Dynamics of Psychopathy and Moral Disengagement in the Etiology of ...

Article

Dynamics of Psychopathy and Moral Disengagement in the Etiology of Crime

Youth Violence and Juvenile Justice 2014, Vol. 12(4) 295-314 ª The Author(s) 2013 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1541204013506919 yvj.sagepub.com

Matt DeLisi1, David J. Peters1, Tamerria Dansby1, Michael G. Vaughn2, Jeffrey J. Shook3, and Andy Hochstetler1

Abstract Moral engagement produces strong emotions that help individuals refrain from serious criminal behavior, but what if a youth is unable to experience these emotions. Based on a sample of adjudicated delinquents and using a series of structural equation models, we test whether moral disengagement varies by level of psychopathy in relation to criminal onset and assess this stability across gender. Psychopathic personality features, moral disengagement, and family stress intermixed in diverse ways depending on the severity of psychopathic personality and gender. At higher levels of psychopathy, the effect of psychopathy on criminal onset was unmediated. However, moral disengagement was found to have mediating effects on criminal onset at lower levels of psychopathy. Study findings lend support to the hypothesis that due to core emotional deficits, youth high on psychopathy are unaffected by the mechanisms of moral disengagement. Results are discussed in light of theories of morality and psychopathy and the treatment of moral deficits among youthful offenders. Keywords crime, criminal onset, juvenile psychopathy, morality, moral engagement, psychopathy traits

Introduction A fundamental reason why most individuals refrain from perpetrating serious criminal behavior relates to morality. The negative valence of the criminal act, the potential consequences from the criminal justice system, and the harm experienced by the victim are generally viewed negatively and serve to dissuade or deter antisocial conduct. Across the terrain of philosophy, social science, behavioral science, sociology, psychology, and criminology, an array of theoretical and conceptual models has been advanced to account for the relationship between moral development and behavior (Haidt, 2008; Hauser, 2006; Wilson, 1993). Transcending the contributions of Plato, Aristotle, Kant, 1

Iowa State University, Ames, IA, USA Saint Louis University, School of Social Work, MO, USA 3 University of Pittsburgh, School of Social Work, Pittsburgh, PA, USA 2

Corresponding Author: Matt DeLisi, Iowa State University, 203A East Hall, Ames, IA 50010, USA. Email: [email protected]

Downloaded from yvj.sagepub.com at CAPELLA UNIVERSITY on February 9, 2015

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Mill, Durkheim, Piaget, Kohlberg, Bandura, and criminological speaking, Sykes and Matza, the cardinal feature of morality is that individuals undergo moral development where they learn to modify their self-motivated desires both in favor of the common good and in recognition of the negative effects that their conduct could have on others. One of the most influential approaches in the morality-behavior arena is Bandura’s (1986, 1991, 1999) social cognitive theory. According to Bandura (1999, p. 193), ‘‘moral reasoning is translated into actions through self-regulatory mechanisms rooted in moral standards and self-sanctions by which moral agency is exercised. The moral self is thus embedded in a broader, sociocognitive self-theory encompassing self-organizing, proactive, self-reflecting, and self-regulative mechanisms. These self-referent processes provide the motivational as well as the cognitive regulators of moral conduct.’’ In this sense, morality involves dynamics interplay between the individual and the environment. Individuals can disengage from morality depending on the social context. Moral disengagement refers to an individual’s tendency to use mechanisms conducive to a selective disengagement of moral censure. Moral disengagement allows people to engage in self-serving behaviors that are in contrast with moral principles while not experiencing negative self-evaluative emotions such as guilt, shame, or remorse.1 Individuals who display higher levels of moral disengagement are likely to also display higher levels of antisocial conduct. Moral disengagement, moral emotions, and various forms of antisocial conduct (e.g., aggression, delinquency, violence, crime) have been found among diverse samples including elementary school children in Italy (Pozzoli, Gini, & Vieno, 2012), Danish middle school students (Obermann, 2011), children and adolescents from impoverished socioeconomic backgrounds (Hyde, Shaw, & Moilanen, 2010), adult male prison inmates selected from the United Kingdom (Wood, Moir, & James, 2009), serious juvenile delinquents in Scotland and the United States (Kiriakidis, 2008; Shulman, Cauffman, Piquero, & Fagan, 2011), and a comparative study involving adult jail inmates, college students, early adolescents, and at-risk middle adolescents from the United States (Stuewig, Tangney, Heigel, Harty, & McCloskey, 2010). In a study of 152 male delinquents selected from a detention center in Scotland, Kiriakidis (2008) found that delinquents scored significantly higher on a moral disengagement scale compared to a community sample of adolescents. Youths with higher moral disengagement were more likely to come from homes serviced by a social worker, had more unstable living situations, and had higher levels of drug use. More importantly, morality has predictive effects on delinquency even while controlling for other known correlates of adolescent antisocial behavior. Drawing on data from nearly 400 adolescents, Paciello, Fida, Tramontano, Lupinetti, and Caprara (2008) identified four developmental pathways of moral disengagement and antisociality. These included a group that was almost always moral, a group with slight moral disengagement at age 14 that declined quickly thereafter, a group that had moderately high moral disengagement until age 16 that declined quickly thereafter, and finally, a small group that had moderate to high levels of moral disengagement across adolescence and into adulthood. Youths with the greatest levels of moral disengagement were the most delinquent, the most aggressive, and committed the most acts of violence compared to youths with lower levels of moral disengagement. Youths with lower moral disengagement were more likely to feel guilty about their delinquent behavior. The most severe group in terms of moral disengagement was also rated by their peers as the most aggressive (also see Fontaine, Fida, Paciello, Tisak, & Caprara, 2014).2 Others have similarly found that moral disengagement is an outcome of multiple child and family risk factors and that it plays a significant role in predicting antisocial behavior (Hyde et al., 2010). To summarize, morality serves to buffer individuals from criminal offending in part due to the negative emotional states that are experienced for committing a behavioral transgression (Rebellon, Piquero, Piquero, & Tibbetts, 2010; Tangney, Stuewig, & Hafez, 2011; Tibbetts, 1997, 2003).


