This course discusses recent developments in the evidence-based treatment and management of obsessive-compulsive disorder (OCD). New and emerging advances in treatment of OCD is reviewed from clinical and translational research studies. Evidence is reviewed including the refinement of assessment methods for diagnosis, the importance of early intervention, relapse prevention, and novel strategies to address treatment resistant OCD. New areas of research around obsessive-compulsive spectrum disorders are discussed as novel forms of treatment are needed to manage these related, but distinct, psychological health problems.

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This course is intended for practitioners who work with individuals and/or groups that have experienced trauma. The supporting article details the ways in which individuals within a given society react to different types of trauma, and the consequent ways that such individuals construct meaning. This report also explores the process of meaning-making at the collective level among both victims and perpetrators. The article is divided into two parts. Part one focuses on victims, and their desire to remember and create a group narrative around the respective trauma. Conversely, part two focuses on perpetrators. An exploration of the changing nature of trauma is further considered with reference to the impact of trauma. Specifically, consideration is given to the way that individuals create meaning for the past, the ways that individuals navigate present challenges respective of the endured traumas, and related preparation for future generations.

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Artificial intelligence (AI) has many applications to mental health treatments. Outcomes for use of AI in mental health treatment are promising. The authors performed an analysis of ethical and social considerations in the use of AI in psychiatry, psychology, and psychotherapy. Major themes identified were anticipated benefits of AI; harm prevention and data ethics; lack of guidance on development, integration, and training; and potential for misuse. Challenges in applications included risk assessment, referrals, and supervision; respecting patient autonomy; uniqueness of human interactions; ethical issues with algorithms; and long-term effects. The authors review potential long-term implications of AI for mental health services and provide recommendations for developing ethical guidelines related to AI in mental health treatment.

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