Overview of Study Designs in Implementation Science

Implementation science seeks to improve the adoption, adaptation, delivery and sustainment of evidence-based interventions in healthcare, and central to this goal is understanding how interventions are delivered effectively in the context of the 7 P’s (see figure, right). Research designed to evaluate the impact of these contexts takes many forms, and design selection is critical to capturing data in a manner that appropriately addresses your research question or questions.

Implementation research largely attends to external validity, whereas most randomized efficacy and effectiveness research designs emphasize internal validity. Given these differing focal points, a debate exists in the field as to the role of randomized design in implementation research and the relative merit of quantitative, qualitative, and mixed methods designs.

The 7 P's: Programs, Practices, Principles, Procedures, Products, Pills, Policies

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To learn more about which study designs are used in implementation research and why, please see below. In addition to two helpful overview articles about research design in implementation research, the National Cancer Institute’s archived Fireside Chat on study designs is a useful primer.

Selected Study Designs Used in Implementation Science

Randomized Control Trials

Definition: A type of experimental clinical study where participants are randomly selected into either the intervention or control group and then followed over time.

Stepped-Wedge Design

Definition: A randomized cross-over design where different clusters cross into the intervention condition at different points in time, all clusters receive the intervention, and the intervention state continues in a given cluster once begun.

Examples of Use


Effectiveness-Implementation Hybrid Design

Definition: A design that focuses both on assessing clinical effectiveness and on implementation.

Curran et al (2012) proposed three types of effectiveness-implementation hybrid designs:

  1. Testing effects of a clinical intervention on relevant outcomes while observing and gathering information on implementation
  2. Dual testing of clinical and implementation interventions/strategies
  3. Testing of an implementation strategy while observing and gathering information on the clinical intervention's impact on relevant outcomes

Webinar: “Hybrid Designs” Combining Elements of Clinical Effectiveness and Implementation Research


Examples of Use

Using PRECIS-2

In 2009, Thorpe and colleagues published A PRagmatic–Explanatory Continuum Indicator Summary (PRECIS): A tool to help trial designers (CMAJ, 2009) to help researchers ensure that decisions made about trial design are aligned with the trial's stated purpose. This tool was refined in 2013 by Loudon and colleagues in PRECIS-2: A tool to improve the applicability of randomised controlled trials (Trials, 2013).

PRECIS-2 organizes the nine elements for consideration into a wheel, consisting of:

  • Eligibility criteria
  • Setting
  • Organization
  • Flexibility of delivery
  • Flexibility of adherence
  • Follow up
  • Primary outcome
  • Primary analysis

To access the PRECIS-2 tool and to learn more about it, please visit PRECIS-2.org.

Intervention Optimization

Multiphase Optimization Strategy (MOST)

Definition: A strategy for building, optimizing, and evaluating interventions using a three-phase method to identify active intervention components and which levels of each component lead to optimal outcomes.


Examples of Use

Mixed Methods

Definition: The combination of at least one numerical (quantitative) research method and at least one non-numerical (qualitative) research method into a single study design.

Webinar: Advanced Topics for Implementation Science Research: Mixed Methods in Implementation Science

Quasi-Experimental Designs

Definition: Used to estimate whether an intervention had causal impact on the target population without the use of random assignment.

Regression Discontinuity

Definition: A quasi-experimental design using pretest-posttest examination of causal effects of interventions, where a threshold determines which recipients receive the intervention. This allows for the estimation of average treatment effect when randomization is not feasible.


Examples of Use

Regression Point Displacement

Definition: A pretest-posttest quasi-experimental design where data is collected at the group level and typically involves one treatment group and more than one control group.