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Antisocial behavior produces feelings of shame, guilt, and remorse that are aversive and unpleasant. But what if an individual is unable to experience negative emotions? Psychopathic personality is characterized by affective, cognitive, and behavioral features where there are deficits in shame, guilt, and remorse, and in the case of primary psychopathy, an absence of these emotions.

Psychopathy and Moral Disengagement Psychopathic personality is characterized by a constellation of interpersonal, affective, lifestyle, and behavioral characteristics that manifest in wide-ranging antisocial behaviors (Cleckley, 1941; DeLisi, 2009; Hare & Neumann, 2008; Ribeiro da Silva, Rijo, & Salekin, 2012; Tuvblad, Bezdjian, Raine, & Baker, 2013). Interpersonally, psychopaths are characterized by glib or superficial charm, narcissism or grandiose self-worth, pathological lying, and conning/manipulation. Affectively, psychopaths are characterized by callousness and lack of empathy, failure to accept responsibility, shallow emotion, and lack of guilt or remorselessness. In terms of lifestyle, psychopaths lack realistic life goals, have a parasitic orientation, and are globally irresponsible, impulsive, and stimulation seeking. Behaviorally, psychopaths have poor behavioral control, evince early behavior problems, engage in juvenile delinquency, are criminally versatile, and have records of noncompliance/revocation of conditional release. When charged with their crimes, psychopathic individuals present as guiltless and are prone to externalize blame.3 The emotional incapacity of psychopathic personality directly relates to moral disengagement because it prevents psychopathic individuals from empathically relating to others. The emotional connectedness to others is required to set into motion the negative or self-conscious emotions, such as guilt or shame. In an explication of early theories of psychopathy, Blackburn (2006, p. 37) observed, ‘‘Role-taking ability enables sensitivity to the reactions of others and is basic to selfcriticism and self-control . . . . Psychopathic traits, such as ignoring the rights of others, impulsivity, emotional poverty, and inability to form lasting interpersonal attachments are behavioral manifestations that could be accounted for by a pathological deficiency in role-taking ability . . . . Inability to experience the social emotions of embarrassment, contrition, and groups loyalty, and lack of selfcontrol are all a consequence of this deficit.’’ In other words, although nonpsychopathic individuals engage in a variety of mechanisms to moral disengagement, psychopathic individuals already present core deficits in moral engagement, empathy, and emotionally connecting with others. Prior research has shown interrelations between antisocial conduct, moral disengagement, and psychopathic personality features where psychopathy scores are positively related to moral disengagement (O’Kane, Fawcett, & Blackburn, 1996; Shulman et al., 2011). In turn, there is evidence that youths with psychopathic personalities characterized by greater impulsivity, narcissism, callousness, guiltlessness, and emotional coldness are not only more antisocial but also more likely to engage in more serious forms of interpersonal violence (Vaughn & DeLisi, 2008; Vaughn, Howard, & DeLisi, 2008). More recent research is even more illustrative. Using data from the Pathways to Desistance Study, Shulman, Cauffman, Piquero, and Fagan (2011) reported significant associations between callous and unemotional traits, moral disengagement, and delinquency. In addition, they found that reductions in moral disengagement—or stated differently, improved moral functioning—were associated with reductions in delinquency. In this respect, moral disengagement, offending, and psychopathic features interact in complex ways. In a novel experimental study, Young, Koenigs, Kruepke, and Newman (2012) tested 20 criminal psychopaths and 25 criminal nonpsychopaths on a moral judgment task where participants evaluated accidental harms, attempted harms, intentional harms, and neutral acts. In cases where an individual unintentionally harmed another, psychopathic offenders viewed these actions as more morally


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permissible. In other words, psychopathic offenders showed impairment at emotionally experiencing the harm of the victim (also see, Gao & Tang, 2013).

Current Focus Given the emotional deficits identified in prior investigations of youth scoring high on measures of psychopathy, it seems reasonable that moral engagement may be related to level of psychopathy. If youth high in psychopathic traits are already unaffected by the mechanisms of moral disengagement due to their core emotional deficits, then the mediating power of this construct may be attenuated. In contrast, youth with lower scores on measures of psychopathic traits may experience moral disengagement in a way that mediates their involvement in rule breaking. We test this hypothesis in a series of structural equation models (SEMs) and also analyze data separately for males and females. Since very little research on gender differences with respect to the interrelationships between psychopathic traits, moral disengagement, and criminal careers has accrued, these analyses are considered exploratory.

