the K-SADS was not included in any of the interviews. Therefore,
the study contains no dimensional parent (nor child) report of the age at which symptoms began as would
typically be measured in a (retrospective) psychiatric interview. To address this concern, we used the
repeated measurement of the K-SADS (i.e., at age 10, 11, 12, 15, 17) across adolescence to create an age
Subtypes of Antisocial Behavior – supplemental materials 2
of onset variable. As age 10 is the threshold for DSM-IV and 5 “early onset”, we coded youth into early
onset (CD diagnosis at age 10), adolescent onset (CD diagnosis at age 11, 12, 15, or 17, but not at 10) and
a non-CD group. We present the results of these analyses in Table S3, noting that there is little overlap
between the K-SADS and trajectory informed variables (see Table S5) and that the K-SADS-based ageof-onset variable shows little predictive power. We are concerned that because this measure seems to
identify very few children as early and late starters, it has poor predictive validity and may not be the
ideal way to measure this construct. In particular, we may be missing many youth who would have met
K-SADS CD criteria before the age of 10.
Additionally, we also attempted to address age of onset via a measure created using the parent
report on the CBCL, which was administered at every assessment. Using the CBCL, we created a
measure of age of onset similar to that created by Moffitt in her first seminal paper on the topic – any
child that scored in the clinical range from age 4 – 8 on the externalizing broad-band scale more than once
was classified as an early starter; any child that was not an early starter, but was rated in the clinical range
more than once during adolescence was labeled a late starter; all other children were labeled low on
externalizing. The results of this analysis are presented in Table S4. As with using the K-SADS to create
age of onset, we found very low numbers of children in each cell and believe the parent-reported CBCL
may be a poor way of identifying late starters (i.e., parents may not be aware of what their teens are
doing). As can be seen in Table S5, there is little agreement between all three methods for creating age of
onset. Though these additional analyses clearly point to weaker predictive validity for age of onset, we are
concerned that these measures are less than ideal in terms of measurement of the construct but may also
point to the need for better measures of this construct in clinical practice.
Subtypes of Antisocial Behavior – supplemental materials 3
Table S1
Predicting Emerging Adult Outcomes From Adolescent Subtypes of Youth Antisocial Behavior Using Dichotomous Measures of Aggression and
Rule Breaking
Outcome
Contrast Code 1:
Presence of AB
Contrast code 2:
age of onset of AB
Any Aggressive
symptom?
Any Rule
Breaking
Symptom?
CU traits
(age 17)
.09 (.10)
.21 (.29)
Step 2
1.4 (.50)**
Self-reported
delinquency
.19 (.04)**
.07 (.12)
.02 (.22)
.32 (.17)+
-.004 (.03)
APD symptoms
.11 (.02)**
.23 (.07)**
.32 (.10)**
.22 (.08)**
-.007 (.01)
APD diagnosis
.16 (.13)
.29 (.29)
1.23 (.52)*
.79 (.49)
-.05 (.08)
Depression
.21 (.16)
-.10 (.34)
1.24 (.62)*
.19 (.54)
-.13 (.10)
Substance Abuse
.13 (.10)
.30 (.29)
.37 (.47)
1.16 (.37)**
.07 (.07)
Substance
Dependence
.13 (.13)
.29 (.30)
.61 (.50)
1.31 (.46)**
.09 (.08)
CU traits
(age 20)
.15 (.07)*
.05 (.21)
.07 (.35)
.34 (.28)
.28 (.05)**
Any arrest/petition?
(adult)
.24 (.09)*
.67 (.27)*
.22 (.43)
.57 (.36)
.06 (.06)
Any arrest/petition?
(adolescence)
.95 (.38)*
.11 (.06)+
N = 266; +p<.10, *p<.05, **p<.01. All tests two-tailed. Each box represents unstandardized regression coefficients with (SE). Self-reported delinquency and
APD symptoms were log transformed to account for their skew. Logistic regression was used for all binary outcomes and linear regression for all continuous
outcomes.
Subtypes of Antisocial Behavior – supplemental materials 4
Table S2
Predicting Emerging Adult Outcomes From Adolescent Subtypes of Youth Antisocial Behavior Using Self-Reported Delinquency-Based Measures
of Aggression and Rule Breaking
Outcome
Contrast Code 1:
Presence of AB
Contrast code 2:
age of onset of AB
+
Self-reported
Aggression
Self-reported Rule
Breaking
CU traits
(age 17)
Step 2
.07 (.09)
-.03 (.05)
.19 (.06)**
.41 (.12)**
.39 (.23)
.23 (.06)**
-.005 (.10)
.018 (.05)
.04 (.02)+
.004 (.02)
.15 (.03)**
.25 (.06)**
.04 (.02)*
.006 (.01)
.001 (.01)
APD diagnosis
.31 (.19)
.49 (.26)+
.11 (.11)
-.005 (.06)
.03 (.09)
Depression
.13 (.19)
-.24 (.32)
.25 (.12)*
.05 (.06)
-.10 (.12)
Substance Abuse
.19 (.16)
.31 (.25)
.09 (.09)
.11 (.06)+
.08 (.07)
Substance
Dependence
.20 (.16)
.22 (.26)
.09 (.11)
.09 (.06)
.09 (.08)
CU traits
(age 20)
.26 (.09)**
.04 (.21)
-.001 (.07)
-.0001 (.05)
.27 (.04)**
Any arrest/petition?
