3 64 CHAPTER 3 framework on the basis of the findings of several meta-analyses (Hanson & Bussière, 1998; Hanson et al., 2009; Hanson & Morton-Bourgon, 2004, 2005; Helmus, Hanson et al., 2013) and of two large-scale recidivism prediction studies (Hanson et al., 2007; Knight & Thornton, 2007). The SRA need framework distinguishes between four domains of dynamic risk factors of adult male sex offenders, sexual interests, distorted attitudes, relational style, and self-management. These domains can be further divided into a number of subdomains (e.g., sexual interest can be subdivided into sexual preoccupation and offense-related sexual interests). The most widely used dynamic risk assessment instruments for adult male sex offenders all contain one or more dynamic risk factors from at least three of the four domains of the SRA need framework—for example, Assessment of Risk Manageability of Individuals with Developmental and Intellectual Limitations who Offend (ARMIDILO; Boer et al., 2013), Sex Offender Treatment Intervention and Progress Scale (SOTIPS; McGrath et al., 2013), STABLE-2007 (Fernandez et al., 2012), and Violence Risk Scale–Sexual Offender version (VRS:SO; Wong et al., 2003). In the first meta-analysis on the predictive properties of dynamic risk assessment instruments, we found that dynamic risk assessment instruments have small to moderate predictive properties for sexual and other types of recidivism in adult male sex offenders (van den Berg et al., 2018). Incremental predictive validity of dynamic over static risk assessment instruments was modest but significant. Above and beyond absolute scores, we found that change scores, which reflect changes in dynamic factors over time, significantly contributed to the prediction of sexual and other forms of recidivism (van den Berg et al., 2018). Although there is growing interest in and support for the predictive properties of dynamic risk assessment instruments, attempts to explain how dynamic risk factors cause offending or reoffending have been largely unsuccessful, partly because of a limited understanding of the interrelationships among these factors (Heffernan & Ward, 2017; Ward & Fortune, 2016b). A promising window into the structure and nature of the interrelationships among dynamic risk factors is offered by the network approach (Borsboom, 2017; Borsboom & Cramer, 2013; van den Berg et al., 2018). Network analysis has been applied to a range of topics, including depression, anxiety, posttraumatic stress, bereavement, autism, psychosis, substance abuse, personality, the general structure of psychiatric symptomatology, and more generally to quality of life (for a review, see Fried et al., 2017). The general goal of such applications is to assess the way constituent components of disorders (i.e., “symptoms”) relate to one another in a complex network; the hope is to elucidate the causal pathways that connect these symptoms. The current study is the first to apply this approach to the construct “recidivism risk” in adult men with a history of sexual offenses. We aim to determine the network structure of stable dynamic risk factors to increase our understanding of how these factors are interrelated and associated to recidivism. We believe that insights gained from network analyses may, ultimately, improve treatment effectiveness in adult men who committed sexual offenses.
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