Method Participants and Procedures The data are derived from a nonprobability sample of adolescent youths in two (one male only and one female only) long-term residential placement facilities for juvenile offenders in Western Pennsylvania (Shook, Vaughn, Goodkind, & Johnson, 2011). Data collection at the boys’ facility occurred from June 2009 through August 2009 and yielded 152 participants. Criteria for boys being enrolled in the study included the age between 14 and 18 years and having been in the facility between 3 and 12 months when recruitment started. Data collection at the girls’ facility occurred over a 4-month period from October 2009 until February 2010. This facility is much smaller than the boys’ facility, so we attempted to include all the girls in the facility and all of those that entered during the data collection period. This procedure yielded 100 participants. The youth in this sample are extensively involved in diverse forms of antisocial conduct and have commensurately extensive juvenile justice histories (DeLisi, Neppl, Lohman, Vaughn, & Shook, 2013; Shook et al., 2011). Data were collected in accordance with protocols approved by the institutional review board at the University of Pittsburgh. After the study was described by facility staff and the youth expressed interest, a supervisor at the facilities provided approval for the youth to take part in the study and the youth were referred to research staff. Prior to administering the instrument, the interviewer explained the purpose of the study and received assent from each youth (consent from those 18 and 19 years old). Structured one-on-one interviews were carried out by trained graduate students using computer-assisted survey interview (CASI) techniques. Interviewers completed an intensive 1-day training session and an interview editor was on-site as youth were interviewed to minimize interviewer omissions and errors. All interviews were conducted in rooms that provided private areas where confidential interviews could be conducted simultaneously with between three to five youth. The CASI data collection procedures allowed the respondent to have each question read to them supplemented by response cards. During the interviews, one on-site data editor helped answer any questions and provided quality control to data collection procedures. More than 95% of those referred to the research team assented to and completed the interview at both facilities. Overall, the characteristics of the study sample are representative of previous studies of residentially incarcerated youth nationally, with regard to average age, race and ethnicity, and offense histories and in terms of their social, behavioral, and delinquency histories (Caldwell, McCormick, Wolfe, & Umstead, 2012; Garcia &


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Lane, 2012; Reynolds, Tarter, Kirisci, & Clark, 2011; Sedlak & Bruce, 2010; Trulson, Haerle, DeLisi, & Marquart, 2011).

Measures Criminal Onset. The Criminal Onset Index (COI) is a latent variable that was measured using 3 items from the Multidimensional Residential Youth Inventory (MRYI; Shook et al., 2011). RY1 is the age at first rule violation (mean [M] ¼ 12.02 years, standard deviation [SD] ¼ 2.76, range ¼ 5–17) where participants were asked ‘‘How old were you when you first violated any of the above rules or laws?’’ The list refers to the 14-item Self-Report of Delinquency (SRD). This measure assesses violent and nonviolent delinquent offending in the 12 months prior to residential placement. The SRD version employed was modeled after a similar measure used in the National Youth Survey (Elliott, Huizinga, & Menard, 1989). Delinquent items include a range of property, drug, violent, offenses. RY2 is the age at first police contact (M ¼ 12.82, SD ¼ 2.26, range ¼ 5–17) where participants were asked ‘‘How old were you when you had your first contact with the police?’’ and RY3 is the age at first juvenile court referral (M ¼ 14.00, SD ¼ 1.73, range ¼ 9–17), where participants were asked ‘‘At what age were you first referred to the juvenile court?’’ Moral Disengagement. The Moral Disengagement Index (MDI) is used to measure the youth’s moral functioning. The 15-item measure is derived from the Mechanisms of Moral Disengagement scale (Bandura, Barbaranelli, Caprara, & Pastorelli, 1996), which is a widely used measure of moral disengagement. The MDI (M ¼ 55.52, SD ¼ 6.74, range ¼ 30–75) showed adequate reliability with the current data (a ¼ .77). The scale contains items such as ‘‘Some people deserve to be treated like animals,’’ which is scored as 1 ¼ strongly agree, 2 ¼ agree, 3 ¼ neither agree nor disagree, 4 ¼ disagree, and 5 ¼ strongly disagree. Lower values reflect greater moral disengagement. Psychopathic Personality. Psychopathic features are assessed using the Youth Psychopathic traits Inventory (YPI; Andershed, Herr, Stattin, & Levander, 2002) total score (M ¼ 105.74, SD ¼ 20.92, range ¼ 53–189). The YPI is a 50-item self-report. Reliability and validity of this instrument in assessing psychopathic features in children and adolescents are strong (Andershed et al., 2002; Vaughn et al., 2008). In the current sample, the YPI possessed good internal consistency reliability (a ¼ .90). Family Stress. The Family Stress Index (FSI) is derived from the Childhood Trauma Questionnaire (CTQ; Bernstein & Fink, 1998) and measures instability, ‘‘My parents were too drunk or high to take care of the family,’’ and ‘‘I lived with different people at different times (like different relatives or foster families),’’ and neglect ‘‘I spent time out of the house and no one knew where I was.’’ Internal consistency reliability in the present sample was adequate (a ¼ .68). Family stress was included since family factors are importantly related to the delinquent development (Beaver, Shutt, Vaughn, DeLisi, & Wright, 2012; Borduin & Ronis, 2012; Diamond, Morris, & Caudill, 2011; Elliott et al., 1989; Sedlak & Brice, 2010).

