Publications

Background and aims: Models of alcohol use risk suggest that drinking motives represent the most proximal risk factors on which more distal factors converge. However, little is known about how distinct risk factors influence each other and alcohol use on
different temporal scales (within a given moment versus over time). We aimed to estimate the dynamic associations of distal (personality and life stressors) and proximal
(drinking motives) risk factors, and their relationship to alcohol use in adolescence and early adulthood using a novel graphical vector autoregressive (GVAR) panel network
approach
Conclusions: Heavy and frequent alcohol use, along with social drinking motives, appear
to be key targets for preventing the development of alcohol-related problems throughout late adolescence. We found no evidence for personality traits and life stressors predisposing towards distinct drinking motives over time

Samenvatting: De sociale omgeving bepaalt voor een belangrijk deel hoe mensen over zichzelf en hun uiterlijk denken. Maar wat anderen precies denken, is vaak een kwestie van gissen en leiden we meestal af uit hoe zij zich ten opzichte van ons gedragen.

In deze bijdrage beschreven we dat inschattingen van het oordeel van anderen onderhevig zijn aan interpretaties en vertekeningen. We hebben een aantal van deze vertekeningen toegelicht en geprobeerd bij elkaar te brengen.

This paper aims to address some of the challenges of EMA data modeling by grouping or clustering similar individuals. A detailed review of all the potential directions for applying
clustering based on time-series patterns. (...) A combination of several well-known ad-hoc evaluation measures was proposed, examining
clustering quality through Silhouette coefficients as well as stability. According to our analysis, kernel-based clustering methods produced the best quality clusters, showing that kernels can be useful for efficient EMA data representations. Suggestions for future work are given. 

Manhapra offers an interesting clinicians’ perspective on acute pain and how chronic pain differs from acute pain. We agree with most of the author’s ideas but would like to add further clarification about 2 issues.(...) Disability becomes more likely when priority is given to controlling pain vs pursuing nonpain goals. A key challenge for researchers and clinicians is finding ways to shift the balance towards exploring various ways to continue daily life, rather than sticking to the limiting protective actions.(...) Second, the differentiation between acute and chronic pain has a long history and remains a topic of debate.

The current study is one of the first to apply network intervention analysis to examine the putative change processes of a psychotherapy.
Results: Contrary to the expectation that intervention effects would pass indirectly to outcomes via processes, network analysis indicated that two anxiety-related outcomes of the trial may have acted as primary mechanisms of the intervention on other outcome and process variables. 
Conclusions: Network intervention analysis facilitated flexible evaluation of ACT’s change processes, and offers a new way to test whether change occurs as theorized in psychotherapies.

We show that the TSST can be harnessed to induce an emotional episodic memory that is sensory-rich and personally meaningful. (...) The TSST has the potential to extend our arsenal of tools for studying the role of emotional memory in symptoms of psychopathology across a range of disorders. Overall, this study contributes to the development of ecologically valid methods for inducing and assessing episodic memory in the lab, which is a necessary first step towards critically testing assumptions regarding the role of emotional memory in psychopathology

In this paper we present emotional memory as a promising candidate for causing a range of transdiagnostic symptoms, and therefore,  deserving a place high on the clinical research agenda. Meanwhile, the arguments made throughout this article may apply to other putative common causes in psychopathology as well. (...) To understand how exactly emotional memory can be depicted in a network, we do not only need more specific criteria in terms of the network architecture, but we also need to clarify the construct at hand and its role in mental disorders. (...) To move forward from here, we argue that the research priority should be to expand the conceptualisation and operationalisation of constructs that are viewed as driving factors in psychopathology.

We believe that the authors’ ideas are interesting and deserve further thought. We also agree that we need a better understanding of the link between acute and chronic pain, and that current constructs such as central sensitization have clear limitations. On the other hand, we also believe that the pain type idea put forward by Finnerup et al.,4 albeit more diversified, may suffer from the same conceptual limitations as central sensitization: both share the common assumption that the behavioral manifestations of pain (the symptoms) are caused by a physiological event either at the central or at the peripheral nervous system (such as injury or inflammation). The consequence of this line of thought is a focus on the identification of the common cause, and when treated appropriately, the observable symptoms should disappear. To the exasperation of many, a common cause for (chronic) pain cannot always be identified, which seriously compromises the search for a successful treatment. A different approach is needed.

This research work highlights the importance of exploiting the wealth of EMA data through more advanced ML models compared to linear ones. Non-linear vs. linear and idiographic vs. nomothetic approaches were investigated for classifying a target variable at a next time-point on different datasets. The results showed great consistency for the idiographic approach, showing that non-linear models yield an enhanced performance on both synthetic and real-world data. (...) Overall, the proposed knowledge distillation method could be recognized as the most beneficial to improve performance of personalized models. However, the differences in both idiographic and nomothetic approaches were not found statistically significant. As a future step, further experiments are needed on more (and larger) datasets for evaluating the examined approaches.

The core ideas of a 10-year research program ‘New Science of Mental Disorders’ are outlined. This research program moves away from the disorder-based ‘one-model-fits-all’ approach to treating mental disorders, and adopts the network approach to psychopathology as its foundation of research. Its core assumption is that dynamically interacting symptoms constitute the disorder. (...) Starting from the foundation of the network approach to psychopathology, our multi-layered (mapping, zooming, targeting) research program intends to further develop this approach, and to critically examine if and how it can transform current clinical practice.(...) If our  research supports the validity and effectiveness of this approach, the ultimate goal is the implementation of network-informed diagnoses and network-based interventions in clinical practice.

In current classifcation systems, selective mutism (SM) is included in the broad anxiety disorders category. Indeed, there is abundant evidence showing that anxiety, and social anxiety in particular, is a prominent feature of SM. In this article, we point out that autism spectrum problems in addition to anxiety problems are sometimes also implicated in SM. To build our case, we summarize evidence showing that SM, social anxiety disorder (SAD), and autism spectrum disorder (ASD) are allied clinical conditions and share communalities in the realm of social difculties. (...) It is not our intention to downplay the role of (social) anxiety in SM, but rather we want to point out that SM may also be connected to ASD and that this may have important implications for the clinical management as well as research of children with this disorder.