Literature Review

The Journal of forensic PsychiaTry & Psychology, 2017 Vol. 28, no. 1, 108–132 http://dx.doi.org/10.1080/14789949.2016.1261175

Biological protective factors of criminal offending: implications for risk assessment research and practice

Samuel Adjorlolo

Department of applied social sciences, city university of hong Kong, hong Kong, s.a.r

ABSTRACT Despite the recognition of the practical and theoretical contributions of protective factors in risk assessment practice, the field has granted significant attention to psychosocial protective factors to the apparent neglect of biological protective factors. This review found a wealth of evidence which strongly and convincingly indicates that biological factors such as high intelligent quotient, executive functioning, skin conductance, and resting heart rate offer protection against criminal and antisocial behaviors. More importantly, the literature is supportive of the view that both risk and protective factors co-occur in the same variables, thus questioning the practice of classifying a set of variables as strictly risk or protective. Specifically, the risk–protective effect is contingent upon individual’s rating as high or low on the factor in question. It is recommended that researchers, academicians, and practitioners strive in their efforts to canvass other salient factors beyond the psychosocial factors as these factors can significantly and positively impact the risk assessment field, both theoretically and practically.

ARTICLE HISTORY received 19 May 2016; accepted 13 october 2016

KEYWORDS risk assessment; protective factors; biological protective factors; risk factors; biopsychosocial model

Risk assessment of criminal offenders basically involves estimating the proba- bility that an individual will commit an offense in the future (Cooke & Michie, 2013), particularly in situations of uncertainty (Ward & Beech, 2015). Risk assessment is currently a growth industry, generating enthusiasm among clinicians and legal professionals.  In Western countries, such as the United States, the frequency with which risk assessment for (re)offending is requested across a variety of mental health and criminal justice contexts, the popularity and somewhat acceptability of  same is historically unprecedented (Vitacco, Erickson, Kurus, & Apple, 2012). Specifically, risk assessment reports are cen- tral to the operations and sanctity of contemporary criminal justice system as

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CONTACT samuel adjorlolo [email protected]

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they guide critical legal and courtroom decisions, spanning incarceration to release of offenders (Skeem & Monahan, 2011). This is notwithstanding the fact that the law is concerned with certainty whereas the risk assessment field speaks in probabilistic terms. In the correctional and mental health systems, risk assessment data sometimes support treatment and rehabilitation strat- egies to mitigate the risk of offending, the so-called risk management (Zara & Farrington, 2013). A distinctive characteristic of the over 120 existing risk assessment instruments is the overwhelming focus on factors that precede, associate with the onset, and predict or statistically correlate with criminal or antisocial behaviors, the so-called risk factors (Ward & Beech, 2015). The age- long observation that not all individuals exposed to crime breeding events such as maltreatment, poverty, and peer influence do engage in criminal activities suggests the availability of protective factors. Put differently, just as there are risk factors facilitating criminal activities, so are protective factors that may predict the low probability of engagement in criminal activities. This implies that both risk and protective factors are germane to further the understanding of an individual’s level of risk of (re)offending. Unfortunately, protective factors have been ignored in the risk assessment field until recently.

The literature explicitly shows that risk factors alone always explain a small proportion of the variance in the outcome variables of interest (e.g. antisocial behavior; Lösel & Farrington, 2012; Miller, 2006; Rogers, 2000). For example, in a review of several meta-analytic studies, Douglas, Hart, Groscup, and Litwack (2014) found that the area under curve (AUC) value of both actu- arial (e.g. Static 99; Hanson & Thornton, 1999) and structured professional judgment (e.g. Historical-Clinical-Risk Management-20; Webster, Douglas, Eaves, & Hart, 1997) risk assessment instruments was .62 and .68, respectively (see also Guy, Douglas, & Hendry, 2010; Viljoen, Mordell, & Beneteau, 2012). The AUC value, ranging from 0 (no prediction), .05 (chance prediction) and 1 (perfect prediction), is the most widely used indicator of predictive validity of risk assessment instruments (Singh, Desmarais, & Van Dorn, 2013). By evaluating Douglas et al.’s (2014) findings against the AUC benchmarks, it seems clear that the existing risk assessment instruments have limited predictive validity. Inclusion of protective factors can reasonably improve the predictive validity of the existing or future risk assessment instruments. As a consequence, some researchers have chastised the field for neglecting protective factors for far too long and have subsequently recommended their inclusion (Miller, 2006; Rogers, 2000). Although the field has responded to this laudable call, efforts have so been concentrated on psychosocial factors to the apparent neglect of biological factors. This review is primarily aimed at canvassing the literature to identify biological factors that may have protective effects.

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Meaning and importance of protective factors

Despite the lack of consensus on the precise definition of protective factors, it is, however, generally understood that they are basically the characteristics of individuals and their environment or situation that can prevent the recur- rence of violent behaviors or facilitate desistance from (re)offending (de Vries Robbé, de Vogel, & de Spa, 2011; de Vries Robbé, Mann, Maruna, & Thornton, 2015; Portnoy, Chen, & Raine, 2013). Protective factors can cause a reduction in criminal behaviors by moderating or mediating the relationship between risk factors and criminal behaviors, or acting independent of risk factors (de Vries Robbé et al., 2015). Not only are these variables important in assessing the risk of offending, but also in the design of intervention programs to mitigate the risk of offending (Lodewijks, de Ruiter, & Doreleijers, 2010) since they can contribute to ‘reducing therapeutic nihilism, …… enhancing insight into an individual’s capacity for growth and recovery ….’(de Ruiter & Nicholls, 2011, p. 163). The relationship among risk factors, protective factors, risk assessment, and risk management can be summarized by the theoretical equation: Risk factors – Protective factors = Risk assessment = Risk management.

Accordingly, where the protective factors far outweigh the risk factors, the equation would be ‘negative’, suggesting minimal or no risk of future offending and so minimal or no treatment is required. In contrast, where the risk factors are qualitatively and quantitatively more than the protective factors, this may result in a ‘positive’ equation which also implies the likelihood of future offending and hence the need for appropriate intervention or treatment. In effect, where sali- ent protective factors are not canvassed and incorporated into the process, indi- vidual’s risk of violence may be inflated, leading an undue and unnecessary loss of personal liberty, as well as a propensity to cause overcrowding at detention or treatment centers. Societal consequences of inaccurate risk assessment include financial burden (e.g. payment of tax). Offenders who are wrongly classified may experience psychological distress and emotional discomfort (see Attrill & Liell, 2007). In addition, risk management strategies informed by the purported risk level may unnecessarily drain limited organization and government resources. Conversely, incorporating irrelevant and inappropriate protective factors may lead to underestimation of risk for violence, with consequences such as threat to public safety and/or self-harm. It follows from the discussions above that attention should be focused on important protective factors to ensure that estimations of risk of (re) offending and risk management, when necessary, are balanced to avert undesirable and unexpected outcomes.

The focus of the present review

Identification and inclusion of important protective factors is considered a key challenge for the risk assessment field for the next generation (Farrington, 2007).

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Unsurprisingly, efforts to incorporate these factors have been restricted to psy- chosocial factors as evidenced by the content of the over 12 different standard- ized instruments (i.e. questionnaires and checklists) assessing protective factors. These instruments include the Dynamic Risk Assessment for Offender Re-Entry (Serin, Mailloux, & Wilson, 2012), Inventory of Offender Risk, Needs, and Strengths (Miller, 2006), the Short-Term Assessment of Risk and Treatability (Webster, Martin, Brink, Nicholls, & Desmarais, 2009), Structured Assessment of Protective Factors for Violence Risk (SAPROF; de Vogel, de Ruiter, Bouman, & de Vries Robb′e, 2009), Structured assessment of Violence Risk in Youth (Borum, Bartel, & Forth, 2006), Protective Factors Scale (Bremer, 2001), and Desistence for Adolescents Who Sexually Harm (DASH-13; Worling, 2013). The interesting but relatively unex- plored question in the literature relates to whether biological factors can offer protection against antisocial and criminal behaviors, as well as whether biolog- ical factors can positively impact risk assessment research and practice.

A wealth of studies have shown that antisocial and criminal behaviors are more likely to result from changes in individual’s biological, psychological, and social characteristics (Byrd & Manuck, 2014; Nordstrom et al., 2011; O’Brien, Mustanski, Skol, Cook, & Wakschlag, 2013; Samek et al., 2015; Zagar, Busch, Isbell, & Hughes, 2009). This reasonably implies that protective factors may also be embedded in an individual’s biological and psychosocial dynamics, and not only in their psychosocial characteristics. Indeed, the hitherto view that biol- ogy has no role to play in criminal tendencies has been questioned strongly by contemporary studies delineating the roles of biological and psychosocial fac- tors in criminogensis (i.e. biosocial research paradigm). The available evidence suggests that some well-researched and revered criminogenic variables such as self-control, psychopathy, and impulsivity have biological underpinnings (Barnes, Beaver, & Boutwell, 2011; Connolly & Beaver, 2014; Walsh & Bolen, 2012). Following from the above, it is academically and intellectually unexciting and perhaps inappropriate to maintain strict disciplinary allegiance or steadfastly cling on to the ‘psychosocial paradigm’ when recent findings could be seen as an opportunity and avenue to rethink and re-conceptualize criminogensis by taking into account both biological and psychosocial predispositions. Thus, in the search for promising protective factors, it would be imperative to consider the totality of individual characteristics, including those pertaining to their bio- logical states. Obviously, protective factors, just like risk factors, are not neces- sarily the same for all offenders. This uncontested observation should serve as a reminder and wake-up call for researchers, academicians, and practitioners to strive to canvass salient biological factors as these factors, in addition to psychosocial factors, can positively impact the risk assessment field, both the- oretically and practically.

