Increased focus on prevention presents health promoters with new opportunities and challenges. In this context, the study of factors influencing policy-maker decisions to scale up health promotion interventions from small projects or controlled trials to wider state, national or international roll-out is increasingly important. This study aimed to: (i) examine the perspectives of senior researchers and policy-makers regarding concepts of 'scaling up' and 'scalability'; (ii) generate an agreed definition of 'scalability' and (iii) identify intervention and research design factors perceived to increase the potential for interventions to be implemented on a more widespread basis or 'scaled up'. A two-stage Delphi process with an expert panel of senior Australian public health intervention researchers (n = 7) and policy-makers (n = 7) and a review of relevant literature were conducted. Through this process 'scalability' was defined as: the ability of a health intervention shown to be efficacious on a small scale and or under controlled conditions to be expanded under real world conditions to reach a greater proportion of the eligible population, while retaining effectiveness. Results showed that in health promotion research insufficient attention is given to issues of effectiveness, reach and adoption; human, technical and organizational resources; costs; intervention delivery; contextual factors and appropriate evaluation approaches. If these issues were addressed in the funding, design and reporting of intervention research, it would advance the quality and usability of research for policy-makers and by doing so improve uptake and expansion of promising programs into practice.

BackgroundTo maximise the impact of public health research, research interventions found to be effective in improving health need to be scaled up and delivered on a population-wide basis. Theoretical frameworks and approaches are useful for describing and understanding how effective interventions are scaled up from small trials into broader policy and practice and can be used as a tool to facilitate effective scale-up. The purpose of this literature review was to synthesise evidence on scaling up public health interventions into population-wide policy and practice, with a focus on the defining and describing frameworks, processes and methods of scaling up public health initiatives.MethodsThe review involved keyword searches of electronic databases including MEDLINE, CINAHL, PsycINFO, EBM Reviews and Google Scholar between August and December 2013. Keywords included ‘scaling up’ and ‘scalability’, while the search terms ‘intervention research’, ‘translational research’, ‘research dissemination’, ‘health promotion’ and ‘public health’ were used to focus the search on public health approaches. Studies included in the review were published in English from January 1990 to December 2013 and described processes, theories or frameworks associated with scaling up public health and health promotion interventions.ResultsThere is a growing body of literature describing frameworks for scaling health interventions, with the review identifying eight frameworks, the majority of which have an explicit focus on scaling up health action in low and middle income country contexts. Key success factors for scaling up included the importance of establishing monitoring and evaluation systems, costing and economic modelling of intervention approaches, active engagement of a range of implementers and the target community, tailoring the scaled-up approach to the local context, the use of participatory approaches, the systematic use of evidence, infrastructure to support implementation, strong leadership and champions, political will, well defined scale-up strategy and strong advocacy.ConclusionsEffective scaling up requires the systematic use of evidence, and it is essential that data from implementation monitoring is linked to decision making throughout the scaling up process. Conceptual frameworks can assist both policy makers and researchers to determine the type of research that is most useful at different stages of scaling up processes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13012-015-0301-6) contains supplementary material, which is available to authorized users.

The 'how to' of scaling up public health interventions for maximum reach and outcomes is receiving greater attention; however, there remains a paucity of practical tools to guide those actively involved in scaling up processes in high-income countries. To fill this gap, the New South Wales Ministry of Health developed Increasing the scale of population health interventions: a guide (2014). The guide was informed by a systematic review of scaling up models and methods, and a two-round Delphi process with a sample of senior policy makers, practitioners and researchers actively involved in scaling up processes.Although it is a practical guide to assist health policy makers, health practitioners and others responsible for scaling up effective population health interventions, it can also be used by researchers in the design of research studies that are potentially suitable for scaling up, particularly where research-practice collaborations are involved. The guide is divided into four steps: step 1, 'scalability assessment', aims to determine if an intervention is scalable; step 2, 'developing a scale up plan', aims to develop a practical and workable scaling up plan that can be used to convince stakeholders there is a compelling case for action.Step 3, 'preparing for scale up', aims to identify ways of securing resources needed for going to scale, operating at scale, and building a foundation of legitimacy and support to sustain the scaling up effort through the implementation stage; and step 4, 'scaling up the intervention', involves putting the plan developed in step 2 into place.Although the guide is written as though the user is starting from the point of assessing the scalability of an intervention, later steps can be used by those already involved in scaling up to review their implementation processes. The guide is not intended to be prescriptive. Its purpose is to help policy makers, practitioners, researchers and other decision makers decide on appropriate methodological and practical choices, and balance what is desirable with what is feasible.

