intensity for the sustained achievement of desirable program goals and population outcomes. This understudied area has been identified as one of the most significant translational research problems. Adding to this challenge is uncertainty regarding the extent to which intervention adaptation and evolution are necessary to address the needs of populations that differ from those in which interventions were originally tested or implemented. This review critically examines and discusses conceptual and methodological issues in studying sustainability, summarizes the multilevel factors that have been found to influence the sustainability of interventions in a range of public health and health care settings, and highlights key areas for future research. AbstractThere is strong interest in implementation science to address the gap between research and practice in public health. Research on the sustainability of evidence-based interventions has been growing rapidly. Sustainability has been defined as the continued use of program components at sufficient (17,97,109). Although numerous evidence-based public health interventions and clinical preventive strategies and treatments are available, it can be challenging to implement and sustain them outside of controlled settings, particularly if they were originally tested in narrow populations or unrepresentative circumstances (49). As a rapidly growing field, implementation science has focused on understanding factors and strategies that influence the initial adoption and integration of evidence-based interventions (EBIs) in real-world settings (103). Whereas significant advancements have been made in understanding the adoption and implementation of EBIs across a range of community and health care settings, less is known about their sustainability. Recently, experts have prioritized sustainability as an understudied area (45), identifying it as "one of the most significant translational research problems of our time" (103, p. 2) and as a persistent challenge across a range of settings and service delivery sectors, and across health behaviors and outcomes.Maximizing the public health impact of EBIs will require investing in sustainability research. This research will enable us to better understand what factors and processes influence the sustainability of interventions and how to plan proactively for the continuation of EBIs. Moreover, there has been growing consideration of the policy and ethical implications of developing effective health programs without investing in sustainability (118). Researchers, health leaders, advocates, policy makers, practitioners, and funders alike have concerns about the long-term impact and value of their investment in discontinued interventions. In addition to lost investments, time, and resources, there are other reasons for which advancing our understanding of the sustainability of EBIs has value (99, 122). Maintaining effective programs and practices is critical for achieving health benefits, particularly if there is a latency period betwee...

When evidence-based programs (EBPs) are scaled up in natural, or non-research, settings, adaptations are commonly made. Given the fidelity-versus-adaptation debate, theoretical rationales have been provided for the pros and cons of adaptations. Yet the basis of this debate is theoretical; thus, empirical evidence is needed to understand the types of adaptations made in natural settings. In the present study, we introduce a taxonomy for understanding adaptations. This taxonomy addresses several aspects of adaptations made to programs including the fit (philosophical or logistical), timing (proactive or reactive), and valence, or the degree to which the adaptations align with the program's goals and theory, (positive, negative, or neutral). Self-reported qualitative data from communities delivering one of ten state-funded EBPs were coded based on the taxonomy constructs; additionally, quantitative data were used to examine the types and reasons for making adaptations under natural conditions. Forty-four percent of respondents reported making adaptations. Adaptations to the procedures, dosage, and content were cited most often. Lack of time, limited resources, and difficulty retaining participants were listed as the most common reasons for making adaptations. Most adaptations were made reactively, as a result of issues of logistical fit, and were not aligned with, or deviated from, the program's goals and theory.

In this article, we consider the broad applicability of latent class analysis (LCA) and related approaches to advance research on child development. First, we describe the role of person-centered methods such as LCA in developmental research, and review prior applications of LCA to the study of development and related areas of research. Then we present practical considerations when applying LCA in developmental research, including model selection and statistical power. Finally, we introduce several recent methodological innovations in LCA, including causal inference in LCA, predicting a distal outcome from latent class membership, and latent class moderation (in which LCA quantifies multidimensional moderators of effects in observational and experimental studies), and we discuss their potential to advance developmental science. We conclude with suggestions for ongoing developmental research using LCA.

