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Presented by Linda M. Collins, PhD

Distinguished Professor, Department of Human Development and Family Studies and Statistics
Director, The Methodology Center
The Pennsylvania State University

Date: February 14, 2020

Time: 8:30 a.m. to 2:30 p.m.


8:15-8:30         Check in/Registration

8:30-11:30        Morning Session

11:30-12:00       Lunch (catered on site)

12:00-2:30       Afternoon Session

*Scheduled breaks at approximately 10:30am and 1:00pm.

Workshop Overview:

Development and evaluation of the majority of the multicomponent behavioral, biobehavioral, and biomedical interventions in use today has been carried out using the classical treatment package approach. This approach consists of identifying the components of the intervention and then evaluating the intervention as a package in a randomized controlled trial (RCT). The RCT is an excellent way to determine whether an intervention is effective, but it is less helpful in providing empirical information that can be used to optimize the intervention to achieve improved effectiveness, efficiency, economy and scalability.

In this workshop an innovative methodological framework, the multiphase optimization strategy (MOST), will be introduced as an alternative to the classical treatment package approach. MOST is based on ideas inspired by engineering methods, which stress both ongoing improvement of products and careful management of research and implementation resources.  A comprehensive strategy for intervention optimization, MOST includes three phases:  preparation; optimization, based on an optimization trial using a highly efficient experimental design; and evaluation, typically using an RCT. MOST can be used to build a new optimized intervention, optimize an existing intervention, or optimize intervention delivery. Using MOST it is possible to engineer an intervention to meet a specific criterion; for example, the objective might be to identify the intervention that achieves the best outcome obtainable for less than a specified implementation cost.

Ongoing intervention development studies using the MOST approach will be used as illustrative examples. A substantial amount of time will be devoted to the design of optimization trials, with an emphasis on the factorial design. Time will be reserved for open discussion of how the concepts presented can be applied in the research of attendees.

Registration and Venue Detail:

  • Class size is limited to 60 participants.
  • Registration will close when the workshop maximum is reached. A standby list will be maintained as needed.
  • Regenstrief Institute is an approved VA vendor.
  • Host location is at Regenstrief Institute, Inc., 1101 West 10th Street, Indianapolis, IN 46202, located on the campus of Indiana University-Purdue University Indianapolis and near downtown Indianapolis.
  • Pay parking is available for guests in the Wilson Street Garage at 811 Wilson Street, Indianapolis, adjacent to the Regenstrief building. A full-sized interactive campus map and directions are available at:
  • Regenstrief Institute and Health Services Research seek to make all attendees feel welcome at this event. If you have a disability and need an accommodation to participate in this program, please contact Lori Losee at (317) 274-9149 or prior to the event.

Dr. Collins’ visit to the IUPUI campus has been co-sponsored by the Indiana University Center for Health Services and Outcomes Research, the Indiana University Melvin and Bren Simon Cancer Center, and Regenstrief Institute, Inc.  If you have questions about this event please contact the Center for Health Services Research at (317) 274-9046.

Learning Objectives

  1. Understand the preparation, optimization, and evaluation phases of MOST.
  2. Understand the concept of an optimization trial.
  3. Review the differences between MOST and the classical approach to intervention development and evaluation.
  4. Discuss potential applications of MOST to develop efficient and immediately scalable interventions, and to optimize intervention delivery.
  5. Understand how to make decisions about what components make up the optimized intervention.