Special interest groups
EUNETHYDIS also facilitates Special Interest Groups (SIGs) that consist of EUNETHYDIS members that work on similar topics. Currently there are 3 SIGs active within EUNETHYDIS:
SIG on ‘Motivation and its relation to ADHD’More info
The general goal of this SIG is to make a start with broadening our view on motivation as it is relevant to the functioning of individuals with ADHD and to the efficacy of their treatment. While the notion that a motivational pathway plays a significant role in the development of ADHD symptoms is well established, motivation as such has been studied only in a very narrow way in the context of ADHD (i.e., effects of rewards on behaviour/choices). However, motivational theories show that motivation is a much richer concept that covers more than extrinsic motivation alone. Therefore, this SIG aims at considering and studying motivation in a richer and fuller manner in individuals with ADHD.
SIG on ‘ADHD Neurotherapies in ADHD’More info
The last two decades of basic neuroimaging in ADHD have delineated consistent brain dysfunctions that lend themselves as suitable targets for neurotherapies. While EEG-NF has been around for 50 years, newer and spatially better resolved imaging techniques that can target these brain dysfunctions in a more specific way have more recently been applied as neurotherapies for ADHD such fMRI-NF or NIRS Neurofeedback. Other ways to modify brain function is by brain stimulation methods such as TMS or transcranial direct current stimulation (tDCS) that have been more applied to other disorders but also recently have shown to be of promise, in particular in combination with cognitive training. Based on the above, this Special Interest Group on ADHD Neurotherapy aims to provide a platform for promoting research into the neurotherapy of ADHD.
SIG on ‘Risk prediction in ADHD/Psychiatry’More info
Research has established that individuals with ADHD are at increased risk for many poor outcomes. An important next goal, not the least because there are interventions available for ADHD with beneficial effects (e.g., ADHD medication), is to develop tools that identify individuals with ADHD who are at low versus high risk of such poor outcomes. Such prediction models could provide additional information to aid treatment decisions and help clinicians identify those who might benefit from more careful monitoring or preventive treatment. Suitable data sources (e.g., electronic health records, national registers and large cohort studies) are now available at different places across the world which can be combined with classic (e.g., regression-based methods) and/or novel (e.g., machine learning/artificial intelligence) approaches to assess the accuracy of prediction models in psychiatry. In fact, recent studies have demonstrated the feasibility of developing risk prediction models in psychiatry, but the literature is still very limited, and many issues remain to be resolved.
Among many things this SIG will address:
- Clinical needs, utility, and implementation, ethical aspects
- What can be offered to ADHD high risk groups and how should we balance between specificity and sensitivity, as well as risk and benefits
- Level of accuracy sufficient for clinical implementation
- Type of model validation should be required for prediction models
- Methodologic features that should be required of prediction modeling studies
- Minimal reporting guidelines for prediction modeling studies
- How generalization of prediction models to different types of populations (e.g., clinical vs. community) or different geographic regions or ethnicities should be addressed