NON-PHARMACOLOGICAL INTERVENTIONS IN LATE-LIFE DEPRESSION AND LATE-LIFE ANXIETY

The American Journal of Geriatric Psychiatry(2020)

引用 0|浏览6
暂无评分
摘要
Mindfulness, Mindfulness Based Cognitive Therapy MBCT and based Problem-solving therapy (PST) techniques have emerging research supporting them as positive additions to treatment as usual/standard care for mood, anxiety and/or cognitive disorders among older adults. This session will highlight this recent research and evidence of the benefits of these interventions in the context of late-life depression (LLD) and late-life anxiety (LLA). In the spirit of the 2020 American Association of Geriatric Psychiatry (AAGP) conference's theme of partnership, these results are presented by a team of researchers located at McGill University, Montreal, Quebec, Canada and the University of Western Ontario, London, Ontario, Canada, working with a variety of interdisciplinary stakeholders and contexts. The aim of this session is to present findings of non-pharmacological, meditation-based intervention clinical trials for, LLD and LLA, as well as potential effects on cognition. The session will be chaired by Soham Rej MD. Emily Ionson M.Sc. will present research findings that examined the feasibility and efficacy of implementing case manager-delivered group-based Problem-solving therapy for LLD in a real-world community setting. Marouane Nassim, M.Sc., will be presenting an RCT examining the efficacy of a chair-side mindfulness intervention compared to an active control condition, the Health Enhancement Program (HEP), in the treatment of depression and anxiety for older patients on hemodialysis. Elena Dikaios, B.A., will present findings of a study examining whether continuation groups are helpful to maintain sustained therapeutic effects of MBCT for late-life depression and anxiety patients in primary care. Following the presentations, there will be an interactive discussion, led by Dr. Akshya Vasudev (discussant) and Dr. Rej, concerning the clinical applications of these interventions and directions for future research.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要