Over the past four decades, significant strides have been made in the science of preventing youth problem behaviors. Subsequently, policymakers and funders have begun to insist on the use of evidence-based programs (EBPs) as a requirement for funding. However, unless practitioners are able to sustain these programs beyond initial seed funding, they are unlikely to achieve their ultimate goal of broad public health impact. Despite its obvious importance, sustainability has received relatively little attention in prevention science until recently. Moreover, there have been few opportunities to study the correlates of sustainability in large-scale, multi-year initiatives involving multiple programs. The present study examined rates of sustainment of a wide range of proven-effective prevention and intervention programs; identified factors related to organizational support and readiness, program and implementer characteristics, and sustainability planning that distinguished sustained programs; and examined variability in these associations across classroom-based, community/mentoring, family-focused prevention, and family treatment program types within the context of a state-wide EBP dissemination initiative in Pennsylvania over 4 years. The majority of EBPs sustained functioning 2 years or more beyond their initial funding. In general, sustained programs reported greater community coalition functioning, communication to key stakeholders, knowledge of the program's logical model, communication with the trainer or program developer, and sustainability planning. In addition to these universal correlates, important program-specific correlates emerged as well. Implications for the technical assistance and support necessary to promote the sustainability of EBPs in nonresearch contexts are also discussed.

A number of programs, policies, and practices have been tested using rigorous scientific methods and shown to prevent behavioral health problems (Catalano et al., Lancet 379:1653–1664, 2012; National Research Council and Institute of Medicine, 2009). Yet these evidence-based interventions (EBIs) are not widely used in public systems, and they have limited reach (Glasgow et al., American Journal of Public Health 102:1274–1281, 2012; National Research Council and Institute of Medicine 2009; Prinz and Sanders, Clinical Psychology Review 27:739–749, 2007). To address this challenge and improve public health and well-being at a population level, the Society for Prevention Research (SPR) formed the Mapping Advances in Prevention Science (MAPS) IV Translation Research Task Force, which considered ways to scale up EBIs in five public systems: behavioral health, child welfare, education, juvenile justice, and public health. After reviewing other efforts to scale up EBIs in public systems, a common set of factors were identified as affecting scale-up in all five systems. The most important factor was the degree to which these systems enacted public policies (i.e., statutes, regulations, and guidance) requiring or recommending EBIs and provided public funds for EBIs. Across systems, other facilitators of scale-up were creating EBIs that are ready for scale-up, public awareness of and support for EBIs, community engagement and capacity to implement EBIs, leadership support for EBIs, a skilled workforce capable of delivering EBIs, and data monitoring and evaluation capacity. It was concluded that the following actions are needed to significantly increase EBI scale-up in public systems: (1) provide more public policies and funding to support the creation, testing, and scaling up of EBIs; (2) develop and evaluate specific frameworks that address systems level barriers impeding EBI scale-up; and (3) promote public support for EBIs, community capacity to implement EBIs at scale, and partnerships between community stakeholders, policy makers, practitioners, and scientists within and across systems.

Although program adaptation is a reality in community-based implementations of evidence-based programs, much of the discussion about adaptation remains theoretical. The primary aim of this study was to replicate two coding systems to examine adaptations in large-scale, community-based disseminations of the Strengthening Families Program for Parents and Youth 10-14, a family-based substance use prevention program. Our second aim was to explore intersections between various dimensions of facilitator-reported adaptations from these two coding systems. Our results indicate that only a few types of adaptations and a few reasons accounted for a majority (over 70 %) of all reported adaptations. We also found that most adaptations were logistical, reactive, and not aligned with program's goals. In many ways, our findings replicate those of the original studies, suggesting the two coding systems are robust even when applied to self-reported data collected from community-based implementations. Our findings on the associations between adaptation dimensions can inform future studies assessing the relationship between adaptations and program outcomes. Studies of local adaptations, like the present one, should help researchers, program developers, and policymakers better understand the issues faced by implementers and guide efforts related to program development, transferability, and sustainability.

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