Statistical Analysis Previous research indicates that the effect of psychopathy on various outcomes differs depending on its base level, especially when analyzing subpopulations that are not representative of the general population (cf., Cox et al., 2013; Dyck, Campbell, Schmidt, & Wershler, 2013; Edens, Marcus, Lilienfeld, & Poythress, 2006; Harris, Rice, & Quinsey, 1994; Marcus, Lilienfeld, Edens, & Poythress, 2006; Skilling, Quinsey, & Craig, 2001). For example, in general population samples the increase in psychopathy between the 40th and 60th percentiles is generally the same as the increase


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1

1

MDI

11 11

1

YPI

21

2

1

2

COI

21 12

21

FSI 22

1

2

22

1

21

0

2

RY1

RY2

1

1 1

31 3

RY3 1

2

3

Figure 1. Model predicting youth criminal onset (COI) and moral disengagement (MDI). COI ¼ Criminal Onset Index; MDI ¼ Moral Disengagement Index.

between the 70th and 90th percentiles. However, in high-risk samples, there may be little difference in psychopathy scores in the middle percentiles, while very large differences may exist in the lower and upper percentiles. In this data the effect of psychopathy on criminal onset is more pronounced at the tails of the distribution, with a moderate effect (b* ¼ 0.223) for the bottom third, no effect (b* ¼ 0.097) for the middle third, and a stronger effect (b* ¼ 0.448) for the top third of cases. To better understand these effects prior to main analyses, the sample was divided into three risk groups based on z-scores on the youth psychopathy index. Persons whose scores fall 1 SD or more below the mean are considered low psychopathy (n ¼ 85), those with scores falling 1 SD or more above the mean are considered high psychopathy (n ¼ 70), and the reminder as average psychopathy (n ¼ 97). This study relied upon SEM as the primary analytic technique. SEMs are used to specify relationships between both manifest and latent variables. SEMs combine path analysis and factor analysis to allow modeling of multiple dependent variables, estimation of direct and indirect effects, measurement of unobserved variables, and estimation of measurement errors. These properties are especially important in criminological research, where complex relationships between latent concepts need to be analyzed. The technique is used to test whether a proposed causal structure is supported by the data, whereby the SEM model attempts to replicate the observed correlations between variables. A good fitting path model means that the replicated correlations closely match the observed correlations in the data (Kline, 2011). In SEM, the focus is on the entire fit of the model, rather than the significance of individual parameters (Bartholomew, 2012). Thus, models parameters are generally interpreted on effect size only rather than on statistical significance (Jo¨reskog, 1993). The path diagram is presented in Figure 1.4 SEM is a covariance structure technique that requires a larger number of variables relative to the parameters estimated. Although the number of cases is important for stable parameters, simple SEMs can be run with small sample sizes (Yang-Wallentin & Jo¨reskog, 2001). Bootstrap standard errors are estimated to provide reliable tests of model fit and parameters, which is important when analyzing relatively small sample sizes (Bollen & Stine, 1993). All data and statistical assumptions of SEM are met for the analysis (Bollen, 1989).

Results Model Fit The SEM predicting youth criminal onset and moral disengagement fits the data well for the full sample high and low psychopathy groups, as evidenced by fit statistics presented in Table 1. The


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Table 1. SEM Fit Statistics. Psychopathy High

n w2 goodness of fit RMSEA D2/IFI r2/TLI

Average

Low

Full

Male

Female

Full

Full

Male

Female

70 3.707 >0.000 1.031 1.136

40 6.577 0.050 0.988 0.941

30 5.225 >0.000 1.024 1.082

97 11.550* 0.098 0.926 0.675

85 7.880 0.061 0.981 0.922

46 1.914 >0.000 1.116 1.705

39 12.694* 0.171 0.936 0.736

Note. IFI = Incremental Fit Index; RMSEA ¼ root mean square error of approximation; TLI ¼ Tucker–Lewis Index. Significant at *p < 0.10, **p < 0.05, ***p < 0.01.

w2 goodness-of-fit tests show low values that are not significantly different from zero, indicating the model adequately fits the data. Root mean square error of approximation (RMSEA) indices evidence adequate fit since values are below 0.10. Incremental fit (D2) and the Tucker–Lewis (r2) indices are all above 0.90, also indicating good model fit. Inspection of the normalized residual covariance shows no extreme values, with most ranging within +0.50. The models are also estimated by gender and exhibit good fit, except for low psychopathy females. However, the model poorly fit the full sample average psychopathy group with higher w2 and RMSEA, lower r2, and larger residuals. Only the results from the high and low psychopathy models will be interpreted, but the results from the average model are presented in Appendix A.

