The need for a complex systems model of evidence for public health
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The traditional action research cycle of needs assessment, development, implementation, monitoring, and evaluation suggests a logical, causal process that is difficult to identify in a complex school system initiative where changes interact with each other and with contextual aspects.
“Traditionally, many action researchers in school interventions have followed the cycle of needs assessment, development, implementation, monitoring, and evaluation of change [23,24]. However, the limitation of following these steps is that they suggest a logical, causal process, which is difficult to identify in a complex school system initiative [25], where changes are interacting with each other”
From The Healthy Primary School of the Future: A Contextual Action-Oriented Research Approach (2018) · cites this paper as [26]
Randomization is neither desirable nor feasible in this study.
“Since randomization is neither desirable nor feasible here [26], a quasi-experimental study design is used.”
From The Healthy Primary School of the Future: A Contextual Action-Oriented Research Approach (2018) · cites this paper as [26]
Thinking about systems helps us understand the interaction between an intervention and the context in which it is implemented in a dynamic way.
“Thinking about systems helps us understand the interaction between an intervention and the context in which it is implemented in a dynamic way.22”
From A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance (2021) · cites this paper as [22]
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- Authors
- Rutter, H., Savona, N., Glonti, K., Bibby, J., Cummins, S., Finegood, D. T., Greaves, F., Harper, L., Hawe, P., Moore, L., Petticrew, M., Rehfuess, E., Shiell, A., Thomas, J., & White, M.
- Affiliations
- London School of Hygiene & Tropical Medicine (GB)
- Health Foundation (GB)
- Simon Fraser University (CA)
- Public Health England (GB)
- The University of Sydney (AU)
- MRC/CSO Social and Public Health Sciences Unit (GB)
- Ludwig-Maximilians-Universität München (DE)
- La Trobe University (AU)
- University College London (GB)
- University of Cambridge (GB)
- Corresponding author
- Rutter, Harry
- ORCID
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 390
- Issue
- 10112
- Pages
- 2602-2604
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- OpenAlex
- W2626277945
- Cited by
- 1,260
- References
- 33
- Citations by year
- 2026: 107 · 2025: 139 · 2024: 147 · 2023: 150 · 2022: 148 · 2021: 149 · 2020: 193 · 2019: 112 · 2018: 90 · 2017: 24
- FWCI
- 102.22
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Pure (University of Bath) (submittedVersion, cc-by-nc-nd)
- Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
- Apollo (University of Cambridge) (submittedVersion, cc-by-nc-nd)
- Apollo
- Funders
- UK Medical Research Council (MC_UU_12017/14)
- Chief Scientist Office (SPHSU14)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Health Sciences › Health Professions › General Health Professions › Public Health Policies and Education
- Keywords
- complex systems, public health evidence, evidence-based public health, causal inference, public health interventions, intervention implementation
- MeSH terms
- Humans, Models, Theoretical, Public Health, Public Health Administration, Systems Analysis, Evidence-Based Practice
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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