It is also important to mention that there are several challenges besetting research and professional activities in relation to protective factors. In par- ticular, the existing models of protective factors appear either obsolete for

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contemporary research, or are mostly confined to developmental psychopa- thology, thus possessing limited or no utility in risk assessment endeavors (e.g. Fitzpatrick, 1997; Hawkins, Catalano, & Miller, 1992; Rhodes & Jason, 1988; Rutter, 1985). This development hinders empirical investigations and insight into pro- tective factors, and also pose substantial challenge to developers of assessment instruments in terms of situating their works in a specific theoretical framework or model (de Vogel, de Vries Robbé, de Ruiter, & Bouman, 2011). As a burgeoning and interesting concept, protective factors can contribute meaningfully to risk assessment and risk management if we are able to (1) define and conceptualize these factors, (2) identify potential protective factors from the relevant literature, (3) develop theoretical and conceptual models to explain their mechanisms of action, (4) conduct studies to validate their mechanisms of action and refine the models, where appropriate, and finally (5) develop instruments that accurately and validly capture these factors (see de Vries Robbé et al., 2015). Efforts to identify germane biological and psychosocial protective factors are instrumen- tal in our quest to develop valid and nuanced theoretical models of protective factors, as well as validate tools to assess these factors. It is quite encouraging that some researchers have expressed profound interest in advancing the liter- ature on protective factors. Recently, de Vries Robbé et al.(2015) presented an extensive review of psychosocial protective factors of sexual offending where they examined in depth issues pertaining to the definitions and conceptual- izations of protective factors. Although risk assessment literature is driven by normative data, there is a gradual recognition of the need for a fined-grained individualized assessment to take into cognizance individual unique factors (Scurich, Monahan, & John, 2012). It is argued that biological protective factors are several of those unique factors that may bear upon risk and could therefore add incremental information to predict an individual’s level of risk to self and/ or society. In light of this, the present review specifically focused on identifying potential and promising biological protective factors.

Biological protective factors

One way to proffer a better understanding and insight into protective variables is to group them into domains. The domains should not only retain conceptual and theoretical relevance, but they should also be consistent with contemporary evidence in the field. Consequently, protective factors can broadly be organized into biological, psychological, and social domains. In this review, the biological domain was subdivided into the following broad headings: genetics, neurocog- nitive, and psychophysiological functioning. The factors discussed below were chosen mainly because of the existence of empirical studies demonstrating their protective effects. This does not in any way suggest that they are the only potential biological protective factors.

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The protective aspects of genetic composition

Biosocial researchers have shown profound interest in elucidating specific candi- date genes that might contribute to antisocial behaviors. The genes identified so far are those pertaining to the (1) dopaminergic system (e.g. MAOA, DRD2, DRD4, COMT), which is concerned with reward sensitivity and sensation seeking, (2) serotoninergic system (e.g. 5-HTT), which is implicated in sensitivity to punish- ment and displeasure, and (3) gamma aminobutric acid or GABA (e.g. GABRA2, GABRG1) system, which also plays significant roles in the excitation and disinhi- bition of the neuronal system (Simons, Beach, & Barr, 2012). The interactions of these genes with each other and environmental factors have been associated with antisocial behaviors, arrest, and incarceration (Beaver, 2011; Caspi et al., 2002; Fergusson, Boden, Horwood, Miller, & Kennedy, 2011; Kim-Cohen et al., 2006; Samek et al., 2015), although others have reported contradictory findings (Haberstick et al., 2014; Huizinga et al., 2006). With respect to protective effects, studies have shown that genetic markers, particularly monoamine oxidase A (MAOA) and 5-Hydroxytriptamine transporter-linked polymorphous region (5-HTTLPR), seem to have buffering protective effects in the face of adversities. MAOA facilitates the breakdown and reuptake of biogenic amines such as sero- tonin, epinephrine, and norepinephrine at the synaptic cleft, thereby rendering them inactive. There are two variants of the MAOA that affect its transcriptional efficiency. The low activity variant (MAOA-L) is less efficient and therefore con- tributes to a higher concentration of intracellular serotonin. In contrast, high activity variant (MAOA-H) is more efficient, and leads to a lower concentration of intracellular serotonin (Viding & Frith, 2006).

In a classical gene–environment interaction longitudinal study, Caspi et al. (2002) found that maltreated individuals with a high MAOA activity showed less negative outcomes (e.g. violent convictions) as compared to those with a low MAOA activity. Similarly, based on a 30-year longitudinal study, Fergusson et al. (2011) reported that individuals with a low-activity MAOA variant who were exposed to childhood abuse were more likely to report later offending and psychological disturbances such as conduct problems and hostility than those with a high-activity MAOA. This finding remained significant after con- trolling for a range of potentially confounding variables. The findings above have been confirmed by several independent (Cicchetti, Rogosch, & Thibodeau, 2012; Fergusson, Boden, Horwood, Miller, & Kennedy, 2012; Kim-Cohen et al., 2006) and meta-analytic investigations (Byrd & Manuck, 2014; Kim-Cohen et al., 2006). Studies have also found that a high-activity MAOA offered protection to whites, but not non-whites (mostly African-Americans and Hispanics; Widom & Brzustowicz, 2006), and males, but not females (Byrd & Manuck, 2014). These findings notwithstanding, the weight of the evidence points toward the sugges- tion that high-MAOA activity genotype can confer some protective functions

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against developing antisocial behaviors in the presence of adverse environmen- tal factors (e.g. maltreatment).

Relatedly, the 5-HTTLPR is one of the major serotonin transporter genes in the serotonergic system, transcribing proteins that regulate the brain’s serotonin level. The 5-HTTLPR thus facilitates prefrontal inhibition. However, the effect of this transporter on behavior is partly related to its short and long versions. The short version, caused by a reduction in the transcriptional efficiency of the 5-HTTLPR, mostly triggers a decrease in serotonin expression and uptake at the synapse, whereas the reverse is true for the long version. Even a copy of the short version reduces the functioning of serotonin in the brain, thereby increasing the likelihood of negative outcomes following exposure to unfavora- ble environmental conditions. Caspi et al. (2003) in a prospective longitudinal cohort study found that the probability of experiencing adverse outcome (i.e. depression) in individuals who were homozygous for the long allele did not increase across different maltreatment categories compared with those who were homozygous for the short allele. Those with both short and long alleles were also at immediate risk. Li and Lee (2010) observed that girls, but not boys, who were homozygous for the short version were 12 times more likely to express severe antisocial behaviors. In another study, children with short allele genotype who suffered from early onset and recurrent maltreatment were more likely to report antisocial behaviors (Cicchetti et al., 2012). In sum, while the short allele genotype appears as a risk factor, the long version, on the other hand, may confer protection against environmental adversities, leading to a low tendency to engage in criminal and antisocial behaviors.

The protective aspect of neurocognitive functioning

Of the various neurocognitive factors, intelligence and executive functioning (EF) are the most studied in relation to criminality.

Intelligence Intelligent quotient (IQ) is fractionated into verbal IQ, performance IQ, and sometimes the difference between verbal and performance IQ (Portnoy et al., 2013). IQ is further classified into low, high, or above average. Low (verbal) IQ has long been associated with antisocial and criminal behaviors (Brennan, Hall, Bor, Najman, & Williams, 2003; Gibson, Piquero, & Tibbetts, 2001; Lynam, Moffitt, & Stouthamer-Loeber, 1993; Moffitt & Caspi, 2001), partly because it acts as a precursor to frustration, failure in socialization, disinhibited self-control, deficit in theory of mind, and inability to delay or postpone gratification (Eriksson, Hodgins, & Tengström, 2005).

In contrast, some have argued that high IQ enhances individual’s ability to withstand the effects of adverse life events by enabling the deployment of effec- tive and appropriate cognitive and behavioral processes such as information

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processing, self-control, and problem-solving (Masten & Coatsworth, 1998; Moffitt, 1993; Vanderbilt-Adriance & Shaw, 2008). In support of the above, studies have shown that high IQ could protect against antisocial and criminal behaviors, even in the presence of risk factors such as a criminal father, a dis- advantaged home, a high risk environment, and previous antisocial behaviors (Kandel et al., 1988; Lahey et al., 1995; Loeber, Pardini, Stouthamer-Loeber, & Raine, 2007; Lösel & Bliesener, 1990; Losel & Bliesener, 1994; Masten et al., 1999; McCord & Ensminger, 1997; Radke-Yarrow & Brown, 1993; Stattin, Romelsjö, & Stenbacka, 1997; Stouthamer-Loeber et al., 1993; Vanderbilt-Adriance & Shaw, 2008; Werner & Smith, 1982; White, Moffitt, & Silva, 1989; Windle & Windle, 1995). Albeit Loeber et al. (2007) found that high IQ was not significantly associated with desistance from criminal activities, there is some consensus that high IQ may provide protective function against the formation and/or manifestation of antisocial behaviors.

