Table 1.

Design types, definitions, uses, and examples from implementation science

Design types	Definitions	Uses	Examples from implementation science
Experimental design
Between-site design	This design compares processes and output among sites having different exposures	Allows investigators to compare processes and output among sites that have different exposures	Ayieko et al. [13] Finch et al. [14] Kilbourne et al. [15]
Within- and between-site design	The comparisons can be made with crossover designs where sites begin in one implementation condition and move to another	Receiving the new implementation strategy, or when it is unethical to withhold a new implementation strategy throughout the study	Smith and Hasan [16] Fuller et al. [17]
Quasi-experimental design
Within-site design	This design examines changes over time within one or more sites exposed to the same dissemination or implementation strategy	These single-site or single-unit (practitioner, clinical team, healthcare system, and community) designs are most commonly compared to their own prior performance	Smith et al. [18] Smith et al. [19] Taljaard et al. [20] Yelland et al. [21]
Observational
Observational (descriptive)	Describes outcomes of interest and their antecedents in their natural context	Useful for evaluating the real-world applicability of evidence	Harrison et al. [22] Salanitro et al. [23]
Other designs/methods
Configurational comparative methods	Combine within-case analysis and logic-based cross-case analysis to identify determinants of outcomes such as implementation	Useful for identifying multiple possible combinations of intervention components and implementation and context characteristics that interact to produce outcomes	Kahwati et al. [24] Breuer et al. [25]
Simulation studies	A method for simulating the behavior of complex systems by describing the entities of a system and the behavioral rules that guide their interactions	Offer a solution for understanding the drivers of implementation and the potential effects of implementation strategies	Zimmerman et al. [26] Jenness et al. [27]
Hybrid Type 1	Tests a clinical intervention while gathering information on its delivery and/or on its potential for implementation in a real-world situation, with primary emphasis on assessing intervention effectiveness	Offers an ideal opportunity to explore implementation to plan for future implementation	Lane-Fall et al. [28] Ma et al. [29]
Hybrid Type 2	Simultaneously tests a clinical intervention and an implementation intervention/strategy	Able to assess intervention effectiveness and feasibility and/or potential impact of an implementation strategy receive equal emphasis	Garner et al. [30] Smith et al. [31]
Hybrid Type 3	Primarily tests an implementation strategy while secondarily collecting data on the clinical intervention and related outcomes	When researchers aim to proceed with implementation studies without completion of the full or at times even a modest portfolio of effectiveness studies beforehand	Bauer et al. [32] Kilbourne et al. [33]