© 2014 American Psychological Association 0021-843X/14/$12.00 DOI: 10.1037/a0036457
Journal of Abnonnal Psychology 2014, Vol. 123, No. 2, 406-411
BRIEF REPORT
Sex Differences in the Etiology of Psychopathic Traits in Youth Courtney A. Ficks, Lu Dong, and Irwin D. Waldman Emory University Few studies have examined the etiology of psychopathic traits in youth, and even fewer have tested whether the genetic and environmental influences underlying these traits differ for boys and girls. We tested for sex differences in the etiology of 3 trait dimensions—impulsivity, narcissism, and callousunemotionahty (CU)—previously found to underlie youth psychopathy in our sample. Using biométrie modeling we tested whether constraining the genetic and environmental influences for each dimension across sex reduced model fit. We also tested for qualitative sex differences in the influences underlying these dimensions by allowing the genetic and environmental correlations between opposite sex dizygotic twins to be less than their respective values in same-sex dizygotic twins. Although the magnitudes of the genetic and environmental influences underlying the CU and narcissistic trait dimensions did not differ for boys and girls, nonshared environmental influences contributed significantly greater variance to impulsive traits in boys. No qualitative sex differences were found in the influences underlying any of the 3 trait dimensions, suggesting that the same genes and environments contribute to these psychopathic traits in males and females. Keywords: sex difference, psychopathy, etiology, heritability
Larsson, 2008; Viding, Blair, Moffitt, & Plomin, 2005; Viding, Jones, Frick, Moffitt, & Plomin, 2008). Nonetheless, few studies have tested for sex differences in these etiological influences, and those that have have yielded mixed evidence. Forsman et al. (2008) reported sex differences in the phenotypic variances for grandiose/manipulative, callous-unemotional (CU), and impulsive/irresponsible traits, but not in the respective contributions of genetic or environmental influences (Forsman et al., 2008). In contrast, Bezdjian et al. (2010) reported higher heritability estimates for callous/disinhibited traits and lower heritability estimates for manipulative/deceitful traits in males. Similarly, Fontaine, Rijsdijk, McCrory, and Viding (2010) examined sex differences in the heritability of CU trait trajectories from late childhood to early adolescence and also found evidence for stronger additive genetic influences on CU traits in boys, but only for boys with high or increasing levels of CU traits over time (Fontaine et al., 2010). Overall, although there is some evidence supporting minimal sex differences in the heritability of psychopathic traits, stronger evidence is needed to inform the search for specific genetic and environmental risk factors and the development of behavioral or pharmacological treatment strategies for boys and girls whose behavior may put themselves or others at risk. The current study is the ftrst study to our knowledge to examine sex differences in the genetic and environmental influences underlying dimensions of the Antisocial Process Screening Device (APSD; Frick & Hare, 2001), one of the most commonly used measures of children's psychopathic traits. Although the factor structure of psychopathic traits in children is controversial, a recent study from our lab on the APSD found strong support for three psychopathic trait dimensions (Narcissism, Callous-Unemotional,
Psychopathy describes a collection of personality traits (e.g., superficial charm, narcissism, lack of empathy) and behaviors (e.g., aggression, manipulation of others, cheating) associated with the victimization of others for personal gain. Sex differences in the mean levels of psychopathic traits have been documented in adults (see Cale & Lilienfeld, 2002 for review) and in children (Dadds, Fraser, Frost, & Hawes, 2005; Sevecke, Pukrop, Kosson, & Krischer, 2009), such that males exhibit higher levels of psychopathic traits than females (Cale & Lilienfeld, 2002). Nevertheless, the evidence has been mixed, as a recent study found evidence for measurement and structural invariance across sex in a child sample, suggesting no sex differences in the latent mean levels of psychopathic traits (Dong et al., 2013). Other evidence regarding sex differences in psychopathy has suggested that psychopathic traits are a stronger predictor of relational aggression in girls (Marsee, Silverthorn, & Frick, 2005). Given this mixed evidence regarding the phenotypic sex differences in psychopathic traits, it is warranted to examine whether sex differences exist in the etiology of psychopathic traits. A handful of twin and family studies suggest that genes have a moderate to large influence, nonshared environment has a small to moderate influence, and shared environment has little or no influence on psychopathic traits (e.g., Bezdjian, Raine, Baker, & Lynam, 2010; Forsman, Lichtenstein, Andershed, &
Courtney A. Ficks, Lu Dong, and Irwin D. Waldman, Department of Psychology, Emory University. Correspondence concerning this article should be addressed to Courtney A. Ficks, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA 30322. E-mail: [email protected]
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ETIOLOGY OF PSYCHOPATHIC TRAITS IN YOUTH
Impulsivity) and full structural and measurement invariance across sex (Dong et al., 2013). In the current study, we tested for both quantitative sex differences (i.e., differences in the magnitude of genetic, shared environmental, or nonshared environmental influences) and qualitative sex differences (i.e., the degree to which the same genes or environments predispose to psychopathic traits in boys and girls).
