BackgroundDespite growth in implementation research, limited scientific attention has focused on understanding and improving sustainability of health interventions. Models of sustainability have been evolving to reflect challenges in the fit between intervention and context.DiscussionWe examine the development of concepts of sustainability, and respond to two frequent assumptions —'voltage drop,’ whereby interventions are expected to yield lower benefits as they move from efficacy to effectiveness to implementation and sustainability, and 'program drift,’ whereby deviation from manualized protocols is assumed to decrease benefit. We posit that these assumptions limit opportunities to improve care, and instead argue for understanding the changing context of healthcare to continuously refine and improve interventions as they are sustained. Sustainability has evolved from being considered as the endgame of a translational research process to a suggested 'adaptation phase’ that integrates and institutionalizes interventions within local organizational and cultural contexts. These recent approaches locate sustainability in the implementation phase of knowledge transfer, but still do not address intervention improvement as a central theme. We propose a Dynamic Sustainability Framework that involves: continued learning and problem solving, ongoing adaptation of interventions with a primary focus on fit between interventions and multi-level contexts, and expectations for ongoing improvement as opposed to diminishing outcomes over time.SummaryA Dynamic Sustainability Framework provides a foundation for research, policy and practice that supports development and testing of falsifiable hypotheses and continued learning to advance the implementation, transportability and impact of health services research.

One of the most critical issues in mental health services research is the gap between what is known about effective treatment and what is provided to consumers in routine care. Concerted efforts are required to advance implementation science and produce skilled implementation researchers. This paper seeks to advance implementation science in mental health services by over viewing the emergence of implementation as an issue for research, by addressing key issues of language and conceptualization, by presenting a heuristic skeleton model for the study of implementation processes, and by identifying the implications for research and training in this emerging field.

Context Theories and frameworks (hereafter called models) enhance dissemination and implementation (D&I) research by making the spread of evidence-based interventions more likely. This work organizes and synthesizes these models by: (1) developing an inventory of models used in D&I research; (2) synthesizing this information; and (3) providing guidance on how to select a model to inform study design and execution. Evidence acquisition This review began with commonly cited models and model developers and used snowball sampling to collect models developed in any year from journal articles, presentations, and books. All models were analyzed and categorized in 2011 based on three author-defined variables: construct flexibility, focus on dissemination and/or implementation activities (D/I), and the socio-ecological framework (SEF) level. Five-point scales were used to rate construct flexibility from broad to operational and D/I activities from dissemination-focused to implementation-focused. All SEF levels (system, community, organization, and individual) applicable to a model were also extracted. Models that addressed policy activities were noted. Evidence synthesis Sixty-one models were included in this review. Each of the five categories in the construct flexibility and D/I scales had/contained at least four models. Models were distributed across all levels of the SEF; the fewest models (n=8) addressed policy activities. To assist researchers in selecting and utilizing a model throughout the research process, the authors present and explain examples of how models have been used. Conclusions These findings may enable researchers to better identify and select models to inform their D&I work.

To address the vast gap between current knowledge and practice in the area of dissemination and implementation research, we address terminology, provide examples of successful applications of this research, discuss key sources of support, and highlight directions and opportunities for future advances. There is a need for research testing approaches to scaling up and sustaining effective interventions, and we propose that further advances in the field will be achieved by focusing dissemination and implementation research on 5 core values: rigor and relevance, efficiency, collaboration, improved capacity, and cumulative knowledge.