Dynamic Individual Risk Networks: Personalized Network Modelling Based on Experience Sampling Data

Abstract

Following a network perspective, risk of sexual reoffending can be understood as a construct that emerges from the interactions between risk factors. If these interrelationships are validly mapped out, this leads to an increased understanding of the risk and thus may contribute to more effective and/or more efficient interventions. This paper reports on personalized network modeling mapping the interrelationships of dynamic risk factors for an individual convicted of sexual offenses, using experience sampling (ESM) based on Stable-2007 items. The longitudinal character of ESM enables both the assessment of interrelations between risk factors within a timeframe and the relationships between risk factors over time. Networks are calculated and compared to the clinical assessment of interrelationships between the risk factors.