Method The sample consisted of 885 twin pairs born in Georgia between 1980 and 1991. Detailed information regarding sample recruitment and participant response rate has been described previously (Ficks, Lahey, & Waldman, 2013). Table 1 shows the distribution of zygosity, sex, age, and ethnicity within the sample.
Measures Zygosity and demographics. Twin pair zygosity was determined via parental responses on a mailed questionnaire to eight items regarding the twins' physical similarity (e.g., "Is it hard for strangers to tell your twins apart based on their physical appearance?"). Each response was coded as 1 or 0 to indicate similarity or difference within the dyad, respectively. One zygosity score per twin pair was obtained by computing the mean of all 8 items. Mean scores less than 0.5 were considered indicative of dizygotic (DZ) status, and scores greater than or equal to 0.5 were considered indicative of monozygotic (MZ) status, given that a score of 0.5 appeared to be the optimal threshold for separating the zygosity distributions for MZs and DZs. Zygosity determination via parent ratings of such items has been shown to result in a cost-effective yet highly accurate determination of twin zygosity (i.e., 96%-99% correct assignment) when compared with DNA-based methods (Jackson, Snieder, Davis, & Treiber, 2001; Spitz et al., 1996). Table 1 Basic Demographics and the Distribution of Psychopathic Traits
Basic demographics Mean age (SD) in years Ethnicity Zygosity APSD Dimensions, M (SD) Callou.s-unemotionality (6 items) Impulsivity (5 items) Narcissism (7 items)
Males (N = 867)
Females (N = 903)
10.58 (3.20) 91% Caucasian 9% African American < 1 % Multiracial/other 55% DZ, 45% MZ
10.57(3.18) 90% Caucasian 8% African American 1% Multiracial/other 53% DZ, 47% MZ
7.90* (4.12) 4.41* (3.67*) 3.08* (3.59)
7.30 (4.23) 3.45 (3.22) 2.68 (3.55)
Note. DZ = dizygotic: MD = monozygotic: APSD = Antisocial Process Screening Device. APSD item scores ranged from 0 to 4, with higher scores indicating greater presence of the trait; item scores were summed to create each dimension. At the time of data collection, children within the sample ranged in age from 4.4 to 17.8 years. Information regarding the ethnicity of 69 individuals (4% of the sample) was not reported, and thus the percentages listed in the table represent individuals for whom ethnicity was known. * Significant sex difference (p < .05).
407
Psychopathic traits. Mothers rated their children's psychopathic traits using the APSD (Frick & Hare, 2001), a 20-item screening measure containing items that describe psychopathic traits in boys and girls. In a previous study using this sample (Dong, Wu, & Waldman, 2013; Frick, Bodin, & Barry, 2000), we found that a three-factor model (Frick et al., 2000) that included CU (e.g., "does not show emotions"), impulsive (e.g., "engages in risky activities"), and narcissistic (e.g., "becomes angry when corrected") trait dimensions provided a better fit than a two-factor model in both clinical and community-based samples. We also established full measurement and structural invariance across zygosity (MZ vs. DZ), sex (female vs. male), and age (préadolescents vs. adolescents; Dong et al., 2013; Frick et al., 2000). Although the APSD has traditionally utilized a 3-point (0 to 2) Likert-type response scale, the current study utilized an expanded 5-point response scale, allowing for mothers to indicate that items described their children "not at all" (0) to "very well" (4). The wording of the items was not changed in the process of expanding the response scale, and previous research has supported that the change from a 3-point to 5-point rating scale did not appear to influence the factor structure (Dong et al., 2013). The APSD scores have previously demonstrated moderate to high internal consistency and high stability for parent reports across a 4-year period (intraclass correlation coefficients = .71-.93 across scales; Frick, Kimonis, Dandreaux, & Farell, 2003). In the current study, the internal consistency for each of these dimensions was moderate to high (for boys, a = .53, .78, and .71 for CU, impulsivity, and narcissism, respectively; for girls, a = .54, .78, and .67 for CU, impulsivity, and narcissism, respectively), comparable to those from other studies.