Path Analysis Results The results of the path analysis predicting youth criminal onset and moral disengagement for high psychopathic risk youth is presented in Table 2 and Figures 2 and 3. Keeping in mind the valence of our measures, lower values of COI indicate earlier criminal onset, and lower values of MDI indicate moral disengagement. First, moral engagement (higher MDI) is associated with later youth criminal onset behavior (b ¼ .111), but this overall effect is driven solely by females in the sample (g ¼ .297 for females vs. g ¼ .005 for males). Second, the overall results show that higher youth psychopathy is strongly linked to earlier youth criminal onset (gtotal ¼ .464 and gdirect ¼ .438), and this effect is largely unmediated by moral disengagement (gindirect ¼ .026). However, this unmediated effect only applies to boys in the sample since psychopathy has little effect on moral engagement (g ¼ .027), and engagement has little effect on onset (g ¼ .005). Both the direct and total effects of psychopathy are identical for males (g ¼ 0.440). For young girls, however, psychopathy drives moral disengagement (g ¼ 0.420), but greater moral engagement drives later criminal onset (g ¼ .297). This suggests that while moral engagement suppresses some of the effects of psychopathy, it is overpowered by psychopathy’s effect on moral disengagement. Taken together, the indirect effect of psychopathy through moral disengagement intensifies the direct effect of psychopathy on early criminal onset by about 43% for girls (gtotal ¼ .412, gdirect ¼ .287, gindirect ¼ .125). Third, family stress has a moderate impact on decreasing the age of criminal onset (gtotal ¼ .172). Although the total effect is similar across gender (gtotal ¼ .199 for males and gtotal ¼ .192 for females), for girls we find moral disengagement acting as a suppressor variable that lessens the effect between family stress and earlier criminal onset by 15% (gtotal ¼ .192, gdirect ¼ .225, gindirect ¼ .033). By contrast, the results for low psychopathic risk youth are quite different (refer to Table 3 and Figures 2 and 4). First, we find that moral engagement (higher MDI) is moderately associated with


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Table 2. Results of SEM Predicting Youth Criminal Onset and Moral Disengagement for High Psychopathy Youth (N ¼ 70). High Psychopathy

Path analysis Moral disengagement

Psychopathy Family Stress Criminal onset Psychopathy Indirect via MDI Total effect Family stress Indirect via MDI Total effect Moral disengagement Psychopathy ↔ Family stress pR2 . . . moral disengagement pR2 . . . criminal onset Factor analysis Rule violation Criminal Onset Police contact Criminal Onset Court referral Criminal Onset pR2 . . . rule violation pR2 . . . police contact pR 2 . . . court referral Model fit w2 goodness of fit RMSEA D2/IFI r2/TLI

Full N ¼ 70

Male n ¼ 40

Female n ¼ 30

0.230* 0.057 0.438*** 0.026 0.464*** 0.178 0.006 0.172 0.111 0.246* .050 .295

0.027 0.107 0.440** 0.000 0.444*** 0.198 0.001 0.199 0.005 0.483** .015 .318

0.420** 0.112 0.287 0.125 0.412*** 0.225 0.033 0.192 0.297 0.072 .182 .290

0.687*** 0.775*** 0.706*** .471 .600 .499

0.791*** 0.741*** 0.672*** .626 .549 .451

3.707 >0.000 1.031 1.136

6.577 0.050 0.988 0.941

0.545** 0.798** 0.749** .297 .636 .560 5.225 >0.000 1.024 1.082

Note. Standardized coefficients are reported. IFI = Incremental Fit Index; RMSEA ¼ root mean square error of approximation; TLI ¼ Tucker–Lewis Index. Significant at *p < 0.10, **p < 0.05, ***p < 0.01.

earlier age of criminal onset, with stronger effects among girls (b ¼ .395) than boys (b ¼ .205). This is opposite of what is found for high psychopathy youth, where engagement is associated with later onset, especially among girls. Second, the total relationship between youth psychopathy and earlier criminal onset is much less for low-risk than high-risk youth. The effect is moderate for low-risk girls (gtotal ¼ .193), but nonexistent for low-risk boys (gtotal ¼ .012). However, psychopathy’s effect on early onset is suppressed somewhat through moral engagement, resulting in slightly later onset. In girls, moral engagement suppresses the direct relationship by 11% (gdirect ¼ .217, gindirect ¼ .024). By comparison, among high-risk youth these relationships are stronger for both genders, and moral disengagement leads to earlier onset among high-risk girls. Last, family stress has a moderate impact on earlier criminal onset for low-risk youth (gtotal ¼ .195), an effect similar to high-risk youth. What is different, however, is that family stress primarily impacts low-risk boys (gtotal ¼ .445) and is intensified by moral disengagement. Family stress has a negligible impact on girls (gtotal ¼ .107). In summary, the results show that moral engagement is linked to later criminal onset for high psychopathy girls, but counterintuitively has the opposite effect when linked with earlier onset low psychopathy boys and girls—counter to what is expected. Youth psychopathy is strongly associated with earlier criminal onset for high-risk youth. For boys, this effect is unmediated by moral


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High Psychopathy MDI

–0.230

YPI

–0.178

FSI

0.111

0.687

–0.070

RY2

RY3

1

1

1

MDI

0.295

FSI

–0.168

2 0.600

3 0.499

1 0.010 –0.276

1

2 0.142

COI

–0.141

0.096

0.706

RY1

1

YPI

2 0.295

0.775

1 0.471

Low Psychopathy

1

COI

–0.438

0.057

0.246

1 0.050

1

0.556

0.789

0.878

RY1

RY2

RY3

1

1

1

1 0.310

2 0.622

3 0.771

Figure 2. Path results predicting youth criminal onset (COI) and moral disengagement (MDI) by psychopathic risk. COI ¼ Criminal Onset Index; MDI ¼ Moral Disengagement Index.

disengagement, whereas for girls disengagement intensifies early onset by over 40%. Greater family stresses relate to earlier onset among high-risk youth and low-risk boys but has no effect on low-risk girls.

