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Akers (2001) is often credited with introducing social learning theory to criminology and criminal justice. By integrating Sutherland's work on differential association (Sutherland & Cressey, 2002) with aspects of Skinner's (2002) operant learning and Bandura's (1986) social learning models, Akers was able to construct a social learning theory of crime. The four core elements of Akers' model are differential association, definitions, differential reinforcement, and imitation. Differential association and definitions (attitudes towards crime) come from Sutherland's theory, differential reinforcement comes from Skinner's model, and imitation (modelling) comes from Bandura's theory. Definitions are the most weakly operationalized component of Sutherland/Akers' learning theory of crime (Matsueda, 2008), but along with differential associations, are among its strongest features (Pratt et al., 2005). The purpose of this study was to illustrate how it may be possible to operationalize the cognitive features of social learning theory by integrating aspects of deterrence/rational choice theory with constructs from Walters' (2012b) lifestyle theory of crime.
Choice plays a prominent role in several major theories of crime, to include deterrence (Paternoster, 1997) or rational choice (Clarke & Felson, 1976) theory and Gottfredson and Hirschi's (2006) general theory of crime. Whereas these theories conceptualize choice as an objective, economic process, Walters (2012b) views choice as a subjective, psychological process. In their reconceptualization of general and specific deterrence, Stafford and Warr (1978) draw attention to the fact that direct experience with the criminal justice system can shape a person's perception of the certainty, severity, and celerity of punishment, and in a recent review of the literature on deterrence theory, Piquero, Paternoster, Pogarsky, and Loughran (2010) identified several factors that may help shape these perceptions: social bonding, moral inhibition, emotional arousal, decision-making competence, and heuristic biases, to name a few. The practical and policy implications of these results and of efforts to integrate learning and deterrence theories are substantial, but require an organizing framework. To this end, the current study employs cognitive mediation as an organizing framework in an effort to understand the well-documented relationship between past and future criminality.
A principal role of cognition in behavioural science research is as a mediator of important variable relationships (MacKinnon & MacKinnon, 1988). One of the most important relationships in the criminal justice field is the relationship between past and future criminality (Gendreau, Little, & Goggin, 1990). Attempts to explain the past-crime–future-crime relationship, or what is sometimes referred to as crime continuity, have not proven as successful as attempts to document it. Two opposing models have nonetheless been advanced in an effort to explain this phenomenon: population heterogeneity and state dependence (Nagin & Paternoster, 2010). Proponents of the population heterogeneity position contend that time-stable differences in criminal propensity account for crime continuity by means of their ability to correlate with antisocial behaviour at various points in a person's life (Cleckley, 1994; Wilson & Herrnstein, 2002) Proponents of the state dependence position, on the other hand, assert that early antisocial behaviour promotes future criminality by altering perceptions of sanction severity, certainty, and celerity (Loughran, Pogarsky, Piquero, & Paternoster, 2000), destroying informal social control networks (Bernburg & Krohn, 2010), and knifing off opportunities for conventional behaviour (Sampson & Laub, 1959).
Studies comparing the population heterogeneity and state dependence theories of crime continuity have produced mixed results, with some studies supporting the population heterogeneity position (Nagin & Farrington, 1991; Paternoster, Dean, Piquero, Mazerolle, & Brame, 1986), other studies supporting the state dependence position (Nagin & Paternoster, 2000; Paternoster & Brame, 1997), and at least one study supporting both positions (Blokland & Nieuwbeerta, 1989). What is required is a theory capable of incorporating the population heterogeneity and state dependence positions, as well as aspects of learning and deterrence theory, into a single model. Walters (2012b) proposes such a model in the form of six quasi–time-stable cognitive factors hypothesized to mediate important crime relationships. Walters (2013b) determined that two of these variables (criminal thinking and low self-efficacy to avoid police contact) successfully mediated the relationship between past criminality and future criminality. Additional research is required, however, to determine whether the other four cognitive variables in Walters' (2012b) model also mediate crime continuity.
Walters (2012b) construes crime as an amalgam of two overlapping dimensions – a proactive/instrumental dimension and a reactive/impulsive dimension. Table 1 illustrates how the six quasi–time-stable cognitive factors help define and clarify the proactive and reactive dimensions. A review of six items used previously by Turner and Piquero (2012a) to assess attitudinal low self-control suggests that they may have been measuring the reactive elements of two of Walters' (2012b) six quasi–time-stable cognitive variables (i.e., short-term goals and physically hedonistic values). It was consequently reasoned that these items might be capable of mediating the relationship between past and future criminality in participants from the original Turner and Piquero (2012a) study. Two hypotheses were tested in the current investigation. The first hypothesis predicted that the six items previously used to assess attitudinal low self-control would fit a two-factor model (short-terms goals and physically hedonistic values) significantly better than a one-factor model. The second hypothesis predicted that scales created from the short-term goals and physically hedonistic values factors would successfully mediate the past-criminality–future-criminality relationship.
