Realist randomised controlled trials: A new approach to evaluating complex public health interventions
Abstract
Randomized trials of complex public health interventions generally aim to identify what works, accrediting specific intervention 'products' as effective. This approach often fails to give sufficient consideration to how intervention components interact with each other and with local context. 'Realists' argue that trials misunderstand the scientific method, offer only a 'successionist' approach to causation, which brackets out the complexity of social causation, and fail to ask which interventions work, for whom and under what circumstances. We counter-argue that trials are useful in evaluating social interventions because randomized control groups actually take proper account of rather than bracket out the complexity of social causation. Nonetheless, realists are right to stress understanding of 'what works, for whom and under what circumstances' and to argue for the importance of theorizing and empirically examining underlying mechanisms. We propose that these aims can be (and sometimes already are) examined within randomized trials. Such 'realist' trials should aim to: examine the effects of intervention components separately and in combination, for example using multi-arm studies and factorial trials; explore mechanisms of change, for example analysing how pathway variables mediate intervention effects; use multiple trials across contexts to test how intervention effects vary with context; draw on complementary qualitative and quantitative data; and be oriented towards building and validating 'mid-level' program theories which would set out how interventions interact with context to produce outcomes. This last suggestion resonates with recent suggestions that, in delivering truly 'complex' interventions, fidelity is important not so much in terms of precise activities but, rather, key intervention 'processes' and 'functions'. Realist trials would additionally determine the validity of program theory rather than only examining 'what works' to better inform policy and practice in the long-term.
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Qualitative research can strengthen the design of randomized controlled trials of complex public health interventions, and this argument applies equally to natural experiments.
“Qualitative research can strengthen the design of RCTs of complex public health interventions (10, 56), and this argument applies equally to NEs (38).”
From Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research (2017) · cites this paper as [10]
Findings from process evaluation can facilitate further development of the intervention programme theory.
“Such findings can facilitate further development of the intervention programme theory.75”
From A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance (2021) · cites this paper as [75]
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- Authors
- Bonell, C., Fletcher, A., Morton, M., Lorenc, T., & Moore, L.
- Affiliations
- University of Oxford (GB)
- London School of Hygiene & Tropical Medicine (GB)
- Cardiff University (GB)
- Corresponding author
- Bonell, Chris
- Venue
- Social Science & Medicine
- Publisher
- Elsevier BV
- Published
- 2012-12
- Volume
- 75
- Issue
- 12
- Pages
- 2299-2306
- ISSN
- 0277-9536 (ISSN-L)
- OpenAlex
- W2100643950
- Cited by
- 582
- References
- 71
- Citations by year
- 2026: 18 · 2025: 22 · 2024: 29 · 2023: 32 · 2022: 52 · 2021: 50 · 2020: 97 · 2019: 49 · 2018: 50 · 2017: 48 · 2016: 42 · 2015: 48 · 2014: 22 · 2013: 22
- FWCI
- 52.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Social Science & Medicine (publishedVersion)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Funders
- Economic and Social Research Council (ES/G007543/1)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- realist research, randomized controlled trials, social causation, mechanisms of change, program theory, multi-arm trials, factorial trial, context effects, intervention fidelity, theory validation
- MeSH terms
- Health Promotion, Humans, Public Health, Program Evaluation, Randomized Controlled Trials as Topic
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