Factor Analysis Results Next examining the results of the factor analysis, we find the latent criminal onset variable can be reliably estimated across high and low psychopathic youth. Validity/factor coefficients (l) and reliability coefficients (pR2) for each observed variable are presented in Tables 2 and 3, with higher values indicating better measurement of the latent onset variable. However, different variables tend to drive criminal onset across risk groups and gender. For high psychopathy boys, all three indicators are valid and reliable measures of criminal onset. However, for high-risk girls only police contact and court referrals contribute to the factor model. For low-risk youth, both police contact and court referrals contribute to valid and reliable measures, but rule violation suffers from poor reliability.


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High Psychopathy Males –0.027 YPI 0.483 FSI

1 1 0.015 MDI

0.005 COI

–0.440

–0.107 –0.198

1 2 0.318

0.791 RY1

0.741

0.672

RY2

RY3

1

1 1 1 2 3 0.626 0.549 0.451 High Psychopathy Females –0.420 YPI 0.072 FSI

1 1 0.182 MDI

0.112 –0.225

0.297

1 2 0.290 COI

–0.287 0.545

0.798

0.749

RY1

RY2

RY3

1

1

1

1 0.297

2 0.636

3 0.560

Figure 3. Path results predicting youth criminal onset (COI) and moral disengagement (MDI) for high psychopathy males and females. COI ¼ Criminal Onset Index; MDI ¼ Moral Disengagement Index.

Taken together, the results indicate that rule violation only contributes minimally to measuring youth criminal onset.

Discussion In his presidential address to the American Society of Criminology, Messner (2012) discusses a moral awakening occurring in criminology. The bedrock concept that undergirds this integrated understanding is morality. The present study integrates morality with a long-standing criminological tradition namely the criminal career paradigm. With respect to delinquent careers, there are two pieces of information about its emergence that are critical to understand. First, there is widespread recognition across multiple conceptual models in the social and behavioral sciences that parameters of the delinquent career, such as onset and desistance, are not discrete entities but instead reflect complex processes that encompass the interplay of many different inputs (Andersson & Torstensson Levander, 2013; DeLisi & Piquero, 2011; Walters & DeLisi, 2013; Wu & Barnes, 2013). In the


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Table 3. Results of SEM Predicting Youth Criminal Onset and Moral Disengagement for Low Psychopathy Youth (N ¼ 85). Low Psychopathy

Path analysis Moral disengagement

Psychopathy Family stress Criminal onset Psychopathy Indirect via MDI Total effect Family stress Indirect via MDI Total effect Moral disengagement Psychopathy ↔ Family stress pR2 . . . moral disengagement pR2 . . . criminal onset Factor analysis Rule violation Criminal Onset Police contact Criminal Onset Court referral Criminal Onset pR2 . . . rule violation pR2 . . . police contact pR2 . . . court referral Model fit w2 goodness of fit RMSEA D2/IFI r2/TLI

Full N ¼ 85

Male n ¼ 46

Female n ¼ 39

0.070 0.096 0.141 0.019 0.122 0.168 0.027 0.195 0.276** 0.295*** .010 .142

0.040 0.210 0.020 0.008 0.012 0.402** 0.043 0.445** 0.205 0.183 .043 .240

0.060 0.009 0.217 0.024 0.193 0.103 0.004 0.107 0.395** 0.381** .003 .220

0.556*** 0.789*** 0.878*** .310 .622 .771 7.880 0.061 0.981 0.922

0.505*** 0.676*** 0.857*** .255 .457 .743 1.914 >0.000 1.116 1.705

0.531*** 0.948*** 0.968*** .282 .899 .938 12.694* 0.171 0.936 0.736

Note. Standardized coefficients are reported. IFI = Incremental Fit Index; RMSEA ¼ root mean square error of approximation; TLI ¼ Tucker–Lewis Index. Significant at *p < 0.10, **p < 0.05, ***p < 0.01.

current analyses, psychopathic personality features, moral disengagement, and family stress intermixed in diverse ways depending on the severity of psychopathic personality and gender. Second, the onset of an antisocial career is tremendously important for understanding the overall risk factors and psychopathology that characterize an individual. As shown in Appendix B, the high, average, and low psychopathy groups display clear and dramatic differences in terms of their risk profiles for problem behaviors and the emergence of delinquency. Acutely psychopathic youth break rules earlier, are arrested sooner, and get processed by the juvenile court earlier than their peers. They also experience significantly more family stress. Interestingly, the high, average, and low groups have comparable mean scores on moral disengagement, and the variable effects of moral disengagement in the models illustrates how it operates differently across the psychopathy distribution. The strong direct effect of psychopathy on criminal onset that is mostly unmediated by moral disengagement (except for high psychopathy females) is consistent with the view that psychopathy is a strongly pernicious condition with a strong association for delinquency (Blackburn, 2006; DeLisi, 2009; Hare & Neumann, 2008; Vaughn et al., 2008). In contrast, moral disengagement is a construct that reflects dynamism between the self, the conscience, the environment, and behavior (Bandura, 1999; Bandura et al., 1996). For low psychopathy youth in the current sample, moral disengagement was associated with earlier criminal onset


306


Low Psychopathy Males –0.040 YPI 0.183 FSI

1 1 0.043 MDI

–0.205 COI

–0.020

0.210 –0.402

0.505

0.381 FSI

0.857

RY2

RY3

1

1

1

2 0.457

3 0.743

1 1 0.003 –0.060

YPI

0.676

RY1 1 0.255 Low Psychopathy Females

1 2 0.240

MDI

0.009 –0.103

–0.395

1 2 0.220 COI

–0.217 0.531

0.948

0.968

RY1

RY2

RY3

1

1

1

1 0.282

2 0.899

3 0.938

Figure 4. Path results predicting youth criminal onset (COI) and moral disengagement (MDI) for low psychopathy males and females. COI ¼ Criminal Onset Index; MDI ¼ Moral Disengagement Index.