Executive functioning EF has been referred to as a complex set of executive processes such as (1) volition (i.e. evaluating one’s needs and adopting measures to achieve them); (2) planning (i.e. identifying steps necessary to achieve some desired goals); (3) purposive action (i.e. translating intention or plan into productive and self- serving activity); and lastly (4) effective performance (i.e. ability to monitor, self-correct, and regulate the performance of an act) (Lezak, Howieson, Bigler, & Tranel, 2012; see also Adjorlolo, 2016a, 2016b; Adjorlolo & Egbenya, 2016). Raine and Liu (1998) proposed a putative predisposition model linking prefrontal cor- tex (PFC) dysfunction and violence at the neurophysiological, neurobehavio- ral, social, and cognitive levels. At the neurophysiological level, reduced PFC functions could lead to a reduced or loss of inhibition or control of subcortical structures (e.g. amygdala) implicated in aggressive tendencies. For instance, chronic stress in humans has been found to weaken the brain region (i.e. the PFC) that regulates the amygdala which is associated with fear and emotion processing. Consequently, at the neurobehavioral, this may result in emotional and aggressive outburst at the slightest provocation or stressful events. Deficits in problem-solving skills and concept formation which are necessary to develop prosocial skills to handle aggressive situations arising from daily interpersonal interactions may result in antisocial behaviors at the social level. Lastly, at the cognitive level, reduced PFC activities can result in poor concentration and defective reasoning which may have adverse consequences on performance at school and work. This in turn may lead to economic deprivation, and hence predisposing individuals to procriminal lifestyle. Systematic investigations have found poor or defective EF processes in individuals with antisocial and criminal behaviors (Adjorlolo & Egbenya, 2016; Joyal, Plante-Beaulieu, & de Chanterac, 2014; Morgan & Lilienfeld, 2000; Ogilvie, Stewart, Chan, & Shum, 2011).

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Although studies investigating the protective effects of EF are relatively scarce, there are some indications that individuals with ‘intact’ neurocognition are more likely to self-regulate and inhibit disturbing emotions when exposed to stressful, threatening, or provocative situations. To illustrate, aggressive ten- dencies can successfully be inhibited by drawing on several executive abilities such as information processing, perspective taking, anticipating consequences, and defusing hostile situations (Giancola, 2000). These cognitive processes are indeed needed to regulate affective and behavioral responses. Santor, Ingram, and Kusumakar (2003) investigated the role of EF deficits in verbal aggres- sive tendencies in adolescents under conditions of increasing and decreasing provocation over winning and losing trials. It emerged that adolescents with profound EF difficulties indexed by performance on EF tasks (e.g. Conditional Associative Learning Task) responded with more verbal aggression with increas- ing levels of provocation than those with less EF difficulties. Cross-sectional and longitudinal data have also shown that individuals with strong ability to inhibit irrelevant and prepotent stimuli did not develop conduct disorder, even though they have been exposed to adverse environmental conditions (e.g. low socioeconomic status) (Nigg, Nikolas, Friderici, Park, & Zucker, 2007). According to Loeber et al. (2007), delayed verbal memory and sustained attention, but not cognitive flexibility, offered protection against delinquent behaviors. In another study, Sprague, Verona, Kalkhoff, and Kilmer (2011) found that perceived stress and EF significantly interacted to predict aggressive behaviors. In this study, stress was strongly related to aggressive tendencies in participants with low EF. In yet another study, EF mediated the relationship between temperament and antisocial behaviors in girls with conduct disorder (Giancola, Mezzich, & Tarter, 1998), and attention deficit/ hyperactivity disorder and social problems (Tseng & Gau, 2013). Several other studies found that EF moderates/mediates (i.e. protective effects) the development of antisocial and psychopathological behaviors (Giancola, Martin, Tarter, Pelham, & Moss, 1996; Giancola, Moss, Martin, Kirisci, & Tarter, 1996; Spada, Nikčević, Moneta, & Wells, 2008). This finding has largely corroborated the suggestion that EF might be a promising individual characteristic that could help in the promotion of social-emotional competence to guard against legally and morally unacceptable behaviors (Riggs, Jahromi, Razza, Dillworth-Bart, & Mueller, 2006).

The protective aspects of psychophysiological indicators

Psychophysiological markers that have received much scholarly attention with respect to antisocial behavior are resting heart rate and skin conductance.

Resting heart rate Heart rate in general is controlled by both parasympathetic and sympathetic branches of the autonomic nervous system (Portnoy & Farrington, 2015). Resting

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heart rate reflects the number of times a heart beats during times of inactivity. It is principally divided into low and high resting rates. Two major perspectives are commonly used in discourses involving low resting heart rate and antisocial behaviors: (1) the stimulation seeking and (2) fearlessness hypotheses (Raine, 1993, 2002; Weir & Kosloski, 2015). According to the stimulation seeking per- spective, there are differences in the level of cortical and autonomic activation or arousal among individuals with varying heart rates. Individuals with low resting heart rate are more likely to have chronically underaroused nervous system, and so may feel psychologically unsettled. Consequently, they may engage in behaviors, including aggressive and antisocial behaviors, to stimulate their arousal to an optimum level. The fearlessness hypothesis also maintains that low resting heart rate is a predisposition factor to bravery which in turn facili- tates the execution of aggressive and antisocial behaviors, making individuals less responsive to punishment and other punitive measures. In keeping with the above, meta-analytic studies have found significant effects of low resting heart rate on antisocial behaviors (Lorber, 2004; Ortiz & Raine, 2004; Portnoy & Farrington, 2015).

On the other hand, high heart rate appears to offer protection against antiso- cial behaviors (Farrington, 1994; Lösel & Bender, 1997; Raine & Venables, 1981), aggressive behaviors (Kindlon et al., 1995), adult criminality (Farrington, 1994), and violent convictions (Farrington, 1997) in male and female adults and adoles- cents exposed to family and other risk factors. It has been found that individuals with criminal fathers who did not become criminals themselves had signifi- cantly higher heart rate activity compared with those classified as criminals with criminal fathers, criminals with noncriminal fathers, and noncriminals with noncriminal fathers (Brennan et al., 1997). High resting heart rate has also been shown to significantly mediate the relationship between social adversity and different indicators of antisocial behaviors, including delinquency and conduct disorder (Choy et al., 2015). It should be noted, however, that mixed results were found for the influence of high resting heart rate on desistance from criminal activities (de Vries-Bouw et al., 2011; Raine, Venables, & Williams, 1996), partly due to methodological issues such as small sample size. Nevertheless, these pre- liminary studies support the view that high heart rate can protect individuals at risk of antisocial behaviors from developing and expressing antisocial behaviors.

Skin conductance Closely linked to resting heart rate is skin conductance. Categorized into high or low, skin conductance is also mostly used to index sympathetic nervous system activations (Gordis, Feres, Olezeski, Rabkin, & Trickett, 2010). Low skin conductance level may indicate low trait anxiety (Kagan, Reznick, & Snidman, 1987), fearlessness, and sensation seeking behaviors such as aggressive behav- iors (van Goozen, Fairchild, Snoek, & Harold, 2007), and low inhibition of aggres- sive behaviors (Raine, 2005). Low skin conductance has also been related to

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learning difficulties which facilitate insensitivity to punishment (Raine, Lencz, Bihrle, LaCasse, & Colletti, 2000; Shannon, Beauchaine, Brenner, Neuhaus, & Gatzke-Kopp, 2007). Studies have found that low skin conductance level in the presence of psychosocial risk factors increases the probability of antisocial and aggressive behaviors in children (Erath, El-Sheikh, & Cummings, 2009), adoles- cents (Fairchild, Van Goozen, Stollery, & Goodyer, 2008; Gao, Raine, Venables, Dawson, & Mednick, 2010), and in adults with psychopathic traits (Birbaumer et al., 2005; Rothemund et al., 2012).

In contrast, increase in sympathetic nervous system activities, indexed by high skin conductance, has been found to offer protective function against antisocial behaviors, even among individuals at high risk of these behaviors. Raine, Venables, and Williams (1990) examined the skin conductance level of 15-year-old male participants while their criminal behaviors were assessed at age 24 years. It emerged that those with criminal records at age 24 had signif- icantly lower skin conductance responses than the other subjects. Moreover, lack of skin conductance was significantly more prevalent in the participants with criminal records than those without records of criminal activities. Similarly, in Brennan et al.’s (1997) study reported above, high skin conductance level was displayed by males with criminal fathers who did not become criminals com- pared with the other groups of participants. Other studies have found high skin conductance among adolescents who desisted from adult criminal behaviors compared to those who did not (Raine, Reynolds, Venables, & Mednick, 1997; Raine, Venables, & Williams, 1995; Raine et al., 1996).

Taken as a whole, this review has identified some promising biological fac- tors that may offer protection against antisocial behaviors, and may therefore contribute to and enrich the literature on protective factors for risk assessment purposes. In particular, high intelligence quotient, EF, skin conductance, and resting heart rate are promising variables that could be targets for further empir- ical investigations. Likewise, high genetic activities, for instance: high MAOA activity, are also promising biological protective factors.

