Alternatives to the Randomized Controlled Trial
Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspective...
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| Published in | American journal of public health (1971) Vol. 98; no. 8; pp. 1359 - 1366 |
|---|---|
| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Washington, DC
Am Public Health Assoc
01.08.2008
American Public Health Association |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option.
Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment.
In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented. |
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| AbstractList | Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented. [PUBLICATION ABSTRACT] Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented.Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented. Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented. Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented. |
| Author | Fishbein, Martin Clatts, Michael Holtgrave, David Szapocznik, Jose Pequegnat, Willo Gaist, Paul West, Stephen G Des Jarlais, Don C Rapkin, Bruce Duan, Naihua Mullen, Patricia Dolan |
| AuthorAffiliation | Stephen G. West is with Arizona State University, Tempe. Naihua Duan is with Columbia University, New York, NY, and New York State Psychiatric Institute, New York. Willo Pequegnat is with the National Institute of Mental Health, Bethesda, MD. Paul Gaist is with the National Institutes of Health, Bethesda. Don C. Des Jarlais is with Beth Israel Medical Center, New York. David Holtgrave is with the Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD. José Szapocznik is with the University of Miami School of Medicine, Miami, FL. Martin Fishbein is with the Annenberg School for Communication, University of Pennsylvania, Philadelphia. Bruce Rapkin is with Memorial Sloan-Kettering Cancer Center, New York. Michael Clatts is with the National Development and Research Institutes, Inc, New York. Patricia Mullen is with the University of Texas School of Public Health, Houston |
| AuthorAffiliation_xml | – name: Stephen G. West is with Arizona State University, Tempe. Naihua Duan is with Columbia University, New York, NY, and New York State Psychiatric Institute, New York. Willo Pequegnat is with the National Institute of Mental Health, Bethesda, MD. Paul Gaist is with the National Institutes of Health, Bethesda. Don C. Des Jarlais is with Beth Israel Medical Center, New York. David Holtgrave is with the Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD. José Szapocznik is with the University of Miami School of Medicine, Miami, FL. Martin Fishbein is with the Annenberg School for Communication, University of Pennsylvania, Philadelphia. Bruce Rapkin is with Memorial Sloan-Kettering Cancer Center, New York. Michael Clatts is with the National Development and Research Institutes, Inc, New York. Patricia Mullen is with the University of Texas School of Public Health, Houston |
| Author_xml | – sequence: 1 fullname: West, Stephen G – sequence: 2 fullname: Duan, Naihua – sequence: 3 fullname: Pequegnat, Willo – sequence: 4 fullname: Gaist, Paul – sequence: 5 fullname: Des Jarlais, Don C – sequence: 6 fullname: Holtgrave, David – sequence: 7 fullname: Szapocznik, Jose – sequence: 8 fullname: Fishbein, Martin – sequence: 9 fullname: Rapkin, Bruce – sequence: 10 fullname: Clatts, Michael – sequence: 11 fullname: Mullen, Patricia Dolan |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20528874$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/18556609$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | 2008 INIST-CNRS Copyright American Public Health Association Aug 2008 American Journal of Public Health 2008 |
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| Keywords | Human Clinical trial Randomization Public health |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Note. The views in this article are those of the authors. No official endorsement by the US Department of Health and Human Services or the US National Institutes of Health is intended or should be inferred. Peer Reviewed Contributors S. G. West participated in the initial workshop and helped develop the outline, wrote the initial draft and subsequent drafts of the article incorporating additions and edits, and wrote the final article. N. Duan participated in the initial workshop, participated in the development of the paper outline, drafted part of the article and reviewed and edited the entire article. W. Pequegnat conceptualized the initial workshop on which the article is based, co-chaired the workshop and guided development of original outline, wrote the introduction for the first draft, provided feedback on multiple drafts, and coordinated continued development of the article. P. Gaist participated in the original workshop, guided development of the original outline, provided significant input and contributions throughout the planning, writing, review, and revision stages of this article. He has served as 1 of the 2 primary coordinators responsible for overseeing each phase that has been required in the development and writing of this article. D. C. Des Jarlais chaired the initial workshop that led to the writing of the article, contributed text to various drafts, edited and approved the final draft. D. Holtgrave, J. Szapocznik, M. Fishbein, B. Rapkin, M. C. Clatts, and P.D. Mullen attended the workshop, helped conceptualize ideas, contributed text, and reviewed and edited drafts. Requests for reprints should be sent to Stephen G. West, Psychology Department, Arizona State University, Tempe, AZ 85287-1104 (e-mail: sgwest@asu.edu). |
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| SubjectTerms | Biological and medical sciences Causality Choice Behavior Clinical trials Confidence intervals Employment Environmental effects Epidemiologic Research Design Humans Hurricanes Intervention Job hunting Medical research Medical sciences Miscellaneous Observational studies Passive smoking Prevention programs Public Health Public health. Hygiene Public health. Hygiene-occupational medicine Qualitative Research Randomized Controlled Trials as Topic Regression Analysis Religious organizations Reproducibility of Results Research Innovations and Recommendations Research Subjects - psychology Studies Tobacco smoke Validity |
| Title | Alternatives to the Randomized Controlled Trial |
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