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. In the course, the following key topics will be covered, including clinical trial designs from traditional pharmacological, device, and non-pharmacological intervention studies to emerging work on SMART or other adaptive design approach; clinically meaningful intervention outcomes; New theories and research on intervention personalization and engagement; Mechanisms and causality in intervention studies; Multi-modality signal processing and data analysis for neurophysiological-behavioral data for interventions from both traditional biostatistics and emerging AI/machine learning perspectives; and Human-machine interface and other technical applications in personalization.
3 units · Medical Option (Med-Ltr-CR/NC)
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. In the course, the following key topics will be covered, including clinical trial designs from traditional pharmacological, device, and non-pharmacological intervention studies to emerging work on SMART or other adaptive design approach; clinically meaningful intervention outcomes; New theories and research on intervention personalization and engagement; Mechanisms and causality in intervention studies; Multi-modality signal processing and data analysis for neurophysiological-behavioral data for interventions from both traditional biostatistics and emerging AI/machine learning perspectives; and Human-machine interface and other technical applications in personalization.
Offered in Spring 2027 at Stanford University.