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Using basic neurobiological measures in criminological research

Research on the relationship between neurobiological factors and antisocial behavior has grown exponentially in recent decades. As a result, criminal behavior has been related to impairments in different biological systems, such as genetics, hormones and brain functioning. The development of innovative techniques, for example brain imaging techniques and physiological measurements, can partially explain the increase in neurobiological studies on criminal behavior. Despite a recent zeitgeist change, which has led to a greater acceptance of neurobiology as an additional approach for the study of criminal behavior, neurobiological measurements dot not yet play a more significant role in criminological research and practice. This article aims to familiarize crime researchers and other interested readers with two important neurobiological measures, namely neuropsychological assessment and resting heart rate measurement, and with how these measures can play an important role in criminological research. It will argue that neuroscientific approaches might benefit the field of criminology in several important ways, from assessing the empirical validity of criminological theories to improving the effectiveness of correctional intervention programs. Furthermore, this article will provide insight into how to use these measures in research, to guide interested readers towards their application in their own studies.

Using the biopsychosocial model for identifying subgroups of detained juveniles at different risk of re-offending in practice: a latent class regression analysis approach

Juvenile delinquents constitute a heterogeneous group, which complicates decision-making based on risk assessment. Various psychosocial factors have been used to define clinically relevant subgroups of juvenile offenders, while neurobiological variables have not yet been integrated in this context. Moreover, translation of neurobiological group differences to individual risk assessment has proven difficult. We aimed to identify clinically relevant subgroups associated with differential youth offending outcomes, based on psychosocial and neurobiological characteristics, and to test whether the resulting model can be used for risk assessment of individual cases.