This course is aimed at intervention scientists working in any area--including public health, education, criminal justice, and others—interested in learning about an innovative framework for conducting intervention research. This course will show you how to use the multiphase optimization strategy (MOST) to: streamline interventions by eliminating inactive components; identify the combination of components that offers the greatest effectiveness without exceeding a defined implementation budget; develop interventions for immediate scalability; look inside the “black box” to understand which intervention components work and which do not; and improve interventions programmatically over time. In this course you will relate the MOST framework to your research objectives; learn how MOST differs from the standard approach to intervention development and evaluation; learn how to complete the preparation and optimization phases of MOST; and become familiar with rigorous and highly efficient experimental designs that will enable you to examine the performance of individual intervention components.
Offert par
Introduction to the Multiphase Optimization Strategy (MOST)
New York UniversityÀ propos de ce cours
Statistics for the behavioral/social sciences at least through multiple regression
Background in behavioral intervention science
Statistics for the behavioral/social sciences at least through multiple regression
Background in behavioral intervention science
Offert par
New York University
New York University is a leading global institution for scholarship, teaching, and research. Based in New York City with campuses and sites in 14 additional major cities across the world, NYU embraces diversity among faculty, staff and students to ensure the highest caliber, most inclusive educational experience.
Programme de cours : ce que vous apprendrez dans ce cours
Week 1 - MOST is a different way of thinking
Week 1 - MOST is a different way of thinking
Week 2 - The preparation phase: Laying the foundation for successful optimization
Week 3 - Introduction to the factorial optimization trial
Week 4 - Some conceptual and technical aspects of the factorial experiment
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