Implications for research

The central finding of this review is that protective factors are embedded in indi- viduals’ biological states, and not only in their psychological and social dynamics as suggested by previous studies. Based on the findings of this review and pre- vious studies, protective factors may be construed as biological, psychological, and social factors that have the propensity to moderate and/or mediate the relationship between risk factors and antisocial behaviors or act independently of risk factors of antisocial and criminal behaviors. The above conceptualiza- tion is illustrated by the proposed biopsychosocial model of criminal offending (Figure 1). According to the model, there is a general pathway (path ‘A’) relating risk factors to (the risk of ) offending or indicating the effects of risk factors on

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(the risk of ) offending. The risk-offending pathway can be moderated (path ‘B’) or mediated (path ‘C’) by protective factors. The protective factors can directly (path ‘D’) influence and cause a reduction in criminal behaviors (i.e. act inde- pendently of risk factors).

As moderators, protective factors can buffer the effects of risk factors, thereby conferring some sort of resilience on individuals who are exposed to either varying or equal degrees of risk factors which sometimes cannot be avoided (Jones, Brown, Robinson, & Frey, 2014; Krohn, Lizotte, Bushway, Schmidt, & Phillips, 2014; Lodewijks et al., 2010; Noltemeyer & Bush, 2013; Rennie & Dolan, 2010). The probability of engaging in criminal behaviors may be low when the protective factors far outweigh the risk factors, both in quantity (i.e. number) and quality (i.e. strength). Rutter (1990), for instance, noted that the process of protection from criminal behaviors depends on the ‘multiplicative interactions or synergistic effects in which one variable potentiates the effect of another’ (p. 206). Examination of the moderating effects of several criminogenic varia- bles appeared to be a highly favored methodological approach (Jones et al., 2014; Lodewijks et al., 2010; Rennie & Dolan, 2010; Santor et al., 2003; Sprague et al., 2011). This largely reflects the central objective of contemporary (biosocial) research approach that sees criminal and antisocial behaviors as the outcome of the interactions between biological and psychosocial factors. Moderation effects can be investigated in two ways. One involves the use of the outcome variable (i.e. antisocial behavior) as the dependent variable, and the significance of the interaction between potential biological protective factors and psychosocial risk

Psychosocial

Psychosocial e.g., Violence at home Substance abuse

Biological e.g.,

high IQ High EF

Psychosocial High social support High expectations

Biopsychosocial e.g., Birth complications × abusive parenting Low MAOA× maltreatment

Biological e.g., Low executive function Low Resting heart rate

Risk factors Protective factors

Figure 1. Biopsychosocial model of criminal offending. notes: a  =  Pathway relating risk factors and (risk of ) offending, B  =  moderator pathway of risk factors and (risk of ) offending, c = mediator pathway of risk factors and (risk of ) offending, and D = independent pathway of protective factors and (risk of ) offending. iQ = intelligent quotient, ef = executive functioning, and Maoa = monoamine oxidase a.

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factors can be probed (see, Aiken & West, 1991; Bauer & Curran, 2005; Cohen, Cohen, West, & Aiken, 2003). The other approach involves the use of the putative biological factor as the outcome variable and the interaction between antisocial behavior and psychosocial risk factor is examined (e.g. Brennan et al., 1997; Kandel et al., 1988; Raine et al., 1996).

The relationship between risk factors and antisocial behaviors can be medi- ated by protective factors (Fitzpatrick, 1997; Ullrich & Coid, 2011). As mediators, protective factors are expected to correlate negatively with the outcome varia- ble (e.g. antisocial factors) and risk factors. The risk of antisocial behaviors may be less in instances where protective factors are more, particularly in terms of quality, relative to risk factors. Conversely, a quantitative and qualitative increase in risk factors more than the protective factors means that the risk factors will generally weaken or reduce the effects of protective factors (Fitzpatrick, 1997; Ullrich & Coid, 2011), thus resulting in a heightened risk of antisocial behaviors.

Lastly, protective factors can exert their influence independently without necessarily acting as moderators or mediators (Loeber & Farrington, 2012; Lösel & Farrington, 2012; Ullrich & Coid, 2011). That is, they can predict the probability of low antisocial behavior in the absence of other factors. The trichotimiza- tion approach (Loeber & Farrington, 2012) has been used to investigate the direct protective effects of biological and psychosocial variables. This approach involves dividing participants’ scores on the biological protective factor to form three groups – upper, middle, and lower groups – and using the middle group as a reference or comparison group. With this approach, a significant difference between the lower and the reference groups with respect to the outcome var- iable (i.e. antisocial behaviors) indicates that this end of the variable may be a risk factor. On the other hand, a significant difference in the outcome variable between the higher and the comparison groups suggests that this end of the variable may work as a protective factor.

The practice of labeling a set of variables as strictly protective or risk related (Fergusson & Lynskey, 1996; Luthar, Cicchetti, & Becker, 2000; Rae- Grant, Thomas, Offord, & Boyle, 1989) has largely contributed to the devel- opment of assessment measures targeting only risk factors (e.g. Static 99, Hanson & Thornton, 1999) or protective factors (e.g. SAPROF; de Vogel et al., 2009). Indeed, some variables such as substance abuse and psychopathic traits are known to facilitate engagement in criminal activities whereas other set of variables such as religiosity tend to have more protective effects against criminal behaviors (Pearce, Jones, Schwab-stone, & Ruchkin, 2003). However, strictly grouping variables as either risk or protective can obscure their differential effects which in turn may negatively affect efforts to elu- cidate salient protective factors. Consistent with previous studies of psy- chosocial protective factors (Noltemeyer & Bush, 2013; Stouthamer-Loeber et al., 1993; Stouthamer-Loeber, Loeber, Wei, Farrington, & Wikström, 2002), this review has clearly shown that protective and risk effects co-occur in the

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same set of biological variables. Thus, to avoid the problem of generalizing a set of variables as risk or protective factors, it would be imperative to investigate what is construed as the Dose Hypothesis. This hypothesis states that the differential effect (risk, protective, and neutral) of biological and psychosocial criminogenic variables is influenced by their dose levels (e.g. high, medium, and low). Thus, a set of variables (e.g. EF; social support) could be examined and rated concurrently for their risk and protective effects. High and low scores in the variables in question do not necessarily imply less and high probabilities of antisocial behaviors, respectively, as this may depend on the type and nature of the variables, as well as individual char- acteristics (e.g. gender, age, and race). For example, individuals committing white-collar crimes are more likely to have high neurocognitive functioning (Raine et al., 2012), although we noted earlier that offenders in general are more likely to have EF deficits.

This hypothesis could be tested against several competing models in the liter- ature. For instance, a recently proposed model, the Triple Imbalance Hypothesis, by van Honk, Harmon-Jones, Morgan, and Schutter (2010) seeks to suggest that reactive aggressive behaviors are induced by low cortisol, low serotonergic, and high testosterone levels. These neurochemical changes are believed to facili- tate the down-regulation or decoupling of the cortical–subcortical communi- cation (i.e. weakens the PFC regulation of the amygdala). Granted the above, the interesting question is whether high cortisol, high serotonergic, and low testosterone may function as protective factors against aggressive behaviors. Moreover, although there is overwhelming contemporary evidence implicating the interaction between biological and psychosocial factors in criminal behav- iors, what is unclear or unexplored concerns the interaction, multiplicative, or synergistic effects of two or more biological protective factors, or biological and psychosocial protective factors at different dose levels in predicting low probability of offending. In another point of discussion, the differential impacts of biological protective factors on the two main types of aggressive behaviors: deliberate, instrumental, or planned and reactive or expressive (see Adjorlolo & Chan, 2015), are an interesting area since some offenders, especially homicide offenders, referred for assessment fall into one of the two categories. Insights gleaned from testing the Dose Hypothesis can provide empirical basis to refine the existing ‘risk factor-dominated’ assessment tools, while laying a solid and empirical foundation on which newer tools could be developed. This is another opportunity to develop tests to measure biological protective variables. These tests should not necessarily be developed as components of psychosocial risk assessment instrument. Instead, like the psychopathy checklist, they can be developed and administered as stand-alone measures. Some existing measures of neurocognitive functioning could be adapted and validated on offenders specifically.

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Implications for risk assessment

Based on the risk assessment equation postulated above, the more protective factors we are able to identify, both at the psychosocial and biological levels, the higher the probability that our risk estimation and risk management strategies will be, respectively, valid and efficient. Hypothetically, an individual with a high social network and support, high self-control, and high EF is more likely to desist from criminal activities compared to another person who scores low in these variables. Thus, incorporating biological protective factors into risk assessment practice, in addition to psychosocial protective factors, is very imperative, par- ticularly given the inverse relationship between the number of protective factors and the tendency to engage in criminal behaviors. Specifically, an increase in the number of protective factors may result in a decrease in violent behaviors (see Lösel & Farrington, 2012).

Another reason to include biological protective factors stems from the obser- vation that some psychosocial protective factors such as self-control, empathy, and problem-solving skills are underpinned or mediated by neuronal or brain processes, precisely the frontal lobe (Walsh & Bolen, 2012). These variables can be assessed at the biological level using biological measures such as neuropsy- chological tests to obtain somewhat objective data, thereby overcoming the limitations (e.g. recall bias; social desirability) inherent in the assessment of these variables using questionnaires, checklists, and interviews. Recent findings have suggested that measurements of risk factors at the biological level, using neu- roscientific and neuropsychological measures, were predictive of recidivism (Aharoni et al., 2013, 2014; Ross & Hoaken, 2011). Impliedly, neurobiological measures assessing neurobiological factors can enhance risk assessment evalu- ations and ultimately ensure valid and precise risk assessment decision-making.

