The Adaptome

Abstract

In the past few decades, prevention scientists have developed and tested a range of interventions with demonstrated benefits on child and adolescent cognitive, affective, and behavioral health. These evidence-based interventions offer promise of population-level benefit if accompanied by findings of implementation science to facilitate adoption, widespread implementation, and sustainment. Though there have been notable examples of successful efforts to scale-up interventions, more work is needed to optimize benefit. Although the traditional pathway from intervention development and testing to implementation has served the research community well—allowing for a systematic advance of evidence-based interventions that appear ready for implementation—progress has been limited by maintaining the hypothesis that evidence generation must be complete prior to implementation. This sets up the challenging dichotomy between fidelity and adaptation, and limits the science of adaptation to findings from randomized trials of adapted interventions. The field can do better. This paper argues for the development of strategies to advance the science of adaptation in the context of implementation that would more comprehensively describe the needed fit between interventions and their settings, and embrace opportunities for ongoing learning about optimal intervention delivery over time. Efforts to build the resulting adaptome (pronounced “adapt-ohm”) will include the construction of a common data platform to house systematically captured information about variations in delivery of evidence-based interventions across multiple populations and contexts, and provide feedback to intervention developers, as well as the implementation research and practice communities. Finally, the article identifies next steps to jumpstart adaptome data platform development.

Organizational theory for dissemination and implementation research

“…A common elements approach to implementation would potentially be most successful: implementing common techniques across EBI models would allow clinicians greater flexibility to meet diverse client needs and organizations more flexibility in training their workers [69, 70]. To optimize intervention delivery, scholars have advocated for efforts to systematically adapt interventions to the varied and unique contexts in which they are disseminated [71]. Evidence regarding successful adaptation of promising interventions to a variety of settings continues to accumulate.…”

Mapping the growing discipline of dissemination and implementation science in health

“…First, it provides data to inform strategic planning to advance specific areas of inquiry (e.g., adaption of evidence-based practices[16]; de-implementation of ineffective health practices and services[17, 18]). Second, it allows individuals who are new to the discipline to identify and understand its origins, including, for example, seminal papers, meetings, and thought leaders.…”

Therapist report of adaptations to delivery of evidence-based practices within a system-driven reform of publicly funded children’s mental health services.

“…As evidence-based practices (EBPs) spread across diverse community practice settings, it is essential to understand how they are modified by end users (Chambers & Norton, 2016). Indeed, Rogers’ (1962, 2003) seminal Diffusion of Innovation theory posits that innovations are inevitably adapted, with the extent and types of modifications depending on characteristics of both the innovation and the adopter.…”

“…Indeed, Rogers’ (1962, 2003) seminal Diffusion of Innovation theory posits that innovations are inevitably adapted, with the extent and types of modifications depending on characteristics of both the innovation and the adopter. Implementatation outcomes may be shaped by adaptations of EBPs that serve to align the practice with the local needs of providers (Chambers & Norton, 2016). Innovations with good potential for reinvention may be more appealing to adopters, ultimately resulting in greater uptake and penetration (Greenhalgh, Robert, Macfarlane, Bate, & Kyriakidou, 2004).…”