Analyses Prior to model-fltting, all trait dimension scores were residualized on age, sex, age^, age X sex, and age^ X sex in order to account for mean level age and sex differences in these traits (McGue & Bouchard, 1984). Next, biométrie model-fltting was conducted in OpenMx (Boker et al., 2011), a structural equation modeling package for R (R Core Team, 2012). See Figure 1 for an illustration of the univariate biométrie model. A series of hierarchically nested models was used to determine the magnitude of each etiological influence (i.e., a^, c^ or d^, and e^) on the variance in each psychopathic trait dimension, as well as any sex differences in the relative contribution of each of these influences (i.e., quantitative sex differences). The genetic and shared environmental correlations (r^ and r,., respectively) for opposite sex dizygotic twin pairs were also estimated to determine the extent to which the same genes and/or environments influenced these traits for males and females (i.e., qualitative differences). The expected values of r^ are 1.0 and 0.5 for MZ and DZ twins, respectively, given no qualitative sex differences. If qualitative sex differences are present in the genetic influences on a trait, we would expect opposite sex DZ pairs to exhibit a genetic correlation of r^ < 0.5. Similarly, the expected value of r^. is 1.0 for MZ and DZ twins in the absence of qualitative sex differences. If qualitative sex differences are present in the shared environmental influences on a trait, we would expect opposite sex DZ pairs to exhibit a shared environmental correlation of r^ < 1.0. We therefore tested whether constraining r^ or r^. for opposite sex twin pairs to their expected values (0.5 and
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tested for more fine-grained distinctions within this hierarchy of models; see Table 2 notes for a more detailed description of the steps taken in these analyses.
Results Distribution of Psychopathic Traits Descriptive statistics for the sample, including basic demographics and the distribution of psychopathic traits, are reported in Table 1. There were no significant sex differences in age, i(1764) = .09, p = .93, or zygosity, x^(l,1770) = .62, p = .43. Males exhibited significantly higher levels of psychopathic traits across all three dimensions, including CU, /(1662) = 2.96, p = .003, impulsivity, r(1612.83) = 5.69, p < .0001, and narcissism, ?(1660) = 2.29, p = .02, and Levene's test revealed significantly greater variability in impulsivity in males than in females, F = 13.65, p = .0002.
Univariate Analysis
Figure 1. Univariate biométrie model. Paths a, c, and e represent contributions of latent genetic and environmental influences (al-e2) to measured traits in cotwins tl and t2. Coefficients r^ and r^ represent the genetic and shared environmental correlations, respectively, between cotwins. Quantitative sex differences are implied by significant differences in the a, c, and e paths between males and females. Qualitative sex differences are implied if r < 0.5 or r^ < 1.0 for opposite sex twins.
1.0, respectively) decreased model fit, which would imply qualitative sex differences in these traits. Goodness of fit was primarily judged using the Akaike information criterion (AIC) and the Bayesian information criterion (BIC), two commonly used indicators of model fit and parsimony (Akaike, 1974; Schwarz, 1978). Several additional fit indices, including the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root-meansquare residual (SRMR) were also calculated to provide more complete information regarding model fit. We used the following criteria to evaluate model fit: RMSEA s .08 for adequate fit and 0.95 and SRMR < .08 for good fit (Hu & Bentler, 1999). Similar to previous studies of sex differences in phenotypic development (Rhee et al., 2003; Wardle, Carnell, Haworth, & Plomin, 2008), we tested the following hierarchy of models; (a) a full sex-limitation model (Neale & Cardon, 1992) that allowed for quantitative sex differences in a, c or d, and e path estimates and also allowed for either r^. or r^ to be freely estimated; (b) a common effects model that allowed for quantitative sex differences but no qualitative sex differences; (c) a scalar sexlimitation model in which phenotypic variances for each trait were allowed to differ by sex but the variance components (a^, c^ or d^, and e^), and r^., and r^ were equated for boys and girls; and (d) a null model in which the variances, paths, r^, and r^ were all equated, allowing for neither quantitative nor qualitative sex differences in the etiology of these traits. We also
