University of Cambridge > Talks.cam > Department of Psychiatry & CPFT Thursday Lunchtime Seminar Series > Computer-based trainings as an add-on to the treatment of alcohol addiction: Where are we, how did we get there, and where should we go?

Computer-based trainings as an add-on to the treatment of alcohol addiction: Where are we, how did we get there, and where should we go?

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Abstract: Even after extensive treatment, more than half of the treated abstinent alcohol-dependent patients start drinking again. To reduce these high relapse rates, we have developed computer-based trainings, aiming to modify the patients’ automatic alcohol-approach tendencies by means of a simple joystick task. These alcohol-avoidance trainings have been surprisingly successful; they reduce relapse rates by about 10%, on average. In this talk, I will give an overview of the development, evaluation, and implementation of these trainings. I will address successes and failures, I will outline the many open questions that remain, and I will briefly describe extensions of the training to other disorders.

Biography: Mike Rinck is an Associate Professor at Radboud University Nijmegen, The Netherlands, and an Adjunct Professor at Ruhr-University Bochum, Germany. He was trained as a cognitive psychologist; and he was always highly interested in applied research questions. His main research area is experimental psychopathology: He studies biased cognitive processes such as attention, learning, memory, associations and interpretations in various mental disorders. More recently, he worked in the area of Cognitive Bias Modification, that is, the use of computerized training programs designed to re-train biased cognitive processes. His special area of expertise centers around the assessment and modification of automatic approach-avoidance tendencies in various mental disorders. For more information on Prof Rinck, please visit: https://www.ru.nl/english/people/rinck-m/

This talk is part of the Department of Psychiatry & CPFT Thursday Lunchtime Seminar Series series.

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