Part III
Implementation and Scale-Up of Effective Interventions
We have explored strong evidence about the effectiveness of many kinds of strategies for fostering healthy mental, emotional, and behavioral (MEB) development, and turn next to the question of why they have not yet brought greater improvement in outcomes (see Chapter 1). If intervention strategies are to achieve real benefits, not just for individual children and families but for communities and larger populations, they must be implemented well and at broad scales. The most effective strategies cannot achieve their intended benefits if they are not implemented with fidelity—delivered with careful attention to the intended model or design—and optimized to meet objectives for the environments in which they are implemented. Moreover, they must be of sufficient scale to reach intended populations.
Researchers and practitioners not just in fields that address MEB development but across the fields concerned with human services more broadly have been frustrated by the elusiveness of public health impact from demonstrably strong intervention strategies. A key concern in assessing progress has been whether strategies for which there is strong evidence of effectiveness were implemented well—indeed it has been difficult even to document the effectiveness with which child, family, school, and community programs have been broadly implemented (Bruns et al., 2016; Crosse et al., 2011; Moore, Bumbarger, and Cooper, 2013).
Increased attention to implementation has demonstrated that it is considerably more complicated than had been clearly recognized. Effective implementation is as important for simple activities or practices—such as handwashing in health care settings to reduce infection—as it is for the most complex programs and policies. The challenges to implementation range from practical, local ones, such as mobilizing the people and resources needed and demonstrating impacts, to the broadest challenges of building infrastructure and resources to support effective prevention and intervention approaches on a nationwide scale. While fidelity continues to be a cornerstone of quality implementation, a much more comprehensive set of implementation outcomes has
been articulated and is now being used in research and practice to determine the integrity with which a program or practice is being implemented (Proctor et al., 2011).
The authors of the 2009 National Research Council and Institute of Medicine report recognized the importance of implementation and discussed alternative ways of adapting programs for diverse settings and engaging communities in decision making about program implementation. The 2009 report also describes challenges to effective implementation. It touches on the difficulties inherent in different types of settings, as well as broader challenges, including funding the intervention program, integrating intervention objectives with other priorities, ensuring that training and capacity to deliver the intervention are adequate, and providing for monitoring of the program delivery and outcomes. The report presents policy strategies for promoting MEB health and preventing disorder and emphasizes the need for research on implementation and dissemination.
The 2009 report takes note of the emerging field of implementation science and calls specifically for research to support wide-scale implementation that addresses the need for sensitivity to context, as well as the capacity to sustain the effort. The field of implementation science has matured since then. Researchers have expanded understanding of many of these issues, and their contributions are increasingly appreciated in health, education, child welfare, juvenile justice, and other fields (Bauer et al., 2015; Lobb and Colditz, 2013). This work has continued to build evidence about the connections between the integrity of implementation and outcomes. Researchers have refined the definition of implementation as a complex process for ensuring not only that the elements essential to making a program work are faithfully executed but also that an iterative process is used to optimize the program so it can yield its intended benefits as it is scaled up.
Implementation and scale-up are increasingly understood as context-dependent, tailored processes that rely on core sets of partners, strategies, and capacities rather than generalized processes easily overlaid across varied types of settings. Researchers have worked on adaptive program design methods to clearly identify core intervention components and methods for adapting programs in the field based on cultural and community values and processes. Taxonomies of implementation strategies have been developed and are now being used in research and practice to more clearly articulate and test ways of addressing barriers and promoting facilitators of implementation. And the partnerships and system capacities needed to support and sustain implementation and scale-up outcomes have become better articulated and researched, moving well past the necessary—but likely not sufficient—elements of training, materials, funding, and evaluation.1
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1 Norton and colleagues (2017) describe the growth of the field over the last decade, citing increases in journals addressing the subject, scientific conferences and meetings, training resources, measurement instruments and repositories, academic programs and courses, and professional societies. The number of dissemination and implementation
In Part III, we set advances that have emerged since the 2009 report in the context of what was already known to provide a clear overview of the current state of knowledge about this complex process. Chapter 8 offers an overview of some of the foundations on which effective implementation rests: identification of core components, adaptation, and careful strategies for implementation. In Chapter 9, we explore the need for effective partnerships and the capacity to support faithful implementation.
REFERENCES
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theories and frameworks has also accelerated, with a recent review counting more than 61 dissemination and/or implementation models (Tabak et al., 2012).
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