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Courses

Personalization intervention and aging-related mental health

Description: Personalized interventions refer to those in which the design features are selected based on characteristics of the individual, so that the final intervention is unique to a person or a group of people. Aging-related mental health problems (e.g., dementia, late-onset geriatric depression, etc.) are among the most prevalent and challenging health problems worldwide.  The objective of the curriculum is to provide individuals from engineering or clinical background with a comprehensive and up-to-date overview on intervention research targeting aging-related mental health, guided by principles of personalization. At the end of the course, course attendees will be paired up, based on their technical or clinical knowledge and experience and application interest, to design personalized intervention, and establish a comprehensive understanding of intervention research and aging-related mental health outcomes. Principles of personalization will be integrated into the curriculum. The curriculum will serve for growing advanced interdisciplinary scholars in the field of personalized interventions, particularly in the context of aging-related mental health.

Session        

Topic

Description

References/materials

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Example lecture: personalized cognitive training for dementia prevention

A special lecture highlighting the application of personalized cognitive training for the prevention of dementia, offering a practical illustration of course concepts.

Clinical trial design I: Pharmacological and device studies

Examination of various clinical intervention designs, comparing pharmaceutical and device trials, as well as preclinical and clinical phases of development; also discuss emerging work on SMART or other adaptive design approach.

Clinical trial design II: Non-pharmacological studies

Examination of various clinical intervention designs, comparing various types of non-pharmaceutical trials, as well as preclinical and clinical phases of development; also discuss emerging work on SMART or other adaptive design approach.

Clinically meaningful intervention outcomes – neuropsychiatry and neuropsychology

Evaluation of intervention outcomes with a focus on clinically meaningful results in both neuropsychiatry and neuropsychology, emphasizing real-world implications.

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New theories and research on intervention personalization and engagement

Examination of emerging theories and research methodologies that enhance personalization and engagement in interventions, ensuring a comprehensive understanding of current practices.

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Mechanisms and causality in intervention studies

Exploration of mechanisms on brain function and mind-body connection in mental health interventions; study of study designs and analytical methods that establish causality in intervention research, providing a foundation for robust scientific inquiry.

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Multi-modality signal processing and data analysis for neurophysiological-behavioral data for interventions I

Analysis and signal processing techniques for interpreting neurophysiological and behavioral data, facilitating a deeper understanding of intervention outcomes. Emerging AI/machine learning oriented perspective.

Multi-modality signal processing and data analysis for neurophysiological-behavioral data for interventions II

Analysis and signal processing techniques for interpreting neurophysiological and behavioral data, facilitating a deeper understanding of intervention outcomes. Biostatistics oriented perspective.

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Human-machine interface and other technical applications in personalization

In-depth study of the integration of human-machine interfaces in the personalization of interventions, exploring how technology enhances individualized approaches.

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