7 155 DISCUSSION interrelationship of currently known dynamic risk factors. Future studies could test and validate these hypotheses through directed networks derived from data of the repeated measurements obtained, for example, through ESM measurements using single case experimental designs (Barlow et al., 2009, Burger et al., 2020; Epskamp et al., 2018; Kuppens & Myin-Germeys, 2022; Pearl & Mackenzie, 2018). Sixth, although not directly related to research aims and research questions in this dissertation, future and more elaborate network models could take protective factors into account and place them within the network of dynamic risk factors or the external field. Seventh, propositions derived from the NBM-RSR should be tested to further our understanding of the risk of sexual reoffending and to stimulate theoretical discussion on this topic. These propositions revolve around a) risk of sexual reoffending resulting from the construction of a network of causally connected dynamic risk factors, b) network stability, sudden changes, and critical transitions, and c) dynamic risk factors’ relative influence on risk of sexual reoffending. Future research could test whether the risk of sexual reoffending results from a network of causally related dynamic risk factors by investigating the added predictive accuracy of algorithms to estimate the risk of sexual reoffending when the density and connectivity of the network are considered above and beyond the number and strength of dynamic risk factors. Another approach to demonstrate the influence of the network construction on recidivism risk is to examine to what extent both the density and connectivity of the network of dynamic risk factors predict sexual reoffending in adult men with a history of sexual offenses matched on the number and strength of dynamic risk factors. The proposition of the existence of network stability, sudden changes, and critical transitions in networks of dynamic risk factors should also be investigated. To examine this, future research might explore the existence of early warning signals within the network of dynamic risk factors, which are within-system changes in dynamics indicative of a transition from one state to another (Kossakowski, 2020; Scheffer et al., 2012). Also, the proposition regarding dynamic risk factors’ relative influence on risk of sexual reoffending could be investigated. Simulation studies could be conducted to test whether dynamic risk factors with a higher centrality (i.e., having an upsurged number of relatively strong interrelations with other dynamic risk factors) or forming a connection between two or more communities of dynamic risk factors (i.e., being a bridge factor) indeed have relatively stronger impact on networks and therefore on risk of sexual reoffending (Castro et al., 2019; McNally, 2016; Opsahl et al., 2010). An alternative approach to examining the proposition about the relative influence of dynamic risk factors is to test the hypothesis that treatment and risk management strategies focusing on dynamic risk factors with high influence on a network of dynamic risk factors result in a relatively larger reduction in future sexual offending. Eight, ESM methodology can be applied to enhance current individual and group therapy of adult men with a history of sexual offenses. After all, participants involved in the blended ESM procedure reported increased awareness in personal patterns of risk-relevant
RkJQdWJsaXNoZXIy MjY0ODMw