BackgroundInterventions that work must be effectively delivered at scale to achieve population level benefits. Researchers must choose among a vast array of implementation frameworks (> 60) that guide design and evaluation of implementation and scale-up processes. Therefore, we sought to recommend conceptual frameworks that can be used to design, inform, and evaluate implementation of physical activity (PA) and nutrition interventions at different stages of the program life cycle. We also sought to recommend a minimum data set of implementation outcome and determinant variables (indicators) as well as measures and tools deemed most relevant for PA and nutrition researchers.MethodsWe adopted a five-round modified Delphi methodology. For rounds 1, 2, and 3 we administered online surveys to PA and nutrition implementation scientists to generate a rank order list of most commonly used; i) implementation and scale-up frameworks, ii) implementation indicators, and iii) implementation and scale-up measures and tools. Measures and tools were excluded after round 2 as input from participants was very limited. For rounds 4 and 5, we conducted two in-person meetings with an expert group to create a shortlist of implementation and scale-up frameworks, identify a minimum data set of indicators and to discuss application and relevance of frameworks and indicators to the field of PA and nutrition.ResultsThe two most commonly referenced implementation frameworks were the Framework for Effective Implementation and the Consolidated Framework for Implementation Research. We provide the 25 most highly ranked implementation indicators reported by those who participated in rounds 1–3 of the survey. From these, the expert group created a recommended minimum data set of implementation determinants (n = 10) and implementation outcomes (n = 5) and reconciled differences in commonly used terms and definitions.ConclusionsResearchers are confronted with myriad options when conducting implementation and scale-up evaluations. Thus, we identified and prioritized a list of frameworks and a minimum data set of indicators that have potential to improve the quality and consistency of evaluating implementation and scale-up of PA and nutrition interventions. Advancing our science is predicated upon increased efforts to develop a common ‘language’ and adaptable measures and tools.

Maximizing the benefits of investments in obesity research requires effective interventions to be adopted and disseminated broadly across populations (scaled-up).However, interventions often need considerable adaptation to enable implementation at scale, a process that can reduce the effects of interventions. A systematic review was undertaken for trials that sought to deliver an obesity intervention to populations on a larger scale than a preceding randomized controlled trial (RCT) that established its efficacy. Ten scaled-up obesity interventions (six prevention and four treatment) were included. All trials made adaptations to interventions as part of the scale-up process, with mode of delivery adaptations being most common. A metaanalysis of body mass index (BMI)/BMI z score (zBMI) from three prevention RCTs found no significant benefit of scaled-up interventions relative to control (standardized mean difference [SMD] = 0.03; 95% CI, −0.09 to 0.15, P = 0.639 − I 2 = 0.0%). All four treatment interventions reported significant improvement on all measures of weight status. Pooled BMI/zBMI data from prevention trials found significantly lower effects among scaled-up intervention trials than those reported in prescale-up efficacy trials (SMD = −0.11; 95% CI, −0.20 to −0.02, P = 0.018 − I 2 = 0.0%). Across measures of weight status, physical activity/sedentary behaviour, and nutrition, the effects reported in scaled-up interventions were typically 75% or less of the effects reported in pre-scale-up efficacy trials. The findings underscore the challenge of scaling-up obesity interventions.