Parameter estimates and fit statistics from the univariate models for each APSD trait dimension are shown in Table 2. As expected, all residualized dimensional means could be equated for males and females. Variances could also be equated across sex for the CU and narcissism trait dimensions, but as suggested previously by the Levene's test, the variances for impulsivity could not be equated for males and females. For CU, narcissism, and impulsivity, the ACE and AE null effects models (which allowed for neither quantitative nor qualitative sex differences) and the ADE common effects model (which allowed for quantitative but not qualitative sex differences) respectively emerged as the best-fitting models, with parameter estimates indicating moderate to strong genetic influences on each of these trait dimensions. The estimated genetic and shared environmental correlations for opposite sex DZ twin pairs could be constrained to their expected values for each of the APSD trait dimensions without resulting in significantly reduced model fit, providing no support for qualitative sex differences in the genes or environments that predispose to psychopathic traits. In addition, constraining a, c, and e paths to be equal across sex for CU and narcissism did not reduce model fit, providing no evidence that the magnitude of these influences differed for males and females. In contrast, although the a and d paths within the common effects model could be equated across sex for impulsivity, suggesting similar additive and nonadditive genetic influences for boys and girls, equating the e path resulted in significantly reduced model fit, suggesting differences in the nonshared environmental infiuences for boys and girls. This parameter was significantly larger for males, consistent with the aforementioned finding of greater variance in this group. Nonshared environmental influences consequently accounted for a greater proportion of the total variance in impulsivity in males, resulting in slightly different a~, d^, and e^ standardized variance components for males and females. We compared the fit of this model to the fit of the scalar sex-limitation model in which the overall phenotypic variance for impulsivity was allowed to differ for males and females but all etiological influences were constrained to be quantitatively and qualitatively identical. According to the fit statistics, the scalar
ETIOLOGY OF PSYCHOPATHIC TRAITS IN YOUTH
409
Table 2 Standardized Parameter Estimates and Fit Statistics for Univariate Heterogeneity Models of Antisocial Process Screening Device (APSD) Dimensions Males Step
A'
CU la. Full ACE .52 lb. Full ADE .66 lc. Equate means .52 Id. Equate variances .52 2a. Constrain r^ to .5, estimate r^ .52 2b. Constrain r^ to .5, r^ to 1 .52 2c. Equate a .46 2d. Equate c .49 4a. Equate e .49 4b. Constrain c to 0 .69 4c. Constrain a to 0 — IMP la. Full ACE .63 lb. Full ADE .44 lc. Equate means .44 Id. Equate variances .37 2a. Constrain r^ to .5 .44 2b. Equate a .42 2c. Equate d .21 3. Scalar sex-limitation .25 4a. Equate e .24 4b. Constrain ¿ to 0 .59 NAR la. Full ACE .53 lb. Full ADE .58 lc. Equate means .53 la. Equate variances .52 2a. Constrain f^ to .5, estimate r,. .52 2b. Constrain r^ to .5, r^. to 1 .52 2c. Equate a .53 2d. Equate c .58 4a. Equate e .58 4b. Constrain c to 0 .63 4c. Constrain a to 0 —
.12 — .12 .12 .12 .12 .17 .19 .19 — .54 0 — — — — — — — — — .05 — .04 .04 .04 .04 .04 .04 .04 — .46
Females
D'
E'
A'
0 — — — — — — — — —
.36 .34 .36 .36 .36 .36 .37 .32 .32 .31 .46
.37 .71 .37 .37 .37 .37 .46 .49 .49 .69 —
.37 .36 .36 .40 .36 .37 .39= .31 .32 .41
.72 .18 .18 .22 .18 .54 .26 .25 .24 .73
.42 .42 .42 .43 .43 .43 .42 .38 .38 .37 .54
.58 .66 .58 .59 .59 .59 .53 .58 .58 .63 —
.19 .19 .23 .19 .20 .40 .44 .44 — 0 — — — — — — — — —
.34 — .33 .33 .33 .33 .24 .19 .19 — .54 0 — — — — — — — — — .08 — .08 .08 .08 .08 .12 .04 .04 — .46
D"
E'
X"
df
P
AIC
BIC
RMSEA
0 — — — — — — — — —
.30 .29 .30 .30 .30 .30 .29 .32 .32 .31 .46
16.00 24.62 16.33 16.36 16.36 16.36 17.54 20.85 20.85 26.42 54.59
16 16 17 17 17 18 19 20 21 22 22
.45 .08 .50 .50 .50 .57 .55 .41 .47 .23
Journal of Abnonnal Psychology 2014, Vol. 123, No. 2, 406-411
BRIEF REPORT
Sex Differences in the Etiology of Psychopathic Traits in Youth Courtney A. Ficks, Lu Dong, and Irwin D. Waldman Emory University Few studies have examined the etiology of psychopathic traits in youth, and even fewer have tested whether the genetic and environmental influences underlying these traits differ for boys and girls. We tested for sex differences in the etiology of 3 trait dimensions—impulsivity, narcissism, and callousunemotionahty (CU)—previously found to underlie youth psychopathy in our sample. Using biométrie modeling we tested whether constraining the genetic and environmental influences for each dimension across sex reduced model fit. We also tested for qualitative sex differences in the influences underlying these dimensions by allowing the genetic and environmental correlations between opposite sex dizygotic twins to be less than their respective values in same-sex dizygotic twins. Although the magnitudes of the genetic and environmental influences underlying the CU and narcissistic trait dimensions did not differ for boys and girls, nonshared environmental influences contributed significantly greater variance to impulsive traits in boys. No qualitative sex differences were found in the influences underlying any of the 3 trait dimensions, suggesting that the same genes and environments contribute to these psychopathic traits in males and females. Keywords: sex difference, psychopathy, etiology, heritability