Despite the general indication that biological protective factors are prom- ising candidates, several reasons may account for their neglect in risk assess- ment practice and research. Prominent among them include (1) persistent doubt about the role of biological processes in criminal behaviors, despite the emerging biosocial research findings; (2) difficulties in measuring and assessing several biological variables due to lack of knowledge and expertise; (3) the cost associated with undertaking some biological investigations relative to the use of questionnaires and checklists; (4) concerns regarding whether these factors are amenable to treatment or planned intervention; (5) whether the inclusion of these factors such as genetics will invoke ethical and legal issues (e.g. Is the consent of the individual needed in neuroscientific examinations – brain scan, psychophysiological examinations, or genetic analyses? Does the individual has the right not to consent to any intrusive examination?); and (6) possible delay in the criminal adjudication process given the time needed to gather some biological data, thus making the process not only somewhat lengthier but also increasing the cost of justice delivery. These concerns, however, should not

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daunt interest  to investigate the utility of potential biological factors in risk assessment practices. Notably, some of these purported challenges can be cir- cumvented via collaboration with professionals with expertise and experience in assessing and calibrating the biological protective factor in question. In some countries, like the United States, DNA is now collected on all arrestees, and measurement of resting heart rate is included in the standard medical practice at the community level (Glenn & Raine, 2014), thus reducing the challenges associated with accessibility.

Biological factors such as neuropsychological or neurocognitive factors are particularly worth considering given that they are (1) responsive to treatment (i.e. deficits in this domain can be mitigated with neurocognitive remediation program to facilitate desistance from criminal behaviors; Rocha, Marques, Fortuna, Antunes, & Hoaken, 2014); (2) easy to quantify and assess, thus requiring little expertise; and (3) highly studied biological criminogenic variables, particularly EF, and thus have a rich body of literature. As noted in the review, because high EF could serve as a protective factor, decisions regarding whether someone will act violently or aggressively in situations of uncertainty or when provoked could be influenced by his/her level of EF. Even where psychosocial factors such as strong commitment to school and work are identified as protective factors, executive abilities are still relevant. For instance, ability to inhibit unnecessary and provocative stimuli, evaluate the risk, and anticipate the consequences of one’s actions depend on ‘ade- quate’ neurocognitive processes. Initiation and sustaining prosocial behav- iors across a range of environments and situations ultimately depends on one’s neurocognitive capacity. Therefore, excluding neurocognitive factors and more broadly potential biological protective factors in risk assessment can lead to risk assessment results that may not reflect an individual’s true risk state (i.e. over or under-estimation of risk). As noted by the biopsychoso- cial model, every offender referred for assessment for risk of violence should be presumed to have both biological and psychosocial protective factors. However, the source (e.g. protective factors embedded in neurocognitive domain) and the strength of the protective factors may vary considerably from person to person. For example, although offenders with mental illness and those with cognitive disabilities may be grossly impaired in neurocogni- tive functioning, they may have psychophysiological and genetic protective factors. A very important and interesting finding is that risk and protective factors co-occur in the same set of biological variables.  This finding has been reported by studies of psychosocial factors (Noltemeyer & Bush, 2013; Stouthamer-Loeber et al., 1993, 2002). Thus, it would be informative to rate simultaneously a set of variables as both risk (vulnerability) and protective (strength) in estimating individual’s risk of future (re)offending.

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Summary and conclusion

Taken together, it is increasingly difficult to discount the fact that biological factors do protect some individuals from criminal behaviors. In general, high neuropsychological and psychophysiological functioning, as well as high MAOA activities (genetic) are promising biological correlates of desistance. The liter- ature is supportive of the view that both risk and protective factors co-occur or can occur in the same variables, questioning the practice of classifying a set of variables as strictly risk or protective. The major implication of this review, which is an attractive area of scholarly investigations, is that criminogenic vari- ables can have differential effects depending on their characteristics (e.g. high or low levels) – the Dose Hypothesis. In conclusion, the finding of this review is expected to generate enthusiasm among researchers and clinicians to investi- gate and incorporate not only psychosocial protective factors but also biological protective factors in risk assessment practices. We are optimistic that biological protective factors may help improve upon the predictive validity and accuracy of risk assessment instruments, and provide additional information to help in the treatment and management of offenders. To consolidate the preliminary findings reported in this review, including the proposed biospsychosocial model of criminal offending, future empirical investigations are certainly warranted. This is necessary not only to gain insight into how biological protective factors exert their influence, but also to shape and guide the formulation and valida- tion of theoretical and conceptual models, as well as assessment instruments. Importantly, the discussions, recommendations, and conclusions of this review neither diminish nor replace the influence of psychosocial protective factors in predicting desistance from criminal behaviors.

Disclosure statement

No potential conflict of interest was reported by the author.

References

Adjorlolo, S. (2016a). Diagnostic accuracy, sensitivity, and specificity of executive function tests in moderate traumatic brain injury in Ghana. Assessment. Advance online publication. doi:10.1177/1073191116646445

Adjorlolo, S. (2016b). Ecological validity of executive function tests in moderate traumatic brain injury in Ghana. The Clinical Neuropsychologist, 1–21. Advance online publication. doi:10.1080/13854046.2016.1172667

Adjorlolo, S., & Chan, H. C. O. (2015). The nature of instrumentality and expressiveness of homicide crime scene behaviors: A review. Trauma, Violence, & Abuse. Advance online publication. doi:10.1177/1524838015596528

Adjorlolo, S., & Egbenya, D. L. (2016). Executive functioning profiles of adult and juvenile male sexual offenders: A systematic review. The Journal of Forensic Psychiatry and Psychology. Advance online publication. doi:10.1080/14789949.2016.1141431

THE JOURNAL OF FORENSIC PSYCHIATRY & PSYCHOLOGY 125

Aharoni, E., Mallett, J., Vincent, G. M., Harenski, C. L., Calhoun, V. D., Sinnott-Armstrong, W., … Kiehl, K. A. (2014). Predictive accuracy in the neuroprediction of rearrest. Social Neuroscience, 9, 332–336.

Aharoni, E., Vincent, G. M., Harenski, C. L., Calhoun, V. D., Sinnott-Armstrong, W., Gazzaniga, M. S., & Kiehl, K. A. (2013). Neuroprediction of future rearrest. Proceedings of the National Academy of Sciences, 110, 6223–6228.

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.

Attrill, G., & Liell, G. (2007). Offenders views on risk assessment. In N. Padfield (Ed.), Who to release? Parole, fairness and criminal justice (pp. 191–201). Cullompton: Willan.

Barnes, J. C., Beaver, K. M., & Boutwell, B. B. (2011). Examining the genetic underpinnings to Moffitt’s developmental taxonomy: A behavioral genetic analysis. Criminology, 49, 923–954.

Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: Inferential and graphical techniques. Multivariate Behavioral Research, 40, 373–400.

Beaver, K. M. (2011). Environmental moderators of genetic influences on adolescent delinquent involvement and victimization. Journal of Adolescent Research, 26, 84–114.

Birbaumer, N., Veit, R., Lotze, M., Erb, M., Hermann, C., Grodd, W., & Flor, H. (2005). Deficient fear conditioning in psychopathy. Archives of General Psychiatry, 62, 799–805.

Borum, R., Bartel, P., & Forth, A. (2006). Manual for the structured assessment for violence risk in youth (SAVRY). Odessa, FL: Psychological Assessment Resources.

Bremer, J. F. (2001). Protective Factors Scale: Determining the level of intervention for youth with harming sexual behaviour. St Paul, MN: Project Pathfinder.

Brennan, P. A., Hall, J., Bor, W., Najman, J. M., & Williams, G. (2003). Integrating biological and social processes in relation to early-onset persistent aggression in boys and girls. Developmental Psychology, 39, 309–323.

Brennan, P. A., Raine, A., Schulsinger, F., Kirkegaard-Sorensen, L., Knop, J., Hutchings, B., … Mednick, S. A. (1997). Psychophysiological protective factors for male subjects at high risk for criminal behavior. American Journal of Psychiatry, 154, 853–855.

Byrd, A. L., & Manuck, S. B. (2014). MAOA, childhood maltreatment and antisocial behavior: Meta-analysis of a gene-environment interaction. Biological Psychiatry, 75, 9–17.

Caspi, A., McClay, J., Moffitt, T. E., Mill, J., Martin, J., Craig, I. W., … Poulton, R. (2002). Role of genotype in the cycle of violence in maltreated children. Science, 297, 851–854.

Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., … Braithwaite, A. (2003). Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science, 301, 386–389.

Choy, O., Raine, A., Portnoy, J., Rudo-Hutt, A., Gao, Y., & Soyfer, L. (2015). The mediating role of heart rate on the social adversity-antisocial behavior relationship: A social neurocriminology perspective. Journal of Research in Crime and Delinquency, 52, 303–341.

Cicchetti, D., Rogosch, F. A., & Thibodeau, E. (2012). The effects of child maltreatment on early signs of antisocial behavior: Genetic moderation by tryptophan hydroxylase, serotonin transporter, and monoamine oxidase-A-genes. Development and Psychopathology, 24, 907–928.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.

Connolly, E. J., & Beaver, K. M. (2014). Examining the genetic and environmental influences on self-control and delinquency: Results from a genetically informative analysis of sibling pairs. Journal of Interpersonal Violence, 29, 707–735.