Background: Promising health interventions tested in pilot studies will only achieve population-wide impact if they are implemented at scale across communities and health systems. Scaling up effective health interventions is vital as not doing so denies the community the most effective services and programmes. However, there remains a paucity of practical tools to assess the suitability of health interventions for scale-up. The Intervention Scalability Assessment Tool (ISAT) was developed to support policy-makers and practitioners to make systematic assessments of the suitability of health interventions for scale-up. Methods: The ISAT was developed over three stages; the first stage involved a literature review to identify similar tools and frameworks that could be used to guide scalability assessments, and expert input to develop draft ISAT content. In the second stage, the draft ISAT tool was tested with end users. The third stage involved revising and re-testing the ISAT with end users to further refine the language and structure of the final ISAT. Results: A variety of information and sources of evidence should be used to complete the ISAT. The ISAT consists of three parts. Part A: 'setting the scene' requires consideration of the context in which the intervention is being considered for scale-up and consists of five domains, as follows: (1) the problem; (2) the intervention; (3) strategic/ political context; (4) evidence of effectiveness; and (5) intervention costs and benefits. Part B asks users to assess the potential implementation and scale-up requirements within five domains, namely (1) fidelity and adaptation; (2) reach and acceptability; (3) delivery setting and workforce; (4) implementation infrastructure; and (5) sustainability. Part C generates a graphical representation of the strengths and weaknesses of the readiness of the proposed intervention for scale-up. Users are also prompted for a recommendation as to whether the intervention (1) is recommended for scale-up, (2) is promising but needs further information before scaling up, or (3) does not yet merit scale-up. Conclusion: The ISAT fills an important gap in applied scalability assessment and can become a critical decision support tool for policy-makers and practitioners when selecting health interventions for scale-up. Although the ISAT is designed to be a health policy and practitioner tool, it can also be used by researchers in the design of research to fill important evidence gaps.

BackgroundDecisions to scale up population health interventions from small projects to wider state or national implementation is fundamental to maximising population-wide health improvements. The objectives of this study were to examine: i) how decisions to scale up interventions are currently made in practice; ii) the role that evidence plays in informing decisions to scale up interventions; and iii) the role policy makers, practitioners, and researchers play in this process.MethodsInterviews with an expert panel of senior Australian and international public health policy-makers (n = 7), practitioners (n = 7), and researchers (n = 7) were conducted in May 2013 with a participation rate of 84%.ResultsScaling up decisions were generally made through iterative processes and led by policy makers and/or practitioners, but ultimately approved by political leaders and/or senior executives of funding agencies. Research evidence formed a component of the overall set of information used in decision-making, but its contribution was limited by the paucity of relevant intervention effectiveness research, and data on costs and cost effectiveness. Policy makers, practitioners/service managers, and researchers had different, but complementary roles to play in the process of scaling up interventions.ConclusionsThis analysis articulates the processes of how decisions to scale up interventions are made, the roles of evidence, and contribution of different professional groups. More intervention research that includes data on the effectiveness, reach, and costs of operating at scale and key service delivery issues (including acceptability and fit of interventions and delivery models) should be sought as this has the potential to substantially advance the relevance and ultimately usability of research evidence for scaling up population health action.

The recent proliferation of strategies designed to increase the use of research in health policy (knowledge exchange) demands better application of contemporary conceptual understandings of how research shapes policy. Predictive models, or action frameworks, are needed to organise existing knowledge and enable a more systematic approach to the selection and testing of intervention strategies. Useful action frameworks need to meet four criteria: have a clearly articulated purpose; be informed by existing knowledge; provide an organising structure to build new knowledge; and be capable of guiding the development and testing of interventions. This paper describes the development of the SPIRIT Action Framework. A literature search and interviews with policy makers identified modifiable factors likely to influence the use of research in policy. An iterative process was used to combine these factors into a pragmatic tool which meets the four criteria. The SPIRIT Action Framework can guide conceptually-informed practical decisions in the selection and testing of interventions to increase the use of research in policy. The SPIRIT Action Framework hypothesises that a catalyst is required for the use of research, the response to which is determined by the capacity of the organisation to engage with research. Where there is sufficient capacity, a series of research engagement actions might occur that facilitate research use. These hypotheses are being tested in ongoing empirical work.