Cognitive Behavior Therapy for Anxious Adolescents: Developmental Influences on Treatment Design and Delivery

Anxiety disorders in adolescence are common and disruptive, pointing to a need for effective treatments for this age group. Cognitive behavior therapy (CBT) is one of the most popular interventions for adolescent anxiety, and there is empirical support for its application. However, a significant proportion of adolescent clients continue to report anxiety symptoms post-treatment. This paper underscores the need to attend to the unique developmental characteristics of the adolescent period when designing and delivering treatment, in an effort to enhance treatment effectiveness. Informed by the literature from developmental psychology, developmental psychopathology, and clinical child and adolescent psychology, we review the ‘why’ and the ‘how’ of developmentally appropriate CBT for anxious adolescents. ‘Why’ it is important to consider developmental factors in designing and delivering CBT for anxious adolescents is addressed by examining the age-related findings of treatment outcome studies and exploring the influence of developmental factors, including cognitive capacities, on engagement in CBT. ‘How’ clinicians can developmentally tailor CBT for anxious adolescents in six key domains of treatment design and delivery is illustrated with suggestions drawn from both clinically and research-oriented literature. Finally, recommendations are made for research into developmentally appropriate CBT for anxious adolescents

Saving Human Lives: What Complexity Science and Information Systems can Contribute

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.Comment: 67 pages, 25 figures; accepted for publication in Journal of Statistical Physics [for related work see http://www.futurict.eu/

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

© Springer Nature Switzerland AG 2018. A major problem in the field of peace and conflict studies is to extract events from a variety of news sources. The events need to be coded with an event type and annotated with entities from a domain specific ontology for future retrieval and analysis. The problem is dynamic in nature, characterised by new or changing groups and targets, and the emergence of new types of events. A number of automated event extraction systems exist that detect thousands of events on a daily basis. The resulting datasets, however, lack sufficient coverage of specific domains and suffer from too many duplicated and irrelevant events. Therefore expert event coding and validation is required to ensure sufficient quality and coverage of a conflict. We propose a new framework for semi-automatic rule-based event extraction and coding based on the use of deep syntactic-semantic patterns created from normal user input to an event annotation system. The method is implemented in a prototype Event Coding Assistant that processes news articles to suggest relevant events to a user who can correct or accept the suggestions. Over time as a knowledge base of patterns is built, event extraction accuracy improves and, as shown by analysis of system logs, the workload of the user is decreased