The following guiding principles are integral to the IDEAS Impact Framework:
Precision involves having a clear understanding of what a program entails, what it targets, and what the ultimate goals are. For example, a program might target family routines with the ultimate goal of reducing child behavior problems. Investigating the relationship between targets and outcomes helps us move beyond the question “does it work?” to “how does it work?” Precision also involves clarity about the person- and place-based factors that determine who the program is most (or least) helpful for. Precision in program development and testing then enables both segmentation and modularity.
Members of the team working on Learning Through Play discuss the principle of segmentation and how it is helping to guide their approach.
Through segmentation, we can systematically generate that precise knowledge about who benefits most (and least) and in what contexts, and more closely match programs with the needs of specific subgroups and contexts. Segmentation specifies salient characteristics of the individuals involved in the program beyond the usual variables such as race, family income, parent’s education level, or whether a program is home- or center-based. These additional characteristics—which might include factors like a child’s attention skills, a parent’s mental health status, or a teacher’s knowledge of child development—allow us to clearly identify for whom a program works—and for whom it doesn’t.
Modularity is the degree to which the components of a program can be separated and re-combined. Modular programs can be implemented with ease in existing programs or service structures because teams can incorporate the specific components that make sense for their programs. This approach offers a practical and cost-effective pathway to targeted scaling. Understanding why different programs or their components are effective for different populations can help us identify a program’s “key ingredients,” which can then be incorporated, in suitable mixes, into broader service systems. This contrasts with the conventional approach, which involves implementing the full package of a program, without understanding the specific impacts of each component.
Members of the team working on Attachment Vitamins discuss the principle of fast-cycle iteration and how it has strengthened the program.
Fast-cycle iteration is a process for quickly incorporating what we’ve learned back into the design of the program. In contrast to more traditional randomized control trials, which involve high numbers of participants over several years, project teams using IDEAS Impact Framework fast-cycle iteration start with a series of low-cost, relatively small-scale pilot tests that enable them to establish feasibility and begin to explore the program’s theory of change. Each fast-cycle iteration, which can take place over weeks or a few months, is an opportunity to make refinements to the program based on what is and isn’t working, and to move toward higher levels of evidence at a faster pace.
Members of the team working on FIND discuss the principle of co-creation and how it has influenced the program.
Co-creation refers to bringing together different parties to produce a mutually valued outcome. The FOI approach to innovation brings together researchers, practitioners, and community members in order to develop, implement, test, and adapt ideas. This process increases the likelihood that the programs will meet communities’ unmet challenges, are relevant to real-world contexts, and can be scaled.
Members of the Bienestar en tu Embarazo (Wellness in Your Pregnancy) team from Mexico and the Fortalecendo Laços (Strengthening Bonds) team from Brazil discuss the importance of shared learning in their interventions.
The principle of shared learning is also critical in the IDEAS Impact Framework. The FOI network is a community of innovation, with opportunities for multidisciplinary learning across programs and sites. To help facilitate this cross-project learning, IDEAS Impact Framework-engaged projects use common measures and share de-identified data from each program trial with a centralized data repository, allowing for greater aggregation across multiple programs and contexts. Finally, learning from failure as well as success, and sharing this learning with a committed and multidisciplinary community, is an essential and valued part of the work.