The DOI matches its Crossref record; 156 of the 157 references it cites were found in a registry or an index.
Adaptive Designs for Randomized Trials in Public Health
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“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]
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Evaluating the public health impact of health promotion interventions: the RE-AIM framework.
Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999) · American Journal of Public Health · doi:10.2105/ajph.89.9.1322 · Cited by 7,217
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Identification of Causal Effects Using Instrumental Variables
Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230
Influence : science and practice
Cialdini, R. B. (1985) · Cited by 3,581
Eckstein, S. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9780511550089.028 · Cited by 3,514
Clinical Trials: A Practical Approach.
Hill, I. D., & Pocock, S. (1984) · Biometrics · doi:10.2307/2531186 · Cited by 2,918
Equipoise and the Ethics of Clinical Research
Freedman, B. (1987) · New England Journal of Medicine · doi:10.1056/nejm198707163170304 · Cited by 2,339
Participation in Cancer Clinical Trials: Race-, Sex-, and Age-Based Disparities
Murthy, V. H., Krumholz, H. M., & Gross, C. P. (2004) · JAMA · doi:10.1001/jama.291.22.2720 · Cited by 2,078
Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research
(1994) · doi:10.17226/2139 · Cited by 2,073
Research works printed but not linked: 7
- Bartlett RH, 1976, Trans. Am. Soc. Artif. Intern. Organs, 22, 80
- Berry D, 2001, Biopharm. Rep., 9, 1
- Boruch B, 2002, Socialvetenskaplig Tidskr., 2, 221
- Jo B, 2003, Multilevel Modeling: Methodological Advances, Issues, and Applications, 112
- McDonald C, 1992, MD Comput., 9, 304
- Mugford M, 2008, Cochrane Database Syst. Rev., 3, CD001340
- Muthén BO, 2003, J. Am. Stat. Assoc., 98, 311
Cited by
Sorted by citations
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-013-0528-y · Cited by 12,038
“…poor in assessing the benefit from complex public health or medical interventions that account for individual preferences for or against certain interventions, differential adherence or attrition, or varying dosage or tailoring of an intervention to individual needs'' (Brown et al. 2009, p. 2).”
BackgroundMethodMoher, D., Hopewell, S., Schulz, K. F., Montori, V., Gotzsche, P. C., Devereaux, P. J., Elbourne, D., Egger, M., & Altman, D. G. (2010) · BMJ · doi:10.1136/bmj.c869 · Cited by 8,883
Curran, G. M., Bauer, M., Mittman, B., Pyne, J. M., & Stetler, C. (2012) · Medical Care · doi:10.1097/mlr.0b013e3182408812 · Cited by 4,058
Advancing a Conceptual Model of Evidence-Based Practice Implementation in Public Service Sectors
Aarons, G. A., Hurlburt, M., & Horwitz, S. M. (2011) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-010-0327-7 · Cited by 3,240
“This phase can also include models for expansion and scaling-up within a service system beyond an initial implementation trial (Brown et al. 2009).”
BackgroundMoher, D., Hopewell, S., Schulz, K. F., Montori, V., Gøtzsche, P. C., Devereaux, P. J., Elbourne, D., Egger, M., & Altman, D. G. (2012) · International Journal of Surgery · doi:10.1016/j.ijsu.2011.10.001 · Cited by 2,345
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
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