Larsson, 2008; Viding, Blair, Moffitt, & Plomin, 2005; Viding, Jones, Frick, Moffitt, & Plomin, 2008). Nonetheless, few studies have tested for sex differences in these etiological influences, and those that have have yielded mixed evidence. Forsman et al. (2008) reported sex differences in the phenotypic variances for grandiose/manipulative, callous-unemotional (CU), and impulsive/irresponsible traits, but not in the respective contributions of genetic or environmental influences (Forsman et al., 2008). In contrast, Bezdjian et al. (2010) reported higher heritability estimates for callous/disinhibited traits and lower heritability estimates for manipulative/deceitful traits in males. Similarly, Fontaine, Rijsdijk, McCrory, and Viding (2010) examined sex differences in the heritability of CU trait trajectories from late childhood to early adolescence and also found evidence for stronger additive genetic influences on CU traits in boys, but only for boys with high or increasing levels of CU traits over time (Fontaine et al., 2010). Overall, although there is some evidence supporting minimal sex differences in the heritability of psychopathic traits, stronger evidence is needed to inform the search for specific genetic and environmental risk factors and the development of behavioral or pharmacological treatment strategies for boys and girls whose behavior may put themselves or others at risk. The current study is the ftrst study to our knowledge to examine sex differences in the genetic and environmental influences underlying dimensions of the Antisocial Process Screening Device (APSD; Frick & Hare, 2001), one of the most commonly used measures of children's psychopathic traits. Although the factor structure of psychopathic traits in children is controversial, a recent study from our lab on the APSD found strong support for three psychopathic trait dimensions (Narcissism, Callous-Unemotional,
Psychopathy describes a collection of personality traits (e.g., superficial charm, narcissism, lack of empathy) and behaviors (e.g., aggression, manipulation of others, cheating) associated with the victimization of others for personal gain. Sex differences in the mean levels of psychopathic traits have been documented in adults (see Cale & Lilienfeld, 2002 for review) and in children (Dadds, Fraser, Frost, & Hawes, 2005; Sevecke, Pukrop, Kosson, & Krischer, 2009), such that males exhibit higher levels of psychopathic traits than females (Cale & Lilienfeld, 2002). Nevertheless, the evidence has been mixed, as a recent study found evidence for measurement and structural invariance across sex in a child sample, suggesting no sex differences in the latent mean levels of psychopathic traits (Dong et al., 2013). Other evidence regarding sex differences in psychopathy has suggested that psychopathic traits are a stronger predictor of relational aggression in girls (Marsee, Silverthorn, & Frick, 2005). Given this mixed evidence regarding the phenotypic sex differences in psychopathic traits, it is warranted to examine whether sex differences exist in the etiology of psychopathic traits. A handful of twin and family studies suggest that genes have a moderate to large influence, nonshared environment has a small to moderate influence, and shared environment has little or no influence on psychopathic traits (e.g., Bezdjian, Raine, Baker, & Lynam, 2010; Forsman, Lichtenstein, Andershed, &
Courtney A. Ficks, Lu Dong, and Irwin D. Waldman, Department of Psychology, Emory University. Correspondence concerning this article should be addressed to Courtney A. Ficks, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA 30322. E-mail: [email protected]
406
ETIOLOGY OF PSYCHOPATHIC TRAITS IN YOUTH
Impulsivity) and full structural and measurement invariance across sex (Dong et al., 2013). In the current study, we tested for both quantitative sex differences (i.e., differences in the magnitude of genetic, shared environmental, or nonshared environmental influences) and qualitative sex differences (i.e., the degree to which the same genes or environments predispose to psychopathic traits in boys and girls).
