What are the features of the conceptual model needed for the Preparation Phase of MOST?
A good conceptual model should specify
- the determinants of and influences on the health behavior or outcome to be impacted by the behavioral intervention;
- all important mediators and moderators, including which intervention components, if any, are expected to interact with each other;
- what psychosocial and/or biological theories inform which parts of the model–in most cases there will be several theories that inform a conceptual model; and
- which intervention components are aimed at which mediators.
Sometimes the conceptual model is not a model of a health behavior per se, but a model of maintaining treatment fidelity, promoting adherence or compliance, or the like. The conceptual model is explained in more detail in Chapter 2 of Collins (2018). For an example, see Gwadz et al. (2017).
What is meant by “optimized”?
Collins (2018) defines intervention optimization as “the process of identifying an intervention that provides the best expected outcome obtainable within key constraints imposed by the need for efficiency, economy, and/or scalability.” Note that optimized does not mean best in an absolute or ideal sense. Instead, the optimized intervention is the best intervention that can actually be implemented.
So isn’t optimization just deciding what is “good enough”? How is this so different from the treatment package approach? Every clinical trial uses this “good enough” approach.
Simply saying “well, this is good enough” is not the same as optimization. In fact, the optimized product may not be good enough, and a product considered good enough, or even the ideal, may not be optimal.
Let’s take a straightforward hypothetical example from the field of product development and manufacturing. Suppose you were charged with building and optimizing a global positioning system (GPS). The ideal would be a GPS that can pinpoint your location. The way to come closest to this would be to spare no expense in building the GPS. However, suppose the optimization objective is to build an affordable GPS that costs $100 or less to manufacture. Note that the ideal does not meet this objective. The $100 constraint on manufacturing costs means you cannot choose the most precise and, therefore, most expensive components for your GPS. In this example, optimization means finding the combination of components that comes closest to the ideal without exceeding the $100 limit. Maybe that means going with all moderately-priced components; maybe it means one key component has to be on the expensive side and the others will have to be cheap. Suppose the best GPS you could manufacture for $100—that is, the optimized GPS—can identify locations only within a 400-foot range. This might not be “good enough” even though it has been optimized. Then the company might decide to change the optimization objective by changing the $100 limit and allowing, say, $150 in manufacturing costs. Or, you might be charged with developing cheaper and more effective components that potentially could be used to make a GPS that will be both optimized and “good enough.”
Gwadz, M.V., Collins, L.M., Cleland, C.M., Leonard, N.R., Wilton, L., Gandhi, M., Braithwaite, R.S., Perlman, D.C., Kutnick, A., & Ritchie, A.S. (2017). Using the multiphase optimization strategy (MOST) to optimize an HIV care continuum intervention for vulnerable populations: A study protocol. BMC Public Health, 17, 383.