Table 1. Cognitive mediators of proactive and reactive criminality
|Cognitive mediator||Proactive/Instrumental dimension||Reactive/Impulsive dimension|
|Thinking styles||Proactive criminal thinking (Mollification, entitlement, power orientation, super-optimism)||Reactive criminal thinking (Cut-off, cognitive indolence, discontinuity)|
|Attributions|| ||Hostile attribution biases|
|Outcome expectancies||Positive outcome expectancies for crime|| |
|Efficacy expectancies||High self-efficacy for crime||Low self-efficacy for conventional behaviour|
|Values||Mental hedonism||Physical hedonism|
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The first hypothesis tested in this study predicted that six items previously used to assess attitudinal low self-control (Turner & Piquero, 2002) would yield two factors from Walters' (2012b) six-factor quasi–time-stable cognitive model: that is, short-term goals and physically hedonistic values. The second hypothesis tested in this study predicted that short-term goals and physically hedonistic values would mediate the past-crime–future-crime relationship when low self-control and important demographic variables (age, race, gender) were controlled. Through a series of confirmatory factor analyses it was determined that a two-factor model, in which items 1 through 3 loaded onto a short-term goals factor and items 4 through 6 loaded onto a physically hedonistic values factor, achieved a significantly better fit than a single, unidimensional model. These results are consequently consistent with the first hypothesis. The second hypothesis, however, received only partial support. Whereas physically hedonistic values displayed a moderately robust partial mediation effect on the past-crime–future-crime relationship, short-term goals failed to demonstrate a significant mediating effect when paired with physically hedonistic values in an SEM path analysis.
The reader might ask why short-term goals failed to mediate the past-crime–future-crime relationship when other variables in Walters' (2012b) model (i.e., criminal thinking, self-efficacy, physically hedonistic values) have successfully mediated this relationship. There are several possible explanations. First, although the items on the short-term goals scale correlated higher with each other (r = .22) than they did with items from the physically hedonistic values scale (r = .17), the physically hedonistic values items displayed a mean interitem correlation that was nearly twice that of the short-term goals items (r = .40). Hence, the physically hedonistic values scale may have done a better job of measuring the physically hedonistic values construct than the short-term goals scale did of measuring the short-term goals construct. Second, the short-term goals variable was found to partially mediate the past-crime–future-crime relationship when considered independent of the physically hedonistic values variable (see Footnote 2), but weakened to the point of non-significance when paired with the stronger physically hedonistic values variable, with which it correlated .31 (see Table 2). Additional or different items may accordingly be required to more effectively measure the short-term goals construct.
The sensitivity test results for the Crime-94 Values-96 Crime-98 mediation analysis revealed that early low self-control assessed behaviourally after the age when low self-control is believed to stabilize (i.e., 8–10 years: Gottfredson & Hirschi, 2006) was incapable of erasing the mediating effect of physically hedonistic values on the past-crime–future-crime relationship. When viewed in light of previous research (Walters, 2013b), there would appear to be a growing body of support for the argument that cognitive variables partially mediate the strong and consistent relationship between past and future criminality. The old adage that the best predictor of future behaviour is past behaviour may be true but is not, in and of itself, an explanation. Cognitive mediation provides an explanation in the form of psychological inertia (the tendency for cognitive variables like criminal thinking and values to be self-perpetuating: Walters, 2012b). Early criminal involvement shapes a person's thinking, which, in turn, influences a person's propensity to engage in future criminality. The model proposed by Walters (2012b), in which six quasi–time-stable-mediating factors give rise to crime continuity through psychological inertia is not incompatible with the existence of additional mediators of the past-crime–future-crime relationship, to include official and unofficial labelling (Bernburg & Krohn, 2010) and cumulative disadvantage (Sampson & Laub, 1959), both of which require direct contact with the criminal justice system. In fact, the interaction of direct (labelling and cumulative disadvantage) and indirect (psychological inertia) learning factors (Stafford & Warr, 1978) could be the driving force behind crime continuity.
In the current study a behavioural measure of low self-control administered at age 11–13 failed to account for the mediating effect of a cognitive measure of physically hedonistic values completed between the ages of 17 and 19. What is the significance of this finding for population heterogeneity explanations of crime continuity and Gottfredson and Hirschi's (2006) general theory of crime? Population heterogeneity may still play a role in crime continuity because the six cognitive mediators are shaped to some extent by genetic and early environmental factors. Twin studies, for instance, reveal that genetic factors account for a significant portion of the variance in people's outcome expectancies for alcohol (Slutske et al., 2005), and developmental studies denote that strong child–mother attachment at age 36 months is associated with fewer hostile attributions when the child is in first grade (McElwain, Booth-LaForce, Lansford, Wu, & Dyer, 1998). Research also indicates that these cognitive variables undergo significant developmental change over time (Bandura, 1986; Weiner, 1985). The same could be said of Gottfredson and Hirschi's (2006) general theory of crime. Some individuals have a stronger predisposition to low self-control than others, but the degree of stability in low self-control proposed by Gottfredson and Hirschi (2006) has not always been confirmed empirically (Burt, Simons, & Simons, 2006; Hay & Forrest, 2013; Turner & Piquero, 2012a). Prior research, in which self-report measures of low self-control were administered to juveniles and young adults, may have confounded the predisposition to low self-control and certain cognitive factors that shape and mediate low self-control over the life course.
