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Alternatives to the Randomized Controlled Trial

Guardado en:
Publicado en:American Journal of Public Health vol. 98, no. 8 (Aug 2008), p. 1359-1366
Autor principal: West, Stephen G, PhD
Otros Autores: Duan, Naihua, PhD, Pequegnat, Willo, PhD, Gaist, Paul, PhD, MPH, Des Jarlais, Don C, PhD, Holtgrave, David, PhD, Szapocznik, José, PhD, Fishbein, Martin, PhD, Rapkin, Bruce, PhD, Clatts, Michael, PhD, Mullen, Patricia Dolan, DrPH
Publicado:
American Public Health Association
Materias:
Causality
Choice Behavior
Epidemiologic Research Design
Humans
Public Health
Qualitative Research
Randomized Controlled Trials as Topic
Regression Analysis
Reproducibility of Results
Research Subjects > psychology
Studies
Medical research
Tobacco smoke
Religious organizations
Prevention programs
Intervention
Confidence intervals
Employment
Clinical trials
Research
Validity
Hurricanes
Job hunting
Environmental effects
Passive smoking
Observational studies
Causal models
Threats
Research design
Tobacco
Alternative approaches
Assignment
Social
Acceso en línea:Citation/Abstract
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Resumen: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.
ISSN:0090-0036
0002-9572
0271-4353
0273-1975
Fuente:ABI/INFORM Global