126 S. ADJORLOLO

Cooke, D. J., & Michie, C. (2013). Violence risk assessment: From prediction to understanding- or from what? To why? In C. Logan & L. Johnstone (Eds.), Managing clinical risk: A guide to effective practice (pp. 3–25). Abingdon: Routledge.

de Ruiter, C., & Nicholls, T. L. (2011). Protective factors in forensic mental health: A new frontier. International Journal of Forensic Mental Health, 10, 160–170.

de Vogel, V., de Ruiter, C., Bouman, Y., & de Vries Robb′e, M. (2009). SAPROF: Guidelines for the assessment of protective factors for violence risk [English version of the Dutch original]. Utrecht: Forum Educatief.

de Vogel, V., de Vries Robbé, M., de Ruiter, C., & Bouman, Y. H. A. (2011). Assessing protective factors in forensic psychiatric practice: Introducing the SAPROF. International Journal of Forensic Mental Health, 10, 171–177.

de Vries-Bouw, M., Popma, A., Vermeiren, R., Doreleijers, T. A. H., Van De Ven, P. M., & Jansen, L. M. C. (2011). The predictive value of low heart rate and heart rate variability during stress for reoffending in delinquent male adolescents. Psychophysiology, 48, 1597–1604.

de Vries Robbé, M., de Vogel, V., & de Spa, E. (2011). Protective factors for violence risk in forensic psychiatric patients: A retrospective validation study of the SAPROF. International Journal of Forensic Mental Health, 10, 178–186.

de Vries Robbé, M., Mann, R. E., Maruna, S., & Thornton, D. (2015). An exploration of protective factors supporting desistance from sexual offending. Sexual Abuse: A Journal of Research and Treatment, 27, 16–33.

Douglas, K. S., Hart, S. D., Groscup, J. L., & Litwack, T. R. (2014). Assessing violence risk. In I. B. Weiner & R. K. Otto (Eds.), The handbook of forensic psychology (4th ed., pp. 385–411). Hoboken, NJ: Wiley.

Erath, S. A., El-Sheikh, M., & Cummings, E. M. (2009). Harsh parenting and child externalizing behavior: Skin conductance level reactivity as a moderator. Child Development, 80, 578–592.

Eriksson, Å., Hodgins, S., & Tengström, A. (2005). Verbal intelligence and criminal offending among men with schizophrenia. International Journal of Forensic Mental Health, 4, 191–200.

Fairchild, G., Van Goozen, S. H., Stollery, S. J., & Goodyer, I. M. (2008). Fear conditioning and affective modulation of the startle reflex in male adolescents with early-onset or adolescence-onset conduct disorder and healthy control subjects. Biological Psychiatry, 63, 279–285.

Farrington, D. P. (1994). Protective factors in the development of juvenile delinquency and adult crime. In 6th Scientifıc Meeting of the Society for Research in Child and Adolescent Psychopathology, London, UK.

Farrington, D.P. (1997). Early prediction of violent and non-violent youthful offending. European Journal on Criminal Policy and Research, 5, 51–66.

Farrington, D. P. (2007). Advancing knowledge about desistance. Journal of Contemporary Criminal Justice, 23, 125–134.

Fergusson, D. M., Boden, J. M., Horwood, L. J., Miller, A., & Kennedy, M. A. (2012). Moderating role of the MAOA genotype in antisocial behaviour. The British Journal of Psychiatry, 200, 116–123. doi:10.1192/bjp.bp.111.093328

Fergusson, D. M., Boden, J. M., Horwood, L. J., Miller, A. L., & Kennedy, M. A. (2011). MAOA, abuse exposure and antisocial behaviour: 30-Year longitudinal study. The British Journal of Psychiatry, 198, 457–463. doi:10.1192/bjp.bp.110.086991

Fergusson, D. M., & Lynskey, M. T. (1996). Adolescent resiliency to family adversity. Journal of Child Psychology and Psychiatry, 37, 281–292.

Fitzpatrick, K. M. (1997). Fighting among America’s youth: A risk and protective factors approach. Journal of Health and Social Behavior, 32, 131–148.

THE JOURNAL OF FORENSIC PSYCHIATRY & PSYCHOLOGY 127

Gao, Y., Raine, A., Venables, P. H., Dawson, M. E., & Mednick, S. A. (2010). Reduced electrodermal fear conditioning from ages 3 to 8 years is associated with aggressive behavior at age 8 years. Journal of Child Psychology and Psychiatry, 51, 550–558.

Giancola, P. R. (2000). Executive functioning: A conceptual framework for alcohol-related aggression. Experimental and Clinical Psychopharmacology, 8, 576–597.

Giancola, P. R., Martin, C. S., Tarter, R. E., Pelham, W. E., & Moss, H. B. (1996). Executive cognitive functioning and aggressive behavior in preadolescent boys at high risk for substance abuse/dependence. Journal of Studies on Alcohol, 57, 352–359.

Giancola, P. R., Mezzich, A. C., & Tarter, R. E. (1998). Executive cognitive functioning, temperament, and antisocial behavior in conduct-disordered adolescent females. Journal of Abnormal Psychology, 107, 629–641.

Giancola, P. R., Moss, H. B., Martin, C. S., Kirisci, L., & Tarter, R. E. (1996). Executive cognitive functioning predicts reactive aggression in boys at high risk for substance abuse: A prospective study. Alcoholism: Clinical and Experimental Research, 20, 740–744. doi:10.1111/j.1530-0277.1996.tb01680.x

Gibson, C. L., Piquero, A. R., & Tibbetts, S. G. (2001). The contribution of family adversity and verbal IQ to criminal behavior. International Journal of Offender Therapy and Comparative Criminology, 45, 574–592.

Glenn, A. L., & Raine, A. (2014). Neurocriminology: Implications for the punishment, prediction and prevention of criminal behavior. Nature Reviews Neuroscience, 15, 54–63. doi:10.1038/nrn3640

Gordis, E. B., Feres, N., Olezeski, C. L., Rabkin, A. N., & Trickett, P. K. (2010). Skin conductance reactivity and respiratory sinus arrhythmia among maltreated and comparison youth: Relations with aggressive behavior. Journal of Pediatric Psychology, 35, 547–558. doi:10.1093/jpepsy/jsp113

Guy, L. S., Douglas, K. S., & Hendry, M. C. (2010). The role of psychopathic personality disorder in violence risk assessments using the HCR-20. Journal of Personality Disorders, 24, 551–580.

Haberstick, B. C., Lessem, J. M., Hewitt, J. K., Smolen, A., Hopfer, C. J., Halpern, C. T., … Harris, K. M. (2014). MAOA genotype, childhood maltreatment, and their interaction in the etiology of adult antisocial behaviors. Biological Psychiatry, 75, 25–30.

Hanson, R. K., & Thornton, D. (1999). Static 99: Improving actuarial risk assessment for sex offenders. User report 99-02. Ottawa: Department of the Solicitor General of Canada.

Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin, 112, 64–105.

Huizinga, D., Haberstick, B. C., Smolen, A., Menard, S., Young, S. E., Corley, R. P., … Hewitt, J. K. (2006). Childhood maltreatment, subsequent antisocial behavior, and the role of monoamine oxidase A genotype. Biological Psychiatry, 60, 677–683.

Jones, N. J., Brown, S. L., Robinson, D., & Frey, D. (2014). Incorporating strengths into quantitative assessments of criminal risk for adult offenders: The service planning instrument. Criminal Justice and Behavior, 42, 321–338. doi:10.1177/0093854814547041

Joyal, C. C., Plante-Beaulieu, J., & de Chanterac, A. (2014). The neuropsychology of sex offenders: A meta-analysis. Sexual Abuse: A Journal of Research and Treatment, 26, 149–177. doi:10.1177/1079063213482842

Kagan, J., Reznick, J. S., & Snidman, N. (1987). The physiology and psychology of behavioral inhibition in children. Child Development, 58, 1459–1473.

Kandel, E., Mednick, S. A., Kirkegaard-Sorensen, L., Hutchings, B., Knop, J., Rosenberg, R., & Schulsinger, F. (1988). IQ as a protective factor for subjects at high risk for antisocial behavior. Journal of Consulting and Clinical Psychology, 56, 224–226.

128 S. ADJORLOLO

Kim-Cohen, J., Caspi, A., Taylor, A., Williams, B., Newcombe, R., Craig, I. W., & Moffitt, T. E. (2006). MAOA, maltreatment, and gene-environment interaction predicting children’s mental health: New evidence and a meta-analysis. Molecular Psychiatry, 11, 903–913.

Kindlon, D. J., Tremblay, R. E., Mezzacappa, E., Earls, F., Laurent, D., & Schaal, B. (1995). Longitudinal patterns of heart rate and fighting behavior in 9− through 12-year-old boys. Journal of the American Academy of Child & Adolescent Psychiatry, 34, 371–377.

Krohn, M. D., Lizotte, A. J., Bushway, S. D., Schmidt, N. M., & Phillips, M. D. (2014). Shelter during the storm: A search for factors that protect at-risk adolescents from violence. Crime & Delinquency, 60, 379–401.

Lahey, B. B., Loeber, R., Hart, E. L., Frick, P. J., Applegate, B., Zhang, Q., … Russo, M. F. (1995). Four-year longitudinal study of conduct disorder in boys: Patterns and predictors of persistence. Journal of Abnormal Psychology, 104, 83–93.