Method The sample consisted of 885 twin pairs born in Georgia between 1980 and 1991. Detailed information regarding sample recruitment and participant response rate has been described previously (Ficks, Lahey, & Waldman, 2013). Table 1 shows the distribution of zygosity, sex, age, and ethnicity within the sample.
Measures Zygosity and demographics. Twin pair zygosity was determined via parental responses on a mailed questionnaire to eight items regarding the twins' physical similarity (e.g., "Is it hard for strangers to tell your twins apart based on their physical appearance?"). Each response was coded as 1 or 0 to indicate similarity or difference within the dyad, respectively. One zygosity score per twin pair was obtained by computing the mean of all 8 items. Mean scores less than 0.5 were considered indicative of dizygotic (DZ) status, and scores greater than or equal to 0.5 were considered indicative of monozygotic (MZ) status, given that a score of 0.5 appeared to be the optimal threshold for separating the zygosity distributions for MZs and DZs. Zygosity determination via parent ratings of such items has been shown to result in a cost-effective yet highly accurate determination of twin zygosity (i.e., 96%-99% correct assignment) when compared with DNA-based methods (Jackson, Snieder, Davis, & Treiber, 2001; Spitz et al., 1996). Table 1 Basic Demographics and the Distribution of Psychopathic Traits
Basic demographics Mean age (SD) in years Ethnicity Zygosity APSD Dimensions, M (SD) Callou.s-unemotionality (6 items) Impulsivity (5 items) Narcissism (7 items)
Males (N = 867)
Females (N = 903)
10.58 (3.20) 91% Caucasian 9% African American < 1 % Multiracial/other 55% DZ, 45% MZ
10.57(3.18) 90% Caucasian 8% African American 1% Multiracial/other 53% DZ, 47% MZ
7.90* (4.12) 4.41* (3.67*) 3.08* (3.59)
7.30 (4.23) 3.45 (3.22) 2.68 (3.55)
Note. DZ = dizygotic: MD = monozygotic: APSD = Antisocial Process Screening Device. APSD item scores ranged from 0 to 4, with higher scores indicating greater presence of the trait; item scores were summed to create each dimension. At the time of data collection, children within the sample ranged in age from 4.4 to 17.8 years. Information regarding the ethnicity of 69 individuals (4% of the sample) was not reported, and thus the percentages listed in the table represent individuals for whom ethnicity was known. * Significant sex difference (p < .05).
407
Psychopathic traits. Mothers rated their children's psychopathic traits using the APSD (Frick & Hare, 2001), a 20-item screening measure containing items that describe psychopathic traits in boys and girls. In a previous study using this sample (Dong, Wu, & Waldman, 2013; Frick, Bodin, & Barry, 2000), we found that a three-factor model (Frick et al., 2000) that included CU (e.g., "does not show emotions"), impulsive (e.g., "engages in risky activities"), and narcissistic (e.g., "becomes angry when corrected") trait dimensions provided a better fit than a two-factor model in both clinical and community-based samples. We also established full measurement and structural invariance across zygosity (MZ vs. DZ), sex (female vs. male), and age (préadolescents vs. adolescents; Dong et al., 2013; Frick et al., 2000). Although the APSD has traditionally utilized a 3-point (0 to 2) Likert-type response scale, the current study utilized an expanded 5-point response scale, allowing for mothers to indicate that items described their children "not at all" (0) to "very well" (4). The wording of the items was not changed in the process of expanding the response scale, and previous research has supported that the change from a 3-point to 5-point rating scale did not appear to influence the factor structure (Dong et al., 2013). The APSD scores have previously demonstrated moderate to high internal consistency and high stability for parent reports across a 4-year period (intraclass correlation coefficients = .71-.93 across scales; Frick, Kimonis, Dandreaux, & Farell, 2003). In the current study, the internal consistency for each of these dimensions was moderate to high (for boys, a = .53, .78, and .71 for CU, impulsivity, and narcissism, respectively; for girls, a = .54, .78, and .67 for CU, impulsivity, and narcissism, respectively), comparable to those from other studies.