Deterrence theory's view of choice as an objective, economic appraisal of the certainty, severity, and celerity of punishment has its origins in the early writings of Becarria and Bentham. Although deterrence theory was not directly tested in this study, a cognitive model composed of subjective, psychological factors with clear implications for decision making (i.e., goals and values) was found to partially mediate the relationship between past criminality and future criminality. This would seem to suggest that the decision making that leads to crime may be at least as psychological as it is economic. A practical implication of the current findings, then, is that through problem-solving training and other forms of cognitive intervention it may be possible to improve the decision-making skills of offenders and in the process make their choices more rational and objective and less impulsive and reactive. Moral values must also be assimilated into the decision-making process, however, because emotionless proactive decisions can be just as destructive as reactive impulsive ones. Therefore, in addition to conducting a proper economic analysis of one's options it is also important that values, goals, and expectancies be incorporated into one's decisions.
A policy implication of the current results is that we must be mindful of the subjective aspects of decision making when imposing sanctions on those who violate society's laws. Prison, for instance, is not generally viewed to be particularly aversive by many high-rate and criminally sophisticated offenders. Many such offenders, in fact, view prison as a means of cultivating new criminal contacts and enhancing their credentials as bona fide law breakers (Muntingh, 2008). Given the apparent criminogenic effect of prison (Bales & Piquero, 2012) it may be wise to avoid prison except in cases where the individual presents a physical threat to the community or where the committed offence demands the most severe non-capital sanction available to society, diverting a majority of offenders, particularly those with no history of violence, to community-based programs. Because rates of offending in the current sample were relatively low, it is important that the current results be replicated in a more criminally involved sample.
The current study is not without limitations, one of which is the use of mediational analysis itself. Spencer, Zanna, and Fong (1993) contend that mediational analysis has been misused and oversold as the primary means of establishing causal relationships. They maintain that a well-planned series of experimental studies are superior to mediational analysis in documenting causal links when the psychological processes under investigation are easy to manipulate but difficult to measure. They nonetheless acknowledge that when the psychological processes under investigation are difficult to manipulate but easy to measure then mediational designs may be the preferred method for establishing causal relationships. The psychological processes central to crime continuity are difficult to manipulate, but many are relatively easy to measure. It would appear, then, that mediational procedures have a place in crime continuity research, with the understanding that causality cannot be unequivocally established in a single mediational study. This is because three conditions must be met before it can be concluded that a causal relationship exists: (1) correlation; (2) direction; and (3) absence of viable alternative explanations. Mediational analysis addresses the first two conditions, but the third condition is only partially addressed in a single study, principally through sensitivity testing.
Whereas all viable alternative explanations of the cognitive mediation effect observed in this and the previous Walters (2013b) investigation have yet to be ruled out, results from the current study cast serious doubt on early low self-control as one such viable alternative explanation. To the extent that the current study involved analysis of secondary data it was limited to variables from the original NLSY-C database. Additional viable alternative explanations that could not be tested because they were not part of the NLSY-C database include criminal associates, labelling effects, cumulative disadvantage, intelligence, and the effect of incarceration on values, goals, and the other four cognitive components of Walters' (2012b) model. In the current study goals and values measured at age 17–19 served as the mediating variable, but had roots extending back before delinquency was measured at age 15–17. Hence, it is possible that goals and values shaped delinquency rather than the other way around. Ruling out this particular alternative hypothesis requires childhood measures of goals and values that could be included as confounding covariates in the Imai et al. procedure. Further research is also required to determine whether the other two cognitive variables in Walters' (2012b) model, attributions and outcome expectancies, mediate important crime-relevant relationships, if the six quasi–time-stable cognitive variables interact with one another to mediate the past-crime–future-crime relationship and other important relationships in the criminal justice field, and if the 2-year time intervals that separated the independent and mediating variables and mediating and dependent variables in this study were optimal.
The extension of learning theory to crime was an important development back when Sutherland and Akers first introduced differential association theory and the social learning model of crime to the fields of criminology and criminal justice. The next step in the development of a comprehensive theory of crime is integrating learning theory with models that emphasize cognitive skills (decision making) and cognitive restructuring (criminal thinking/expectancy challenge). Criminological theory has been dominated by single variable models for too long (Ericson & Carriere, 1996); the time has come to integrate the many disparate ideas that have been developed over the years into more comprehensive models. Statistical mediation and moderation (Baron & Kenny, 1986; Walters, 2013a, 1985; Walters, 1985) offer researchers an opportunity to explore the manner in which variables currently used to explain crime interact with one another. This may not only help explain individual differences in the propensity to commit crime but could also shed light on possible avenues of intervention, prevention, and change.