Table 4 OPTICC-endorsed designs for efficiently testing and refining strategies for optimizing EBI implementation

Factorial

Factorial designs are best for optimizing complex strategies [56, 57] because they efficiently screen multiple components for an effect on target outcomes. Each component is a “factor” that can take several “levels” (e.g., yes vs. no; delivery source). Participants are randomized to cells corresponding to different combinations of levels of each factor allowing for analysis of main effects and interactions with fewer participants compared to RCTs.

MRTs

Microrandomized trials (MRTs) evaluate strategy components delivered repeatedly (e.g., automated reminders about assessments). Each time (“decision point”) that a component can be delivered (e.g., patient visit), provision or non-provision of the component is randomized, allowing multiple components to be randomized concurrently. MRTs are a highly efficient design that takes advantage of within-subject and between-subject comparisons to estimate marginal main effects, changes in component effect over time, and moderating effects.

SMARTs

Sequential Multiple Assignment Randomized Trials (SMARTs) optimize adaptive strategies [58, 59] and help researchers determine decision rules for delivering a sequence of strategies that satisfy a set of optimization criteria, usually effectiveness and cost. Participants are initially randomized to two strategies that differ in intensity or cost and at predetermined times, non-responders are re-randomized to another set of strategy options; this can occur multiple times. SMARTs are highly efficient because analyses can use different sample subsets to answer different research questions (e.g., differences between strategies and the optimal way to support non-responders).

SCEDs

Single-Case Experimental Designs (SCEDs) gather evidence about strategy effects by observing changes in outcomes of interest for each participant (or unit, e.g., clinic). SCEDs are inherently within-subject designs with participants acting as their own controls, achieved through sequencing strategy exposures and comparing outcomes for periods when a participant was exposed to those when no strategy was provided. SCED designs include A-B-A-B and multiple baseline approaches. SCEDs require as few as six participants to provide information about effects, making it highly efficient with the low participant requirement making SCEDs promising for preliminary implementation studies in a single clinic [60, 61].