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Adaptive Designs for Randomized Trials in Public Health
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In this article, we present a discussion of two general ways in which the traditional randomized trial can be modified or adapted in response to the data being collected. We use the term adaptive design to refer to a trial in which characteristics of the study itself, such as the proportion assigned to active intervention versus control, change during the trial in response to data being collected. The term adaptive sequence of trials refers to a decision-making process that fundamentally informs the conceptualization and conduct of each new trial with the results of previous trials. Our discussion below investigates the utility of these two types of adaptations for public health evaluations. Examples are provided to illustrate how adaptation can be used in practice. From these case studies, we discuss whether such evaluations can or should be analyzed as if they were formal randomized trials, and we discuss practical as well as ethical issues arising in the conduct of these new-generation trials.
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“The impetus to blend or explicitly link research traditions in the service of accelerating scientific progress and enhancing public health impact is not at all new,4,38–40 and the idea of blending clinical effectiveness and implementation research elements is also not new.”
From Effectiveness-implementation Hybrid Designs: Combining Elements of Clinical Effectiveness and Implementation Research to Enhance Public Health Impact (2012) · cites this paper as [40]
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“This traditional pipeline does not imply that research always continues to move in one direction as the sequential progression of intervention studies is often cyclical (14).”
From An Overview of Research and Evaluation Designs for Dissemination and Implementation (2017) · cites this paper as [14]
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Design and Analysis in Dissemination and Implementation Research
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Self-citationPrevention Science: An Epidemiological Approach
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Metadata
- Authors
- Brown, C. H., Ten Have, T. R., Jo, B., Dagne, G., Wyman, P. A., Muthén, B., & Gibbons, R. D.
- Affiliations
- University of South Florida (US)
- Department of Biostatistics, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104
- Stanford Medicine (US)
- University of Rochester Medicine (US)
- University of California, Los Angeles (US)
- University of Illinois Chicago (US)
- Venue
- Annual Review of Public Health
- Publisher
- Annual Reviews
- Published
- 2009-04-01
- Volume
- 30
- Issue
- 1
- Pages
- 1-25
- ISSN
- 0163-7525 (ISSN-L)
- 1545-2093
- PMC
- PMC2778326
- OpenAlex
- W2127297180
- Cited by
- 184
- References
- 153
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 4 · 2023: 7 · 2022: 3 · 2021: 18 · 2020: 31 · 2019: 11 · 2018: 9 · 2017: 15 · 2016: 6 · 2015: 11 · 2014: 12 · 2013: 12 · 2012: 13
- FWCI
- 1.40
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annual Review of Public Health (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- Substance Abuse and Mental Health Services Administration
- National Institute of Mental Health (P30MH068685, R01MH078016, R01MH40859, R34MH071189, R01MH076158, R01MH068423, P30MH074678, P20MH071897, R01MH06624, R01MH066319, R01MH069353, R01MH080122, R01MH040859)
- National Institute on Drug Abuse (R01DA025192, P30DA023920)
- National Institute of Neurological Disorders and Stroke (U54NS057405)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Public Administration › Evaluation and Performance Assessment
- Keywords
- adaptive design, adaptive randomization, public health assessment, trial ethics, sequential decision making
- MeSH terms
- Decision Making, Financing, Government, Humans, National Institutes of Health (U.S.), Research Design, United States, Public Health Practice, Randomized Controlled Trials as Topic, Evidence-Based Practice
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