suggesting that the interactional nature of moral disengagement is essential for propelling lower risk individuals toward antisocial behavior. That moral disengagement is largely immaterial to highly psychopathic boys is consistent with the core deficiencies in conscience that pervade the disorder. Consistent with our study hypothesis, highly psychopathic boys do not need to contextualize interpersonal situations and reduce their guilt in order to commit crime, instead they just do it. By contrast, for highly psychopathic girls less moral disengagement leads to later onset, but this is overpowered by psychopathy’s impact on moral disengagement. In other words, psychopathy is so powerful that it negates the beneficial aspects of moral engagement. Overall, the current analyses support prior research that has examined the connections between psychopathic personality and moral disengagement as related to criminal conduct (Fontaine et al., 2014; Hyde et al., 2010; Paciello, Fida, Tramontano, Lupinetti, & Caprara, 2008; Shulman et al., 2011). The current findings also support prior research that has shown the heterogeneity of psychopathic personality among delinquent youth with higher scores consistently associated with more adverse behavioral outcomes


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(cf., Brandt, Kennedy, Patrick, & Curtis, 1997; Dyck et al., 2013; Loper, Hoffschmidt, & Ash, 2001; Stafford & Cornell, 2003; Tuvblad et al., 2013). The present study suggests that psychopathy among youthful offenders may be differentially affected by family stress and instability. In the high psychopathic group, family stress is strongly associated with psychopathy among boys, but not girls. Conversely, in the low psychopathic group, family stress is strongly associated with psychopathy among girls. This suggests two possibilities. First, that the emergence of psychopathy in the criminal career of boys may be driven to some extent by sensitivity to family stress and instability. Among lower risk female youthful offenders, family stress is an important driver of their levels of psychopathy. However, another explanation is that in fledgling psychopathic boys, their behavior may elicit negative responses from family members due to the difficulties associated with managing their behaviors (see, Tuvblad et al., 2013). This process may be less pronounced among girls. The current findings are directly relevant to juvenile justice practitioners and social service workers who serve delinquent youth. For several decades, psychoeducational programs such as Skillstreaming, Aggression Replacement Training, and the PREPARE Curriculum (e.g., Goldstein, 1993, 1999; Goldstein, Glick, & Gibbs, 1998) have targeted the behavioral, emotional, and cognitive deficits of antisocial youth. Specifically, Aggression Replacement Training contains a cognitive intervention that is designed to improve the moral reasoning of youth, and the evaluation studies of it are promising (Amendola & Oliver, 2010). Given the association between moral disengagement and criminal onset among many youth in the current sample, a program that improves moral reasoning would be significant in helping to forestall the emergence of a juvenile justice system contact.

Study Assets and Limitations The current study offers strengths including rich data from an enriched sample of adjudicated youth, multiple measures of antisociality and criminal onset, and a rigorous analytical strategy that looks deeply into the relations between study variables at different levels of risk. There are limitations, however. The study relied upon self-report measures, and we cannot rule out problems in shared method variance. In addition, the study was derived from youthful offenders from a single geographic site and therefore the generalizability of findings is open to question. Another important limitation is the use of a cross-sectional design. Shulman and colleagues (2011) recently utilized longitudinal data to show that moral disengagement and delinquency mutually declined across adolescence, and these effects withstood the important confound of callous and unemotional traits. It would be interesting to see how the current models would look across adolescence as these youth adapted to confinement and after their release. Given the significant linkages between psychopathy, recidivism, and criminal careers (cf., DeLisi, 2005; DeLisi, Vaughn, Gentile, Anderson, & Shook, 2013; Flexon & Meldrum, 2013; Gretton, McBride, Hare, O’Shaughnessy, & Kumka, 2001; Hemphill, Hare, & Wong, 2011), future research could fruitfully evaluate how psychopathy and moral disengagement codevelop over time as a youth becomes ever more enmeshed in an antisocial lifestyle.

Conclusion Moral reasoning is a critical component of decision making related to rule breaking. However, moral reasoning depends to a large extent on emotion (Blair, Mitchell, & Blair, 2005). The ability to experience uncomfortable emotions around the understanding of right and wrong (e.g., empathy) is necessary to proper socialization of morality often expressed in normative acts toward others. One of the hallmark features of psychopathy is the relative inability to experience these emotions even though there may be an understanding of right and wrong (Cima, Tonnaer, & Hauser, 2010). Our


308


results were consistent with this theoretical understanding of psychopathy and morality finding that moral disengagement was not a mediator for high psychopathy youth but was for low psychopathy youth.

