A fifth type of control condition is called parametric/dose finding. This type of control would typically be used early in the development of a new treatment. The goal here is to determine the optimal “dose” or format of treatment. Different forms of intervention that vary on factors such as number, length, or duration of sessions, the use of individual versus group sessions, or variations in the treatment setting comprise the conditions to which individuals are randomly assigned (West & Spring, 2007). Similar to a parametric/dose finding study, in the additive/constructive comparison condition, different randomized groups receive different versions of the treatment (West & Spring, 2007). This can be characterized as a “bottom-up” approach. Those in both the experimental and comparison conditions receive the same active intervention, but those in the experimental condition also receive an additional treatment component that is hypothesized to add efficacy. Investigators can use this type of control condition in the early phases of treatment development or after treatment is established as evidence-based to see if its efficacy can be improved even further. Alternatively, a “top-down” approach called treatment dismantling, also known as “component analysis,” may be used. This approach uses a between-groups design where investigators compare individuals randomized to receive the full efficacious intervention to those randomized to receive a different form of that intervention, minus one or more parts (Lindquist et al., 2007; West & Spring, 2007). Usually, the treatment dismantling approach is used later in treatment development after the intervention’s efficacy is well established. The goal is to develop more efficient and potentially more effective treatments by determining which components of the intervention are necessary and sufficient for maximum clinical change and which may be unnecessary. It essentially represents a “fine- tuning” of the intervention and is important with respect to treatment implementation. As West and Spring (2007, p. 17) state, “The aim from a public health perspective is often to find a low-cost, minimally intensive intervention that improves outcomes for a small percent of the population, which equates in absolute numbers to a large number of people being helped.”

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