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Translation Research in Psychology: from lab to patient and back again

2018.12.10 | Anne-Mette Pedersen

Date Tue 19 Feb
Time 09:00 15:30
Location IMC Meeting Room, Jens Chr. Skous Vej 4, Building 1483-312
Registration has closed


Our understanding of why mental health difficulties occur and how we can treat them requires improvement. There is growing consensus that ‘translational research’ – from laboratory to patient and back again - is fundamental to understanding and improving treatment for mental health disorders. In this workshop, we bring together translational researchers working at different levels. We begin with work bridging the gap between basic neuroscience and treatment, and progress to the implementation of evidence-based treatments in real-world settings. The goal is to present key examples of translational psychological science, demonstrating how we can have a bidirectional flow of information from scientific discovery to practical application.





Prof. Inez Germeys, KU Leuven

Prof. Robert Whelan, Whelan Lab Trinity College Dublin

Dr. Katherine Young, King’s College London  

Dr. Richard LeBeau, Anxiety and Depression Research Center, UCLA 



Preliminary Programme

09.00 - 09.15    Introduction

09.15 - 10.15    From brain to mechanisms: Neuroscience of treatment mechanisms. Dr. Katie Young

10.15 - 11.15    From data to treatment predictors: Big data for Psychiatry. Prof. Robert Whelan

11.15 - 11.30    Interim Discussion

11.30 - 12.30    Lunch

12.30 - 13.30    From lab to the real world: Experience Sampling Methodology. Prof. Inez Germeys 

13.30 - 14.30    From RCTs to implementation: Testing the implementation of CBT for social anxiety in community settings. Dr. Richard LeBeau

14.30 - 15.30    Panel Discussion



Dr. Katherine Young

NIHR Maudsley Biomedical Research Centre Lecturer, King’s College London

Neural mechanisms of psychological treatments

Psychological treatments work. But they don’t always work, and they don’t work for everyone. Understanding how psychological treatments work (their ‘mechanisms’) is an important avenue of research, offering the potential to identify strategies for optimisation, personalization and innovation. Neuroimaging offers one approach to investigating mechanisms of psychological treatments, allowing exploration of patterns of brain activity that change through treatment or predict outcomes. In this talk I will review our current understanding of the mechanisms of psychological treatments for anxiety and depression from a neuroscientific perspective. I will also discuss how findings from neuroscience are beginning to inform development of novel psychological treatments.


Prof. Inez Myin-Germeys

Professor of Psychiatry, Leuven

Experience Sampling Methodology in Psychiatry: from macro to micro environment

Psychopathological symptoms are natural experiences emerging in the realm of ordinary daily life, often in interaction with contextual factors. In the mental health field, there is a growing awareness that the study of these symptoms in the context of everyday life, using Experience Sampling Methodology, may provide a powerful and necessary addition to more conventional research approaches. In my talk, I will work out two examples to demonstrate how using ESM may help in deepening our understanding of the actual processes related to the onset of symptoms as well as in improving interventions at an early stage. I will outline how ESM could be used in clinical practice as an assessment tool to increase our understanding of the psychiatric symptoms and the context in which they occur. In addition, I will give an example of an Ecological Momentary Intervention, a psychological intervention that is delivered in daily life, at moments when people most need it.


Richard LeBeau, Ph.D.

Department of Psychology, UCLA

Associate Director of Clinical Services for the Innovative Treatment Network, Semel Institute for Neuroscience and Human Behavior

From the Laboratory to the Community: The Art and Science of Disseminating Evidence-Based Psychological Interventions

In recent years, clinical scientists are increasingly recognizing that the broader context into which evidence-based psychological interventions are disseminated has a substantial influence on whether they are successfully integrated into routine care. This recognition has led to a shift in focus from dissemination to implementation, which is defined as the integration of a new practice within a specific setting or context. I will present an overview of three implementation projects currently under way in the Anxiety and Depression Research Center at UCLA, along with preliminary data. The first project focuses on delivering an evidence-based treatment (cognitive behavioral therapy for social anxiety disorder) in a novel setting (vocational services centers) to reach individuals who might not otherwise have access to such treatments. The second project focuses on improving the quality and efficiency of service delivery within a large health system (Veteran’s Affairs Hospitals) by training clinicians in evidence-based and computer-assisted interventions. The third project focuses on levering technology to more efficiently use available campus resources to tackle a worsening public health crisis (depression and suicidality among college students). The challenges of implementation work will be discussed, as will exciting new directions for this burgeoning field.


Robert Whelan PhD

School of Psychology & Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland

From data to treatment predictors: Big data for Psychiatry.

In this talk, I will advance the case for applying a ‘Big Data’ approach to advance psychiatry research and practice. In contrast to traditional approaches, Big Data is primarily data driven, using algorithms that search for patterns in data. Many different types of data can be included in a model and there are usually more data points than there are participants. The metric of success in Big Data approaches is usually the ability of a model to make accurate predictions on previously unseen data, rather than a comparison against the null hypothesis. Thus, Big Data is not merely a bigger version of the traditional scientific method, but can offer a substantially different perspective. Big Data approaches – by definition – require big data. Given the near-worldwide ubiquity of smartphones, it is now possible to deliver psychological interventions and to collect both questionnaire and task data from thousands of participants via apps. I will also discuss the ‘citizen scientist’ approach in which thousands of individuals complete short tasks on a daily basis. Furthermore, developments in data science facilitate the interrogation of large amounts of data to find meaningful patterns and predictors of behaviour at the level of the individual. I will present data from studies that applied machine learning to interrogate large datasets relevant to psychiatry.