Related Experiment Video
Updated: Nov 11, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Mechanisms of scaling up: combining a realist perspective and systems analysis to understand successfully scaled
Harriet Koorts1, Samuel Cassar2, Jo Salmon2
1Deakin University, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Geelong, VIC, Australia. h.koorts@deakin.edu.au.
Background:
Sustainable shifts in population behaviours require system-level implementation and embeddedness of large-scale health interventions. This paper aims to understand how different contexts of scaling up interventions affect mechanisms to produce intended and unintended scale up outcomes.
Methods:
A mixed method study combining a realist perspective and systems analysis (causal loop diagrams) of scaled-up physical activity and/or nutrition interventions implemented at a state/national level in Australia (2010-18). The study involved four distinct phases: Phase 1 expert consultation, database and grey literature searches to identify scaled-up interventions; Phase 2 generating initial Context-Mechanism-Outcome configurations (CMOs) from the WHO ExpandNet framework for scaling up; Phase 3 testing and refining CMOs via online surveys and realist interviews with academics, government and non-government organisations (NGOs) involved in scale up of selected interventions (Phase 1); and Phase 4 generating cross-case mid-range theories represented in systems models of scaling up; validated by member checking. Descriptive statistics were reported for online survey data and realist analysis for interview data.
Results:
Seven interventions were analysed, targeting nutrition (n = 1), physical activity (n = 1), or a combination (n = 5). Twenty-six participants completed surveys; 19 completed interviews. Sixty-three CMO pathways underpinned successful scale up, reflecting 36 scale up contexts, 8 key outcomes; linked via 53 commonly occurring mechanisms. All five WHO framework domains were represented in the systems models. Most CMO pathways included 'intervention attributes' and led to outcomes 'community sustainability/embeddedness' and 'stakeholder buy-in/perceived value'. Irrespective of interventions being scaled in similar contexts (e.g., having political favourability); mechanisms still led to both intended and unintended scale up outcomes (e.g., increased or reduced sustainability).
Conclusion:
This paper provides the first evidence for mechanisms underpinning outcomes required for successful scale up of state or nationally delivered interventions. Our findings challenge current prerequisites for effective scaling suggesting other conditions may be necessary. Future scale up approaches that plan for complexity and encourage iterative adaptation throughout, may enhance scale up outcomes. Current linear, context-to-outcome depictions of scale up oversimplify what is a clearly a complex interaction between perceptions, worldviews and goals of those involved. Mechanisms identified in this study could potentially be leveraged during future scale up efforts, to positively influence intervention scalability and sustainability.
Related Concept Videos
Community Based Intervention
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Scaling
Mechanistic Models: Compartment Models in Individual and Population Analysis
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Nursing Interventions II: Selecting and Classifying the Nursing Interventions
Typical Model Studies