(adult)
.42 (.12)**
.61 (.23)**
.03 (.08)
-.004 (.05)
.08 (.06)
Any arrest/petition?
(adolescence)
Self-reported
delinquency
APD symptoms
N = 266; +p<.10, *p<.05, **p<.01. All tests two-tailed. Each box represents unstandardized regression coefficients with (SE). Self-reported delinquency and
APD symptoms were log transformed to account for their skew. Logistic regression was used for all binary outcomes and linear regression for all continuous
outcomes. Please note that as Table S2 was computed with new variables in a follow-up analysis, this dataset was imputed separately from all other results. The
pattern of all variables remained stable but estimates vary slightly with a second imputation of 5 datasets. All data reported here are pooled estimates from the 5
datasets. Aggression and rule-breaking dimensions were created from the Self-Report of Delinquency in a similar fashion to the methods reported in the methods
section: confirmatory factor analysis in Mplus was used to confirm a two factor solution in which specific aggression and rule breaking items loaded onto their
Subtypes of Antisocial Behavior – supplemental materials 5
respective factor with high loadings (i.e., >.6) and low loadings on the other factor. This model fit the data well χ2=446.64, p<.001; CFI=.93, RMSEA=.045. A
list of items on each factor is available upon request.
Table S3
Predicting Emerging Adult Outcomes Using a K-SADS Based Measure of Age of Onset
Outcome
Contrast Code
1: Presence of
AB
Contrast code
2: age of onset
of AB from
K-SADS
Step 1
Contrast Code
1: Presence of
AB
Contrast code
2: age of onset
of AB from
K-SADS
Aggressive
symptoms
Rule Breaking
Symptoms
CU traits
(age 17)
Step 2
.47 (.16)*
-.10 (.37)
.25 (.15)
-.05 (.46)
.34 (.30)
.31 (.16)+
.09 (.08)
.12 (.05)*
.02 (.18)
.03 (.06)
.01 (.17)+
.13 (.09)
.13 (.07)
-.02 (.03)
.14 (.03)**
.005 (.10)
.06 (.03)+
-.006 (.08)
.18 (.04)**
.09 (.03)*
-.02 (.02)
APD diagnosis
.34 (.13)*
.08 (.37)
.11 (.17)
.05 (.42)
.78 (.22)**
.01 (.20)
-.04 (.09)
Depression
.13 (.13)
-.06 (.57)
-.09 (.18)
-.13 (.55)
.46 (.21)*
.25 (.17)
-.15 (.11)
Substance
Abuse
Substance
Dependence
CU traits
(age 20)
.15 (.10)
-.30 (.33)
.01 (.13)
-.30 (.33)
.26 (.20)
.13 (.13)
.04 (.07)
.38 (.14)*
-.06 (.27)
.19 (.14)
-.05 (2.9)
.37 (.20)+
.17 (.13)
.03 (.09)
.22 (.09)*
-.20 (.26)
.10 (.10)
-.07 (.23)
-.11 (.15)
.15 (.12)
.25 (.05)**
.24 (.10)*
-.10 (.31)
.18 (.11)
-.08 (.30)
.08 (.17)
.07 (.14)
.04 (.06)
Any
arrest/petition?
(adolescence)
Self-reported
delinquency
APD symptoms
Any
arrest/petition?
(adult)
N = 266; +p<.10, *p<.05, **p<.01. All tests two-tailed. Each box represents unstandardized regression coefficients with (SE). Self-reported delinquency and
APD symptoms were log transformed to account for their skew. Logistic regression was used for all binary outcomes and linear regression for all continuous
outcomes. Please note that as this table was computed with new variables in a follow-up analysis, this dataset was imputed separately from all other results
Subtypes of Antisocial Behavior – supplemental materials 6
presented in the main manuscript. The pattern of all variables remained stable but estimates vary slightly with a second imputation of 5 datasets. All data reported
here are pooled estimates from the 5 datasets. To assess age of onset from the K-SADS we used the repeated measurement of this interview (i.e., at age 10, 11,
12, 15, 17) across adolescence to create an age of onset variable. As age 10 is the threshold for DSM-IV and 5 “early onset”, we coded youth into early onset
(CD diagnosis at age 10), adolescent onset (CD diagnosis at age 11, 12, 15, or 17, but not at 10) and a non-CD group (see Supplemental Methods above).