Analyses Prior to model-fltting, all trait dimension scores were residualized on age, sex, age^, age X sex, and age^ X sex in order to account for mean level age and sex differences in these traits (McGue & Bouchard, 1984). Next, biométrie model-fltting was conducted in OpenMx (Boker et al., 2011), a structural equation modeling package for R (R Core Team, 2012). See Figure 1 for an illustration of the univariate biométrie model. A series of hierarchically nested models was used to determine the magnitude of each etiological influence (i.e., a^, c^ or d^, and e^) on the variance in each psychopathic trait dimension, as well as any sex differences in the relative contribution of each of these influences (i.e., quantitative sex differences). The genetic and shared environmental correlations (r^ and r,., respectively) for opposite sex dizygotic twin pairs were also estimated to determine the extent to which the same genes and/or environments influenced these traits for males and females (i.e., qualitative differences). The expected values of r^ are 1.0 and 0.5 for MZ and DZ twins, respectively, given no qualitative sex differences. If qualitative sex differences are present in the genetic influences on a trait, we would expect opposite sex DZ pairs to exhibit a genetic correlation of r^ < 0.5. Similarly, the expected value of r^. is 1.0 for MZ and DZ twins in the absence of qualitative sex differences. If qualitative sex differences are present in the shared environmental influences on a trait, we would expect opposite sex DZ pairs to exhibit a shared environmental correlation of r^ < 1.0. We therefore tested whether constraining r^ or r^. for opposite sex twin pairs to their expected values (0.5 and
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tested for more fine-grained distinctions within this hierarchy of models; see Table 2 notes for a more detailed description of the steps taken in these analyses.
Results Distribution of Psychopathic Traits Descriptive statistics for the sample, including basic demographics and the distribution of psychopathic traits, are reported in Table 1. There were no significant sex differences in age, i(1764) = .09, p = .93, or zygosity, x^(l,1770) = .62, p = .43. Males exhibited significantly higher levels of psychopathic traits across all three dimensions, including CU, /(1662) = 2.96, p = .003, impulsivity, r(1612.83) = 5.69, p < .0001, and narcissism, ?(1660) = 2.29, p = .02, and Levene's test revealed significantly greater variability in impulsivity in males than in females, F = 13.65, p = .0002.
Univariate Analysis
Figure 1. Univariate biométrie model. Paths a, c, and e represent contributions of latent genetic and environmental influences (al-e2) to measured traits in cotwins tl and t2. Coefficients r^ and r^ represent the genetic and shared environmental correlations, respectively, between cotwins. Quantitative sex differences are implied by significant differences in the a, c, and e paths between males and females. Qualitative sex differences are implied if r < 0.5 or r^ < 1.0 for opposite sex twins.
1.0, respectively) decreased model fit, which would imply qualitative sex differences in these traits. Goodness of fit was primarily judged using the Akaike information criterion (AIC) and the Bayesian information criterion (BIC), two commonly used indicators of model fit and parsimony (Akaike, 1974; Schwarz, 1978). Several additional fit indices, including the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root-meansquare residual (SRMR) were also calculated to provide more complete information regarding model fit. We used the following criteria to evaluate model fit: RMSEA s .08 for adequate fit and 0.95 and SRMR < .08 for good fit (Hu & Bentler, 1999). Similar to previous studies of sex differences in phenotypic development (Rhee et al., 2003; Wardle, Carnell, Haworth, & Plomin, 2008), we tested the following hierarchy of models; (a) a full sex-limitation model (Neale & Cardon, 1992) that allowed for quantitative sex differences in a, c or d, and e path estimates and also allowed for either r^. or r^ to be freely estimated; (b) a common effects model that allowed for quantitative sex differences but no qualitative sex differences; (c) a scalar sexlimitation model in which phenotypic variances for each trait were allowed to differ by sex but the variance components (a^, c^ or d^, and e^), and r^., and r^ were equated for boys and girls; and (d) a null model in which the variances, paths, r^, and r^ were all equated, allowing for neither quantitative nor qualitative sex differences in the etiology of these traits. We also
