6 132 CHAPTER 6 Non-sexual liking of children Affiliation with childhood Propensities model Network approach Emotional congruence with children Initiation contact with children child-like characteristics Non-sexual liking of children Affiliation with childhood Contact with children child-like characteristics A B Figure 6.2 Dynamic risk factor emotional congruence with children presented as (a; left) a latent variable within the Propensities Model, (b; right) a result of causal interacting risk-relevant emotion, cognition, and behavior. Figure and legend adapted with permission from “Understanding the Risk of Sexual Reoffending in Adult Men: A Network-Based Model,” by J. W. van den Berg et al., 2023, Sexual Abuse, p. 6. Advance online publication. Copyright © 2023 by the Author(s). Given these limitations of the Propensities Model, further theoretical work is needed to create a stronger foundation for empirically testable hypotheses concerning the development and nature of dynamic risk factors and how they impact the risk of sexual reoffending (Mann et al., 2010; Paquette & Cortoni, 2021; Prentky et al., 2015). In response to the limitations of the current Propensities Model, we propose a networkbased model that provides a coherent and empirically testable account regarding the risk of sexual reoffending. The next section describes the basic theoretical premises of our network approach applied to the risk of sexual reoffending. 6.2 NETWORK-BASED MODEL OF RISK OF SEXUAL REOFFENDING (NBM-RSR) The risk of sexual reoffending is dynamic in nature and varies over time and across contexts (Babchishin & Hanson, 2020; Lussier et al., 2020; Olver & Stockdale, 2020; Nitsche et al., 2022). The NBM-RSR assumes that risk of sexual reoffending: (A) Results from a self-sustaining network of causally interacting dynamic risk factors (van den Berg et al., 2020; van den Berg et al., 2022), (B) Is multifactorially determined through the construction of the network (i.e., the network topology; Borsboom et al., 2019). (C) Varies due to influences from both within and outside the dynamic risk factor network (i.e., the external field).
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