Overview of MOST

What is the multiphase optimization strategy (MOST)?

MOST is a comprehensive, principled, engineering-inspired framework for optimizing and evaluating multicomponent behavioral and biobehavioral interventions. MOST includes a randomized controlled trial (RCT) for intervention evaluation, but unlike the standard approach to intervention development, also includes other phases of research before the RCT. These phases of research are aimed at intervention optimization using criteria selected by the scientist. The goal may be to develop a cost-effective intervention, an intervention that achieves a specified level of effectiveness, the briefest intervention that achieves a minimum level of effectiveness, or any other reasonable and explicitly operationalized goal. The MOST framework relies heavily on resource management by strategic use of highly efficient experimental designs. MOST is designed to be practical, and holds out the possibility of achieving more rapid long-run improvement of interventions without requiring a dramatic increase in intervention research resources. (See preface and Chapter 1 of Collins, 2018.)

Where can I read more about MOST?

View the MOST recommended reading list.

What qualifies as a “multicomponent behavioral intervention”?

A multicomponent behavioral intervention is any multicomponent intervention in which at least one of the components is behavioral. In other words, an intervention that combines behavioral and pharmaceutical components would be considered behavioral according to this definition.

What is an intervention component?

A multicomponent behavioral intervention is any multicomponent intervention with more than one component, in which at least one of the components is behavioral. Here the term behavior is broadly defined to include attitudes, cognitions, and skills.  If there is at least one medical component, such as a drug, surgery, or other medical treatment in addition to any behavioral components, the intervention is considered biobehavioral. (See Chapter 1 of Collins (2018).)

An intervention scientist conducts MOST because he or she needs to make decisions about what to include in an intervention. If you are asking yourself “Should I include X?” then X can probably be considered a component of the intervention.

As discussed in Chaper 1 in Collins (2018), an intervention component can impact efficacy, effectiveness, and/or cost-effectiveness. To contrast some very different takes on intervention components, read the articles in the Implementations of MOST section of the recommended reading list.

Why is some of the terminology used on this web site different from the terminology used in the articles in the recommended reading list?

The MOST framework has been refined to make it more consistent with the goals and objectives of intervention science, as opposed to engineering. Beginning in about 2014, articles reflect this change. (See preface of Collins (2018).)

What are the phases of MOST?

Figure 1 is a flow chart depicting the three phases of MOST: preparation, optimization, and evaluation. MOST is a framework, not an off-the-shelf procedure, so the details can vary somewhat from study to study. This means that a variation on this flow chart may do a better job of describing any particular application of MOST.

Overview of MOST. 1. Preparation Phase - Purpose: Lay groundwork for optimization. Activities: a. Derive/revise conceptual model. b. Identify set of candidate components. c. Conduct pilot tests. d. Identify optimization criterion. 2. Optimization – Purpose: Build optimized intervention. Activities: a. conduct optimization trial(s). i. Factorial experiment ii. Fractional factorial experiment iii. SMART iv. Micro-randomized trial v. System identification vi. Other b. Identify intervention that meets optimization criteria 3. Optimized intervention expected to be sufficiently effective? Yes = continue to Evaluation. No = return to Preparation (due to the Resource Management Principle.” 4. Evaluation Phase – Purpose: Confirm effectiveness of optimized intervention. Activity: Random controlled trial

Figure 1 is drawn from page 24 of
Collins, L. M. (2018). Optimization of behavioral, biobehavioral, and biomedical interventions: the multiphase optimization strategy (MOST). Springer.

The preparation phase

The purpose of the preparation phase is to lay the groundwork for optimization of the intervention. Information from sources such as behavioral theory, scientific literature, and secondary analyses of existing data is used to form the basis of a theoretical model. This model is critical for guiding decisions in MOST, in particular, the selection of which intervention components to examine. Any pilot testing of intervention components (highly recommended) is done in this phase.

An essential part of the preparation phase is identifying and operationalizing a clear optimization criterion. This is a definition of the end product to be achieved by optimizing the intervention. One straightforward optimization criterion is simply “no inactive components.” Constraints such as limits on cost, time, and participant logistical or cognitive burden can be incorporated into the optimization criterion, but they must be explicitly identified and operationalized. For example, a project funded by the National Institute of Diabetes and Digestive and Kidney Diseases(Principal Investigators are B. Spring and L. Collins) is using MOST to develop the most effective weight reduction intervention that can be implemented for $500 per person or less. (For more about the preparation phase see Chapters 1 and 2 in Collins, 2018.)

The optimization phase

As the name implies, in this phase the investigator optimizes the intervention. This involves selecting the components and component levels that make up the intervention that meets the optimization criterion. It is necessary to gather empirical information to do this. The approach depends on what information is required. Very often estimates of the individual and combined effectiveness of a set of intervention components are required for optimization. This information is typically gathered by means of an efficient randomized experiment called an optimization trail. include the factorial experiment; fractional factorial experiment; sequential, multiple assignment, randomized trial (SMART); and micro-randomized trial (MRT). Sometimes a system identification experiment is used (Chapter 8 in Collins, 2018). The results from this experiment form the basis for making decisions about component selection and formation of the optimized intervention (Chapter 7 in Collins, 2018).

At the end of the optimization phase, the investigator has selected the intervention components and component levels that make up the optimized intervention. Figure 1, above, shows a diamond immediately after the optimization phase, indicating that a decision is required. At this point the investigator has a rough sense of the likely overall effectiveness of the optimized intervention. If, based on the effect size estimates obtained in the optimization trial, it appears that the optimized intervention will have an effect that is sufficiently large to justify evaluating it with an RCT, it would make sense to proceed to the evaluation phase. On the other hand, the results of the component selection experiment may indicate that the optimized intervention is likely to have a very small effect. For example, the optimization criterion may call for an intervention comprised of only active components, and perhaps the experiment indicates that there is only one such component. In this case, it may not make sense to proceed to the evaluation phase. As Figure 1 indicates, it may be advisable to return to the preparation phase and reconsider the theoretical model, pilot test some new intervention components, and so on.

The evaluation phase

The evaluation phase consists of a standard RCT comparing the optimized intervention to a suitable control or comparison condition. As Figure 1 shows, there is another decision point immediately after the evaluation phase. If the RCT indicates that the optimized intervention is not effective, then it is necessary to return to the preparation phase and reconsider the theoretical model or the approach to intervention. If the RCT indicates that the optimized intervention is effective, implementation can begin.


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Read about establishing a conceptual model.