Parameter estimates and fit statistics from the univariate models for each APSD trait dimension are shown in Table 2. As expected, all residualized dimensional means could be equated for males and females. Variances could also be equated across sex for the CU and narcissism trait dimensions, but as suggested previously by the Levene's test, the variances for impulsivity could not be equated for males and females. For CU, narcissism, and impulsivity, the ACE and AE null effects models (which allowed for neither quantitative nor qualitative sex differences) and the ADE common effects model (which allowed for quantitative but not qualitative sex differences) respectively emerged as the best-fitting models, with parameter estimates indicating moderate to strong genetic influences on each of these trait dimensions. The estimated genetic and shared environmental correlations for opposite sex DZ twin pairs could be constrained to their expected values for each of the APSD trait dimensions without resulting in significantly reduced model fit, providing no support for qualitative sex differences in the genes or environments that predispose to psychopathic traits. In addition, constraining a, c, and e paths to be equal across sex for CU and narcissism did not reduce model fit, providing no evidence that the magnitude of these influences differed for males and females. In contrast, although the a and d paths within the common effects model could be equated across sex for impulsivity, suggesting similar additive and nonadditive genetic influences for boys and girls, equating the e path resulted in significantly reduced model fit, suggesting differences in the nonshared environmental infiuences for boys and girls. This parameter was significantly larger for males, consistent with the aforementioned finding of greater variance in this group. Nonshared environmental influences consequently accounted for a greater proportion of the total variance in impulsivity in males, resulting in slightly different a~, d^, and e^ standardized variance components for males and females. We compared the fit of this model to the fit of the scalar sex-limitation model in which the overall phenotypic variance for impulsivity was allowed to differ for males and females but all etiological influences were constrained to be quantitatively and qualitatively identical. According to the fit statistics, the scalar
ETIOLOGY OF PSYCHOPATHIC TRAITS IN YOUTH
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Table 2 Standardized Parameter Estimates and Fit Statistics for Univariate Heterogeneity Models of Antisocial Process Screening Device (APSD) Dimensions Males Step
A'
CU la. Full ACE .52 lb. Full ADE .66 lc. Equate means .52 Id. Equate variances .52 2a. Constrain r^ to .5, estimate r^ .52 2b. Constrain r^ to .5, r^ to 1 .52 2c. Equate a .46 2d. Equate c .49 4a. Equate e .49 4b. Constrain c to 0 .69 4c. Constrain a to 0 — IMP la. Full ACE .63 lb. Full ADE .44 lc. Equate means .44 Id. Equate variances .37 2a. Constrain r^ to .5 .44 2b. Equate a .42 2c. Equate d .21 3. Scalar sex-limitation .25 4a. Equate e .24 4b. Constrain ¿ to 0 .59 NAR la. Full ACE .53 lb. Full ADE .58 lc. Equate means .53 la. Equate variances .52 2a. Constrain f^ to .5, estimate r,. .52 2b. Constrain r^ to .5, r^. to 1 .52 2c. Equate a .53 2d. Equate c .58 4a. Equate e .58 4b. Constrain c to 0 .63 4c. Constrain a to 0 —
.12 — .12 .12 .12 .12 .17 .19 .19 — .54 0 — — — — — — — — — .05 — .04 .04 .04 .04 .04 .04 .04 — .46
Females
D'
E'
A'
0 — — — — — — — — —
.36 .34 .36 .36 .36 .36 .37 .32 .32 .31 .46
.37 .71 .37 .37 .37 .37 .46 .49 .49 .69 —
.37 .36 .36 .40 .36 .37 .39= .31 .32 .41
.72 .18 .18 .22 .18 .54 .26 .25 .24 .73
.42 .42 .42 .43 .43 .43 .42 .38 .38 .37 .54
.58 .66 .58 .59 .59 .59 .53 .58 .58 .63 —
.19 .19 .23 .19 .20 .40 .44 .44 — 0 — — — — — — — — —
.34 — .33 .33 .33 .33 .24 .19 .19 — .54 0 — — — — — — — — — .08 — .08 .08 .08 .08 .12 .04 .04 — .46
D"
E'
X"
df
P
AIC
BIC
RMSEA
0 — — — — — — — — —
.30 .29 .30 .30 .30 .30 .29 .32 .32 .31 .46
16.00 24.62 16.33 16.36 16.36 16.36 17.54 20.85 20.85 26.42 54.59
16 16 17 17 17 18 19 20 21 22 22
.45 .08 .50 .50 .50 .57 .55 .41 .47 .23
