Knowledge Neighborhoods: Building the Infrastructure for Evidence-Based Practice in Mental Health

A new analysis of research-practice partnerships by Lawrence Palinkas, Cherry Short, and Marleen Wong takes us beyond traditional notions of “translating” research findings to practice. Focusing on collaboration and mutual exchange, Palinkas and colleagues call into question traditional roles and how evidence is used and whether our field has outgrown its own metaphors regarding bridging the research practice gap.

Most current thinking about improving mental health practice assumes that evidence production is the responsibility of the researcher and that application of evidence is the responsibility of the service provider. This notion has shaped contemporary thinking about dissemination of evidence-based treatments, emphasizing the controlled application in service settings of procedures previously tested under rigorous experimental conditions.

My colleagues and I recently offered a perspective to contextualize this dissemination model within a larger framework of knowledge management. We suggest that the existing evidence-based treatment paradigm, and its implications for researchers and service providers, is but one of many strategies for using evidence to improve service outcomes for families and communities. Even if it is the very best strategy, we argue that there are nevertheless limitations, such as when evidence-based treatments sometimes do not achieve desired results, are not available, or are thrown off by unforeseen circumstances.

Knowledge flows in many directions, and the knowledge needed to prioritize therapeutic action in mental health comes from a variety of sources.

Knowledge flows in many directions, and the knowledge needed to prioritize therapeutic action in mental health comes from a variety of sources. Effective and efficient mental health systems of the future will need to balance knowledge from multiple sources, often gathered at different points in time. Useful evidence comes not only from research, but from mental health consumers (e.g., progress feedback), local aggregate findings (e.g., program evaluation, local standards, and preferences), and clinical theory (e.g., fundamental principles of biology, emotions, or behavior). These must be coordinated and prioritized, depending on the decision at hand and the current circumstances.

Should we continue to use an evidence-based protocol when faced with a poor response? Should we discontinue a service with local evidence of positive outcomes but no experimental research support? Should we adapt an established evidence-based treatment based on emerging experimental findings regarding mechanisms of change? Our collective endeavor involves weighing different sources of evidence in the service of prioritizing the most reliable path toward positive outcomes. So, the real question is whether we can take evidence that has been garnered by randomized trials, coordinate with evolving clinical theory, local practice, and evidence obtained today from an individual seeking help, and ultimately move forward with an idea for what to do next.

This may be possible, but not merely by crossing a bridge. Instead of thinking of research and practice as a point A and point B journey, we might instead think of traveling around a neighborhood. The best neighborhoods have the infrastructure to invite purposeful collaboration and interaction while maintaining comfort and practicality. Roads, homes, schools, and parks make up a system where residents connect. A neighborhood-like network of cooperation, rather than just a bridge from one point to another, would allow for purposeful collaboration in pursuit of positive outcomes, bringing together not only researchers and practitioners, but educators, policymakers, and consumers.

Instead of thinking of research and practice as a point A and point B journey, we might instead think of traveling around a neighborhood.

What might this neighborhood look like? Palinkas and colleagues outline three partnerships in which the researcher had significant involvement in implementation. But if we call into question the notion of bridge building, then should we also question the notion of researcher as bridge builder? At present, researchers are certainly among the most suitable candidates for this role, but perhaps this is an artifact of a pre-industrial state of behavioral health care. Consider that few of us today buy our food from farmers or our clothing from tailors—there is usually a third party service that allows massive scaling of these basic commodities. Of relevance to behavioral health, industry is replete with examples of appealing and efficient knowledge management structures, from online user reviews to searchable evidence repositories and wikis. Likewise, institutions of higher education have centuries of experience with credentialing, curricular management, skill development, and training. Bending these structures to support the aim of positive mental health functioning is a solvable and scalable task, but it may be the product of neither those who consume nor those who produce the knowledge that will travel through those structures.

A working example might be a provider referencing an evidence-based protocol developed and tested by researchers, but selecting a specific procedure using a third party meta-analytic tool that identifies one specific procedure as best indicated, adapting or adjusting that content for a planned clinical encounter using 1) feedback technology indicating current progress and trend as well as consistency with expected trends from the relevant literature, 2) patient preferences obtained through face-to-face or smartphone interview, and 3) web-delivered relevant theoretical developments that have outpaced treatment validation research (e.g., a novel finding on increasing client memory of a skill, but not yet validated in a full treatment context). This provider would then prepare for the procedure by viewing an online video sponsored by a local university. This example is not hypothetical—working prototypes have been implemented in a variety of settings, but simply have not become mainstream.

Possibilities are many, but the basic idea is that knowledge comes from multiple sources and may involve many entities that will need to coordinate according to common standards. The knowledge neighborhood is not a definitive metaphor. Instead, it is a means to suggest that it may be time to question the current knowledge architecture and ask ourselves whether all parties are actively engaged in finding solutions to the challenges we face. I look forward to the possibility that consumers, educators, practitioners, and researchers come together to build that neighborhood instead of just crossing bridges.



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