Appendix A Table A1. Results of SEM Predicting Youth Criminal Onset and Moral Disengagement by Psychopathy Risk (N ¼ 252). High Psychopathy, Average Psychopathy, Low Psychopathy, n ¼ 70 n ¼ 97 n ¼ 85 Path analysis Moral disengagement

Psychopathy

Family stress Psychopathy Indirect via MDI Total effect Family stress Indirect via MDI Total effect Moral disengagement Psychopathy ↔ Family stress pR2 . . . moral disengagement pR2 . . . Criminal onset Factor analysis Rule violation Criminal onset Police contact Criminal onset Court referral Criminal onset pR2 . . . rule violation pR2 . . . police contact pR2 . . . court referral Model fit w2 Goodness of fit RMSEA D2/IFI r2/TLI Criminal onset

.230*

.024

.070

.057 .438*** .026 .464*** .178 .006 .172 .111

.017 .034 .002 .032 .284** .001 .285** .066

.246* .050 .295

.112 .001 .083

.295*** .010 .142

.687*** .775*** .706*** .471 .600 .499

.664*** .732*** .720*** .441 .537 .519

.556*** .789*** .878*** .310 .622 .771

3.707 >0.000 1.031 1.136

11.550* 0.098 0.926 0.675

.096 .141 .019 .122 .168 .027 .195* .276**

7.880 0.061 0.981 0.922

Note. Standardized coefficients are reported. IFI = Incremental Fit Index; RMSEA ¼ root mean square error of approximatio; TLI ¼ Tucker–Lewis Index. Significant at *p < 0.10, **p < 0.05, ***p < 0.01,



309

High n ¼ 70

Average n ¼ 97

Rule violation 11.74 (2.58) 11.81 (3.01) Police contact 12.70 (2.32) 12.52 (2.32) Court referral 13.94 (1.83) 13.91 (1.67) Moral 55.74 (6.16) 55.84 (7.71) disengagement Psychopathy 131.36 (15.55) 105.57 (6.21) Family stress 91.94 (60.10) 81.62 (62.67)

Mean (Standard Deviation)

Psychopathy

Table B1. Descriptive Statistics (N ¼ 252).

Appendix B

(2.57) (2.11) (1.73) (5.99)

11.67 (2.65) 12.38 (2.22) 13.65 (1.92) 54.95 (6.01)

Male n ¼ 40 11.87 13.13 14.33 56.80

(2.53) (2.43) (1.65) (6.29)

Female n ¼ 30 11.35 (3.22) 12.23 (2.41) 13.72 (1.60) 56.00 (7.07)

Male n ¼ 66

Female n ¼ 31 12.83 (2.21) 13.10 (2.02) 14.34 (1.76) 55.48 (9.04)

Average

11.95 (2.37) 12.43 (2.11) 13.84 (1.91) 54.38 (5.39)

Male n ¼ 46

Female n ¼ 39 13.13 (2.67) 14.26 (1.65) 14.46 (1.45) 55.64 (6.62)

Low

84.58 (8.13) 133.53 (17.28) 128.47 (12.58) 105.42 (6.45) 105.87 (5.77) 84.85 (6.97) 84.26 (9.42) 59.29 (59.33) 84.77 (53.29) 99.58 (66.67) 72.92 (53.08) 96.77 (75.14) 53.21 (48.56) 65.38 (68.55)

12.51 13.27 14.13 54.96

Low n ¼ 85

High

310


Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes 1. Various mechanisms of moral disengagement exist. In his social cognitive approach, Bandura (1986, 1999) suggests that moral justification, euphemistic labeling, advantageous comparisons, displacement of responsibility, diffusion of responsibility, disregard or distortion of consequences, dehumanization, and attribution of blame facilitate moral disengagement. In their criminological research, Sykes and Matza (1957) suggested that denial of blame, denial of injury, denial of responsibility, appeal to higher loyalties, and condemnation of the condemners were ways that delinquents freed themselves morally to engage in delinquency. 2. In other words, individuals who displayed the most severe moral disengagement were also the most severe in terms of aggression, crime, and violence. These findings comport with epidemiological research and developmental taxonomy theory that articulates the existence of a small pathological nonoffender group and a small pathological severe offender group (DeLisi, 2013; Jennings & Reingle, 2012; Moffitt, 1993, 2006; Vaughn, DeLisi, et al., 2011; Vaughn, Fu, et al., 2011) among a much larger group with normative offending. 3. There is scholarly disagreement about how pronounced these characteristics are among adolescents compared to adults (cf., Edens, Skeem, Cruise, & Cauffman, 2001; Ribeiro da Silva, Rijo, & Salekin, 2012; Skeem, & Cauffman, 2003; Skeem, Polaschek, Patrick, & Lilienfeld, 2011). 4. The SEM estimated in this article contains both a factor model and a path model. The nondeviational factor model measuring youth criminal onset (Criminal Onset Index [COI]), where Reidential Youth (RY)1 through RY3 are the three observed indicators of COI, ni are the intercepts, li are the factor coefficients, and ei are the measurement errors along with its associated covariance matrix Y. In the nondeviational path model, moral disengagement (MDI) and COI (defined in Equation 1) are the dependent variables, ai are the regression intercepts, b21 is the regression path of COI on MDI, gi are the regression paths of the dependent variables on youth psychopathy (Youth Psychopathic traits Inventory ) and family stress (Family Stress Index), and zi are the residual errors along with its associated covariance matrix C.

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Author Biographies Matt DeLisi is Professor and Coordinator of Criminal Justice Studies at Iowa State University. David J. Peters is Assistant Professor in the Department of Sociology at Iowa State University. Tamerria Dansby received a bachelor’s degree in criminal justice from Iowa State University. Michael G. Vaughn is Professor of Social Work at Saint Louis University. Jeffrey J. Shook is Associate Professor of Social Work at the University of Pittsburgh. Andy Hochstetler is Professor in the Department of Sociology at Iowa State University.