Subtypes of Antisocial Behavior – supplemental materials 7
Table S4
Predicting Emerging Adult Outcomes Using a CBCL Based Measure of Age of Onset
Outcome
Any
arrest/petition?
(adolescence)
N=223
Self-reported
delinquency
N=220
APD symptoms
N=220
APD diagnosis
N=221
Substance
Abuse
N=220
Substance
Dependence
N=221
CU traits
(age 20), N=218
Any
arrest/petition?
(adult), N=247
+
Contrast Code Contrast code
1: Presence of 2: age of onset
AB
of AB (CBCL)
Step 1
1.01 (.27)**
.14 (.53)
Contrast Code
1: Presence of
AB
Contrast code
2: age of onset
of AB (CBCL)
Aggressive
symptoms
Rule Breaking
Symptoms
CU traits
(age 17)
.66 (.32)*
.79 (.61)
Step 2
.93 (.32)**
.64 (.18)**
.15 (.07)*
.03 (.14)
.14 (.27)
-.10 (.14)
.35 (.26)
.18 (.09)*
.17 (.06)**
-.001 (.03)
.28 (.09)**
-.05 (.17)
.20 (.08)**
.11 (.15)
.25 (.05)**
.12 (.03)**
-.01 (.01)
.61 (.34)+
-.58 (.65)
.61 (.37)
-.15 (.70)
1.0 (.25)**
.12 (.18)
-.06 (.10)
.35 (.29)
-.09 (.57)
.12 (.32)
.41 (.62)
.61 (.23)**
.33 (.15)*
.07 (.07)
.35 (.35)
-.35 (.66)
.13 (.38)
.27 (.72)
.70 (.22)**
.32 (.16)*
.09 (.08)
.52 (.25)*
.45 (.48)
.24 (.23)
1.0 (.44)*
.09 (.15)
.19 (.10)+
.29 (.04)**
.37 (.23)
-.03 (.44)
.15 (.25)
.28 (.46)
.31 (.19)+
.24 (.13)+
.04 (.06)
p<.10, *p<.05, **p<.01. All tests two-tailed. Note that as SPSS can occasionally have difficulty using multiple imputation with sparse categories (i.e., early vs.
late onset from the CBCL), data could not by imputed and results using listwise deletion are presented. Each box represents unstandardized regression
coefficients with (SE). Self-reported delinquency and APD symptoms were log transformed to account for their skew. Logistic regression was used for all binary
outcomes and linear regression for all continuous outcomes. We created an age of onset variable using the parent report on the CBCL: If children scored in the
clinical range at 2 or more timepoints in childhood (age 3.5, 5.5, 6, 8) they were classified as early starters. If they were scored in the clinical range at 2 or more
timepoints during adolescence (age 10, 11, 12, 15, 17) and were not in the early onset group, they were classified as adolescent onset. Contrast codes were then
Subtypes of Antisocial Behavior – supplemental materials 8
created as described in the methods section. Estimates are not provided for Major Depression diagnosis as the logistical regression model was unstable and would
not converge.
Table S5
Overlap Between Age of Onset as Measured by Trajectory Groups Versus K-SADS CD Diagnosis Versus Parented-Rated CBCL Scores
K-SADS age of onset
Trajectory Group
Never CD diagnosis
Late Starting (CD diagnosis at
age 11 – 15, but not 10)
Early Starting (CD diagnosis at
age 10)
Low AB
133
8
2
Desisting
5
5
4
Late Starting/Moderate
35
11
1
Early Starting/High
5
19
3
These two sets of categories differ significantly from each other (Fisher’s exact test = 83.8, p < .001).
See caption to Table S3 for a description of how the K-SADS age of onset variable was created.
CBCL age of onset
Trajectory Group
Never high on AB
Late Starting
Early Starting
Low AB
161
5
5
Desisting
11
3
1
Late Starting/Moderate
45
4
5
Early Starting/High
26
1
1
These two sets of categories differ significantly from each other (Fisher’s exact test = 12.5, p < .05).
See caption to Table S4 for a description of how the CBCL age of onset variable was created.
K-SADS age of onset
CBCL age of onset
Never CD diagnosis
Late Starting (CD diagnosis at
age 11 – 15, but not 10)
Early Starting (CD diagnosis at
age 10)
Never high on AB
177
36
3
Late starting
2
6
5
Subtypes of Antisocial Behavior – supplemental materials 9
Early Starting
4
3
These two sets of categories differ significantly from each other (Fisher’s exact test = 48.3, p < .001).
4