Lezak, M. D., Howieson, D. B., Bigler, E. D., & Tranel, D. (2012). Neuropsychological assessment (5th ed.). Oxford: Oxford University Press.

Li, J. J., & Lee, S. S. (2010). Latent class analysis of antisocial behavior: Interaction of serotonin transporter genotype and maltreatment. Journal of Abnormal Child Psychology, 38, 789–801. doi:10.1007/s10802-010-9409-y

Lodewijks, H. P. B., de Ruiter, C., & Doreleijers, T. A. H. (2010). The impact of protective factors in desistance from violent reoffending: A study in three samples of adolescent offenders. Journal of Interpersonal Violence, 25, 568–587.

Loeber, R., & Farrington, D. P. (2012). Advancing knowledge about direct protective factors that may reduce youth violence. American Journal of Preventive Medicine, 43(Suppl. 1), S24–S27. doi:10.1016/j.amepre.2012.04.031

Loeber, R., Pardini, D. A., Stouthamer-Loeber, M., & Raine, A. (2007). Do cognitive, physiological, and psychosocial risk and promotive factors predict desistance from delinquency in males? Development and Psychopathology, 19, 867–887.

Lorber, M. F. (2004). Psychophysiology of aggression, psychopathy, and conduct problems: A meta-analysis. Psychological Bulletin, 130, 531–552.

Lösel, F., & Bender, D. (1997). Heart rate and psychosocial correlates of antisocial behavior in high-risk adolescents. In A. Raine, P. A. Brennan, D. P. Farrington, & S. A. Mednick (Eds.), Biosocial bases of violence (pp. 321–324). New York, NY: Plenum.

Lösel, F., & Bliesener, T. (1990). Resilience in adolescence: A study on the generalizability of protective factors. In K. Hurrelmann & F. Lösel (Eds.), Health hazards in adolescence (pp. 299–320). Berlin: Walter de Gruyter.

Losel, F., & Bliesener, T. (1994). Some high-risk adolescents do not develop conduct problems: A study of protective factors. International Journal of Behavioral Development, 17, 753–777.

Lösel, F., & Farrington, D. P. (2012). Direct protective and buffering protective factors in the development of youth violence. American Journal of Preventive Medicine, 43(Suppl. 1), S8–S23. doi:10.1016/j.amepre.2012.04.029

Luthar, S. S., Cicchetti, D., & Becker, B. (2000). Research on resilience: Response to commentaries. Child Development, 71, 573–575.

Lynam, D., Moffitt, T., & Stouthamer-Loeber, M. (1993). Explaining the relation between IQ and delinquency: Class, race, test motivation, school failure, or self-control? Journal of Abnormal Psychology, 102, 187–196.

Masten, A. S., & Coatsworth, J. D. (1998). The development of competence in favorable and unfavorable environments: Lessons from research on successful children. American Psychologist, 53, 205–220.

Masten, A. S., Hubbard, J. J., Gest, S. D., Tellegen, A., Garmezy, N., & Ramirez, M. (1999). Competence in the context of adversity: Pathways to resilience and maladaptation from childhood to late adolescence. Development and Psychopathology, 11, 143–169.

THE JOURNAL OF FORENSIC PSYCHIATRY & PSYCHOLOGY 129

McCord, J., & Ensminger, M. E. (1997). Multiple risks and comorbidity in an African- American population. Criminal Behaviour and Mental Health, 7, 339–352.

Miller, H. A. (2006). A dynamic assessment of offender risk, needs, and strengths in a sample of pre-release general offenders. Behavioral Sciences & the Law, 24, 767–782.

Moffitt, T. E. (1993). The neuropsychology of conduct disorder. Development and Psychopathology, 5, 135–151.

Moffitt, T. E., & Caspi, A. (2001). Childhood predictors differentiate life-course persistent and adolescence-limited antisocial pathways among males and females. Development and Psychopathology, 13, 355–375.

Morgan, A. B., & Lilienfeld, S. O. (2000). A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function. Clinical Psychology Review, 20, 113–136. doi:10.1016/S0272-7358(98)00096-8

Nigg, J., Nikolas, M., Friderici, K., Park, L., & Zucker, R. A. (2007). Genotype and neuropsychological response inhibition as resilience promoters for attention-deficit/ hyperactivity disorder, oppositional defiant disorder, and conduct disorder under conditions of psychosocial adversity. Development and Psychopathology, 19, 767–786.

Noltemeyer, A. L., & Bush, K. R. (2013). Adversity and resilience: A synthesis of international research. School Psychology International, 34, 474–487.

Nordstrom, B. R., Gao, Y., Glenn, A. L., Peskin, M., Rudo-Hutt, A. S., Schug, R. A., … Raine, A. (2011). Neurocriminology. In D. L. B. Robert Huber & B. Patricia (Eds.), Advances in genetics (pp. 255–283). London: Academic Press.

O’Brien, T. C., Mustanski, B. S., Skol, A., Cook, E. H., Jr., & Wakschlag, L. S. (2013). Do dopamine gene variants and prenatal smoking interactively predict youth externalizing behavior? Neurotoxicology and Teratology, 40, 67–73. doi:10.1016/j.ntt.2013.09.002

Ogilvie, J. M., Stewart, A. L., Chan, R. C. K., & Shum, D. H. K. (2011). Neuropsychological measures of executive function and antisocial behavior: A meta-analysis. Criminology, 49, 1063–1107. doi:10.1111/j.1745-9125.2011.00252.x

Ortiz, J., & Raine, A. (2004). Heart rate level and antisocial behavior in children and adolescents: A meta-analysis. Journal of the American Academy of Child & Adolescent Psychiatry, 43, 154–162.

Pearce, M. J., Jones, S. M., Schwab-stone, M. E., & Ruchkin, V. (2003). The protective effects of religiousness and parent involvement on the development of conduct problems among youth exposed to violence. Child Development, 74, 1682–1696.

Portnoy, J., Chen, F. R., & Raine, A. (2013). Biological protective factors for antisocial and criminal behavior. Journal of Criminal Justice, 41, 292–299.

Portnoy, J., & Farrington, D. P. (2015). Resting heart rate and antisocial behavior: An updated systematic review and meta-analysis. Aggression & Violent Behavior, 22, 33–45.

Radke-Yarrow, M., & Brown, E. (1993). Resilience and vulnerability in children of multiple- risk families. Development and Psychopathology, 5, 581–592.

Rae-Grant, N., Thomas, B. H., Offord, D. R., & Boyle, M. H. (1989). Risk, protective factors, and the prevalence of behavioral and emotional disorders in children and adolescents. Journal of the American Academy of Child & Adolescent Psychiatry, 28, 262–268.

Raine, A. (1993). The psychopathology of crime. San Diego, CA: Academic Press. Raine, A. (2002). Annotation: The role of prefrontal deficits, low autonomic arousal, and

early health factors in the development of antisocial and aggressive behavior in children. Journal of Child Psychology and Psychiatry, 43, 417–434.

Raine, A. (2005). The interaction of biological and social measures in the explanation of antisocial and violent behavior. In D. M. Stoff & E. J. Susman (Eds.), Developmental psychobiology of aggression (pp. 13–42). New York, NY: Cambridge University Press.

130 S. ADJORLOLO

Raine, A., Laufer, W. S., Yang, Y., Narr, K. L., Thompson, P., & Toga, A. W. (2012). Increased executive functioning, attention, and cortical thickness in white-collar criminals. Human Brain Mapping, 33, 2932–2940. doi:10.1002/hbm.21415

Raine, A., Lencz, T., Bihrle, S., LaCasse, L., & Colletti, P. (2000). Reduced prefrontal gray matter volume and reduced autonomic activity in antisocial personality disorder. Archives of General Psychiatry, 57, 119–127. doi:10.1001/archpsyc.57.2.119

Raine, A., & Liu, J. H. (1998). Biological predispositions to violence and their implications for biosocial treatment and prevention. Psychology, Crime & Law, 4, 107–125.

Raine, A., Reynolds, C., Venables, P. H., & Mednick, S. A. (1997). Biosocial bases of aggressive behavior in childhood: Resting heart rate, skin conductance orienting, and physique. In A. Raine, P. A. Brennan, D. P. Farrington, & S. A. Mednick (Eds.), Biosocial bases of violence (pp. 107–126). New York NY: Plenum.

Raine, A., & Venables, P. H. (1981). Classical conditioning and socialization – A biosocial interaction. Personality and Individual Differences, 2, 273–283.

Raine, A., Venables, P. H., & Williams, M. (1990). Autonomic orienting responses in 15-Year- Old. The American Journal of Psychiatry, 147, 933–937.

Raine, A., Venables, P. H., & Williams, M. (1995). High autonomic arousal and electrodermal orienting at age 15 years as protective factors against criminal behavior at age 29 years. The American Journal of Psychiatry, 152, 1595–1600.

Raine, A., Venables, P. H., & Williams, M. (1996). Better autonomic conditioning and faster electrodermal half-recovery time at age 15 years as possible protective factors against crime at age 29 years. Developmental Psychology, 32, 624–630.

Rennie, C. E., & Dolan, M. C. (2010). The significance of protective factors in the assessment of risk. Criminal Behaviour and Mental Health, 20, 8–22. doi:10.1002/cbm.750

Rhodes, J. E., & Jason, L. A. (1988). Preventing substance abuse among children and adolescents. New York, NY: Pergamon Press.

