Hello. I'm Linda Collins. I'm Kate Guastaferro. We've developed this online course titled: How to Apply the Multi-phase Optimization Strategy (MOST) in Your Intervention Development Research. In this video, we will offer a brief introduction to the course. We will explain what the course is about and who might want to take it. We'll also talk a bit about the readings for the course. Behavioral, biobehavioral, biomedical, educational, and social structural interventions play an important role in public health worldwide. These are interventions with the purpose of making life better by treating or preventing disease, enhancing mental or physical health, improving academic enjoyment and achievement, or in general, enhancing well-being. At least part of the strategy of these interventions involves helping individuals to make changes to their behavior or cognitions. For example, school-based drug abuse prevention programs help children see that drug use is not normative among their peers, and that in general, their peers disapprove of drug use. These programs also help children develop the behavioral skills needed to resist peer pressure to use drugs. Or, for example, interventions
31
00:01:12,380 --> 00:01:15,230
delivered to Child Protective
Service-involved parents increase parents' basic knowledge of child development and skills in parent-child interactions. These programs lead to a reduction in risk for future maltreatment. These are just two examples out of many possibilities. Other examples can be found in every area of education and public health worldwide. Intervention science is the science of evidence-based development of behavioral, biobehavioral, biomedical, educational, and social structural interventions. For its entire history to date, intervention science has relied primarily on one research paradigm. In this paradigm, which we will call the classical treatment package approach, the components making up the intervention are identified and usually pilot tested. The next step is then assembly of the components into a treatment package and evaluation. The evaluation is done by means of a randomized experiment, usually called a randomized control trial or RCT. We agree that a properly conducted RCT answers an important question, namely whether the treatment package has a statistically and clinically significant effect. However, we believe strongly that simply determining whether or not an intervention has an effect is not enough. Instead, we recommend optimizing the intervention before evaluating it in an RCT. By optimizing an intervention, we mean achieving the strategic balance of effectiveness against affordability, scalability, and efficiency. The result is interventions that eliminate inactive and unnecessary components, are practical to implement and offer good value. MOST is a framework for intervention optimization. As the title of the first week of this course says, MOST is a different way of thinking! It can be hard to get used to at first. But our experience has been that once someone understands this perspective, they never go back to thinking in terms of the classical treatment package approach. As more and more intervention scientists work within the MOST framework, the field will accumulate a coherent base of knowledge about what works and what doesn't, for whom, and under what circumstances. Moreover, taking this approach makes it much more feasible to make incremental and programmatic improvements in interventions over time, so that interventions keep getting better and better. There are five overall learning objectives for this course. They are: "Relate the MOST framework to the objectives of intervention research;" "Compare and contrast the classical treatment package approach and MOST;" "Complete the preparation phase of MOST;" "Design and conduct a rigorous and efficient factorial optimization trial in a field setting;" and "Complete the optimization phase of MOST and identify next steps." The first learning objective, "Relate the MOST framework to the objectives of intervention research," is addressed in Modules 1 and 4. In Module 1 you will learn about key concepts such as optimization and intervention EASE. You will learn the three phases of MOST, which are preparation, optimization, and evaluation. You will also learn the two fundamental principles of MOST, which are the resource management principle and the continual optimization principle, and how these relate to what you already know about intervention research. In Module 4, you will learn how to interpret the meaning of the effects that are estimated in a factorial optimization trial, namely, the main effect and interaction, and how these relate to the objectives of intervention research. The second learning objective, compare and contrast the classical treatment package approach and MOST, is addressed in Modules 1 and 3. In Module 1, you will learn how to summarize key differences in perspective between the classical treatment package approach and MOST. In Module 3, you will learn how to explain the critical differences between the RCT and the factorial optimization trial. The third course learning objective, "Complete the preparation phase of MOST," is addressed in Module 2. This module will teach you how to create a conceptual model using best practices, define the term "pilot study," and distinguish pilot studies from optimization trials, and specify an optimization objective to express what is meant by intervention EASE in a particular study. Quite a bit of attention in Modules 3, 4, and 5 is paid to the fourth course learning objective, "Design and conduct a rigorous and efficient factorial optimization trial in a field setting." In Module 3, you will learn how to explain the key characteristics of the factorial experiment; identify when a factorial experiment is a good choice for an optimization trial design; and explain when and why the factorial experiment is economical as compared to alternatives. In Module 4, you will learn how to discern whether the conclusion priority or decision priority perspective is appropriate; understand the basics of powering a factorial experiment; and apply the resource management principle, one of the fundamental principles of MOST, when there is a cluster structure in the data. Module 5 will show you how to implement a factorial optimization trial in a rigorous manner and follow best practices for responsible conduct of research when implementing a factorial optimization trial. The final course learning objective, "Complete the optimization phase of MOST and identify next steps," is addressed in Module 6. In this module, you will learn how to identify the optimized intervention based on the results of a factorial optimization trial and your optimization objective, then decide what your next steps will be after completion of the optimization phase of MOST. This course is aimed at those who identify as intervention scientists or are training to become intervention scientists. This includes those who work as part of an interdisciplinary team developing and evaluating interventions and those who consider themselves primarily implementation scientists. The material presented here is not highly technical, but it does require graduate-level training in statistics for the social and behavioral sciences, at least up through multiple regression. We designed this course to be cumulative. We strongly recommend starting with Module 1 and proceeding through the modules in order, without skipping any lessons or modules. When you're working on more advanced modules, you may find it helpful to go back and review what was covered in earlier modules. Of course, after you complete the course, you can review any of the course materials as often as you like. We also strongly recommend that as you are completing the course, you do all of the required reading. This book is the required textbook for this course. You can purchase a bound or PDF copy of this book from the publisher Springer. or it may be possible to obtain a PDF copy for free if you're affiliated with a university. You can check with your librarian to see whether that's possible. Make sure that you get the correct book. There is another book with a similar title and cover that was edited by Collins and Kugler containing a series of chapters on advanced topics. You might be interested in that book too. But for this course, you need the book that was written by Collins, with the title, Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). You may wish to read some or all of the articles and book chapters that are mentioned in the lessons. We've provided the complete citations for these at the end of each lesson. Kate and I hope you will enjoy this course and that after you complete it, you'll find yourself thinking differently about intervention science. We also hope you'll find MOST useful in your work. Intervention optimization is a rapidly evolving field, so watch for new scientific literature in this area, and also watch for additional Coursera courses on intervention optimization.
