Abstract

Preventing chronic diseases, such as cancer, cardiovascular disease and diabetes, requires complex interventions, involving multi-component and multi-level efforts that are tailored to the contexts in which they are delivered. Despite an increasing number of complex interventions in public health, many fail to be ‘scaled up’. This study aimed to increase understanding of how and under what conditions complex public health interventions may be scaled up to benefit more people and populations.A realist synthesis was conducted and discussed at an in-person workshop involving practitioners responsible for scaling up activities. Realist approaches view causality through the linkages between changes in contexts (C) that activate mechanisms (M), leading to specific outcomes (O) (CMO configurations). To focus this review, three cases of complex interventions that had been successfully scaled up were included: Vibrant Communities, Youth Build USA and Pathways to Education. A search strategy of published and grey literature related to each case was developed, involving searches of relevant databases and nominations from experts. Data extracted from included documents were classified according to CMO configurations within strategic themes. Findings were compared and contrasted with guidance from diffusion theory, and interpreted with knowledge users to identify practical implications and potential directions for future research.Four core mechanisms were identified, namely awareness, commitment, confidence and trust. These mechanisms were activated within two broad scaling up strategies, those of renewing and regenerating, and documenting success. Within each strategy, specific actions to change contexts included building partnerships, conducting evaluations, engaging political support and adapting funding models. These modified contexts triggered the identified mechanisms, leading to a range of scaling up outcomes, such as commitment of new communities, changes in relevant legislation, or agreements with new funding partners.This synthesis applies and advances theory, realist methods and the practice of scaling up complex interventions. Practitioners may benefit from a number of coordinated efforts, including conducting or commissioning evaluations at strategic moments, mobilising local and political support through relevant partnerships, and promoting ongoing knowledge exchange in peer learning networks. Action research studies guided by these findings, and studies on knowledge translation for realist syntheses are promising future directions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12961-016-0158-4) contains supplementary material, which is available to authorized users.

Highlights

  • Over recent years, the field of implementation science has garnered much interest as a way to study and understand how to close the gap between what we know and what we do to optimise the health of populations [1, 2]

  • This study responds to calls from researchers and those involved in designing or delivering complex interventions, to understand how, why and under what conditions such interventions may be scaled up in order to meet the needs of the populations they serve

  • The following sections present the common mechanisms activated across the three case examples, followed by discussion of their role in scaling up with illustrative context– mechanisms–outcomes (CMO) configurations from the case examples

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Summary

Introduction

The field of implementation science has garnered much interest as a way to study and understand how to close the gap between what we know and what we do to optimise the health of populations [1, 2]. This interest has stemmed from an increasing recognition that, despite the development of innovative products, practices and programs, we have often fallen short of realising their full potential impact, due to widespread adoption and scaling up challenges [3]. Research agendas focused on sustainability are emerging, calling for greater exploration of key sustainability issues such as methods for sustainability research and infrastructure to support sustainability research [9]

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