Riggs, N. R., Jahromi, L. B., Razza, R. P., Dillworth-Bart, J. E., & Mueller, U. (2006). Executive function and the promotion of social-emotional competence. Journal of Applied Developmental Psychology, 27, 300–309.

Rocha, N. B. F., Marques, A. B., Fortuna, R. B., Antunes, A., & Hoaken, P. N. S. (2014). Effectiveness of cognitive remediation for female inmates: A pilot study. The Journal of Forensic Psychiatry & Psychology, 25, 224–237.

Rogers, R. (2000). The uncritical acceptance of risk assessment in forensic practice. Law and Human Behavior, 24, 595–605. doi:10.1023/A:1005575113507

Ross, E. H., & Hoaken, P. N. (2011). Executive cognitive functioning abilities of male first time and return Canadian federal inmates. Canadian Journal of Criminology and Criminal Justice, 53, 377–403.

Rothemund, Y., Ziegler, S., Hermann, C., Gruesser, S. M., Foell, J., Patrick, C. J., & Flor, H. (2012). Fear conditioning in psychopaths: Event-related potentials and peripheral measures. Biological Psychology, 90, 50–59. doi:10.1016/j.biopsycho.2012.02.011

Rutter, M. (1985). Resilience in the face of adversity. Protective factors and resistance to psychiatric disorder. The British Journal of Psychiatry, 147, 598–611.

Rutter, M. (1990). Psychosocial resilience and protective mechanisms. In J. Rolf, A. Masten, D. Cicchetti, K. H. Nuechterlein, & S. Weintraub (Eds.), Risk and protective factors in the development of psychopathology (pp. 181–214). Cambridge: Cambridge University Press.

Samek, D., Hicks, B., Keyes, M., Bailey, J., McGue, M., & Iacono, W. (2015). Gene–environment interplay between parent–child relationship problems and externalizing disorders in adolescence and young adulthood. Psychological Medicine, 45, 333–344.

Santor, D. A., Ingram, A., & Kusumakar, V. (2003). Influence of executive functioning difficulties on verbal aggression in adolescents: Moderating effects of winning and

THE JOURNAL OF FORENSIC PSYCHIATRY & PSYCHOLOGY 131

losing and increasing and decreasing levels of provocation. Aggressive Behavior, 29, 475–488.

Scurich, N., Monahan, J., & John, R. S. (2012). Innumeracy and unpacking: Bridging the nomothetic/idiographic divide in violence risk assessment. Law and Human Behavior, 36, 548–554.

Serin, R. C., Mailloux, D. L., & Wilson, N. J. (2012). The dynamic risk assessment of offender reentry (DRAOR). Unpublished user manual.

Shannon, K. E., Beauchaine, T. P., Brenner, S. L., Neuhaus, E., & Gatzke-Kopp, L. (2007). Familial and temperamental predictors of resilience in children at risk for conduct disorder and depression. Development and Psychopathology, 19, 701–727.

Simons, R. L., Beach, S. R. H., & Barr, A. B. (2012). Differential susceptibility to context: A promising model of the interplay of genes and the social environment. Advances in Group Processes, 29, 139–163. doi:10.1108/S0882-6145(2012)0000029008

Singh, J. P., Desmarais, S. L., & Van Dorn, R. A. (2013). Measurement of predictive validity in violence risk assessment studies: A second-order systematic review. Behavioral Sciences & the Law, 31, 55–73. doi:10.1002/bsl.2053

Skeem, J. L., & Monahan, J. (2011). Current directions in violence risk assessment. Current Directions in Psychological Science, 20, 38–42. doi:10.1177/0963721410397271

Spada, M. M., Nikčević, A. V., Moneta, G. B., & Wells, A. (2008). Metacognition, perceived stress, and negative emotion. Personality and Individual Differences, 44, 1172–1181. doi:10.1016/j.paid.2007.11.010

Sprague, J., Verona, E., Kalkhoff, W., & Kilmer, A. (2011). Moderators and mediators of the stress-aggression relationship: Executive function and state anger. Emotion, 11, 61–73.

Stattin, H., Romelsjö, A., & Stenbacka, M. (1997). Personal resources as modifiers of the risk for future criminality: An analysis of protective factors in relation to 18-year-old boys. British Journal of Criminology, 37, 198–223.

Stouthamer-Loeber, M., Loeber, R., Farrington, D. P., Zhang, Q., Van Kammen, W., & Maguin, E. (1993). The double edge of protective and risk factors for delinquency: Interrelations and developmental patterns. Development and Psychopathology, 5, 683–701.

Stouthamer-Loeber, M., Loeber, R., Wei, E., Farrington, D. P., & Wikström, P.-O. H. (2002). Risk and promotive effects in the explanation of persistent serious delinquency in boys. Journal of Consulting and Clinical Psychology, 70, 111–123.

Tseng, W.-L., & Gau, S. S.-F. (2013). Executive function as a mediator in the link between attention-deficit/hyperactivity disorder and social problems. Journal of Child Psychology and Psychiatry, 54, 996–1004. doi:10.1111/jcpp.12072

Ullrich, S., & Coid, J. (2011). Protective factors for violence among released prisoners – Effects over time and interactions with static risk. Journal of Consulting and Clinical Psychology, 79, 381–390. doi:10.1037/a0023613

van Goozen, S. H. M., Fairchild, G., Snoek, H., & Harold, G. T. (2007). The evidence for a neurobiological model of childhood antisocial behavior. Psychological Bulletin, 133, 149–182. doi:10.1037/0033-2909.133.1.149

van Honk, J., Harmon-Jones, E., Morgan, B. E., & Schutter, D. J. L. G. (2010). Socially explosive minds: The triple imbalance hypothesis of reactive aggression. Journal of Personality, 78, 67–94. doi:10.1111/j.1467-6494.2009.00609.x

Vanderbilt-Adriance, E., & Shaw, D. S. (2008). Protective factors and the development of resilience in the context of neighborhood disadvantage. Journal of Abnormal Child Psychology, 36, 887–901. doi:10.1007/s10802-008-9220-1

Viding, E., & Frith, U. (2006). Genes for susceptibility to violence lurk in the brain. Proceedings of the National Academy of Sciences, 103, 6085–6086. doi:10.1073/pnas.0601350103

132 S. ADJORLOLO

Viljoen, J. L., Mordell, S., & Beneteau, J. L. (2012). Prediction of adolescent sexual reoffending: A meta-analysis of the J-SOAP-II, ERASOR, J-SORRAT-II, and Static-99. Law and Human Behavior, 36, 423–438. doi:10.1037/h0093938

Vitacco, M. J., Erickson, S. K., Kurus, S., & Apple, B. N. (2012). The role of the Violence Risk Appraisal Guide and Historical, Clinical, Risk-20 in US courts: A case law survey. Psychology, Public Policy, and Law, 18, 361–391.

Walsh, A., & Bolen, J. D. (2012). The neurobiology of criminal behavior: Gene-brain-culture interaction. Burlington, VT: Ashgate.

Ward, T., & Beech, A. R. (2015). Dynamic risk factors: A theoretical dead-end? Psychology, Crime & Law, 21, 100–113. doi:10.1080/1068316X.2014.917854

Webster, C. D., Douglas, K., Eaves, D., & Hart, S. (1997). HCR-20: Assessing risk for violence, version 2. Burnaby: Simon Fraser University.

Webster, C. D., Martin, M. L., Brink, J., Nicholls, T. L., & Desmarais, S. (2009). Manual for the short-term assessment of risk and treatability (START ) (version 1.1). Port Coquitlam: Forensic Psychiatric Services Commission and St. Joseph’s Healthcare.

Weir, H., & Kosloski, A. E. (2015). Melding theoretical perspectives: A gendered look at low-resting heart rate and developmental trajectories of antisocial behavior. Criminal Justice Studies, 28, 104–123. doi:10.1080/1478601X.2015.1004915

Werner, E., & Smith, R. (1982). A longitudinal study of resilient children and youth. New York, NY: McGraw-Hill.

White, J. L., Moffitt, T. E., & Silva, P. A. (1989). A prospective replication of the protective effects of IQ in subjects at high risk for juvenile delinquency. Journal of Consulting and Clinical Psychology, 57, 719–724.

Widom, C. S., & Brzustowicz, L. M. (2006). MAOA and the “cycle of violence:” Childhood abuse and neglect, MAOA genotype, and risk for violent and antisocial behavior. Biological Psychiatry, 60, 684–689.

Windle, R. C., & Windle, M. (1995). Longitudinal patterns of physical aggression: Associations with adult social, psychiatric, and personality functioning and testosterone levels. Development and Psychopathology, 7, 563–585.

Worling, J. R. (2013). Desistence for adolescents who sexually harm (Unpublished document). Retrieved from http://www.erasor.org/new-protective-factors.html

Zagar, R. J., Busch, K. G., Isbell, S. A., & Hughes, J. R. (2009). An empirical theory of the development of homicide within individuals. Psychological Reports, 104, 199–245. doi:10.2466/PR0.104.1.199-245

Zara, G., & Farrington, D. P. (2013). Assessment of risk for juvenile compared with adult criminal onset implications for policy, prevention, and intervention. Psychology, Public Policy, and Law, 19, 235–249.

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