Page 129 - Age of onset of disruptive behavior of residentially treated adolescents -Sjoukje de Boer

Directions for Future Research
The present thesis aimed at identifying subgroups within a clinical inpatient
cohort of youths characterized by both psychiatric disorders and severe disruptive behavior based on the age of onset of their disruptive behavior. This was prompted by
the idea that differentiation in subgroups may benefit intervention and may eventually
result in more individualized and appropriate intervention and as a consequence
better treatment results (Vermeiren, 2003). Results of the present thesis indicated
that in clinical practice, the EO and AO sub classification has limited value for such differentiation. Beside the finding that EO disruptive behavior was predictive of dropout, the EO and AO sub classification did not seem to yield much in terms of outcome. However, we cannot generalize our findings to other clinical samples. For 7 that purpose, research should focus on other clinical samples, for instance those with predominantly disruptive behavior and specific psychiatric disorders or minor psychiatric problems. Given previous research questioning the clinical usefulness of the
age of onset distinction (Colins & Vermeiren, 2013; Jambroes et al., 2016), it is unlikely
that such research will give positive results. For this reason, it is of interest to focus on
other factors as well, such as the recently promoted LPE specifier (DSM 5).
Although one may wonder whether making any subdivision is useful at all, dividing into subgroups should help clinicians to develop and offer more tailor made, comprehensive and individualized interventions. Hence the question is how we can sub-classify a very complex clinical sample with severe disruptive behavior and co- occurring psychiatric disorders in such a way that treatment can be applied more effectively. Instead of examining dichotomous subdivisions, dimensional approaches are probably more useful. Brazil and colleagues for instance, advocate an approach that describes each individual as a combination of multidimensional traits (Brazil, Van Dongen, Maes, Mars, & Baskin-Sommers, 2018). In this, a combination of interacting biological (e.g., genetic, brain, and physiological) and cognitive (e.g., executive functioning, social cognition) dimensions should be considered (Brazil et al., 2018), which is in line with the vision of the Research Domain Criteria (RDoC)(Insel et al., 2010). This RDoC project was launched by the National Institute of Mental Health (NIMH) to create a new classification framework for research on mental disorders. In
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