Developing multicomponent interventions using fractional factorial designs
Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of pot...
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Published in | Statistics in medicine Vol. 28; no. 21; pp. 2687 - 2708 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
20.09.2009
Wiley Subscription Services, Inc |
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Abstract | Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. Copyright © 2009 John Wiley & Sons, Ltd. |
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AbstractList | Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. [PUBLICATION ABSTRACT] Abstract Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. Copyright © 2009 John Wiley & Sons, Ltd. Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refiing such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. Copyright © 2009 John Wiley & Sons, Ltd. |
Author | Strecher, Victor J. Chakraborty, Bibhas Murphy, Susan A. Collins, Linda M. |
AuthorAffiliation | 1 Department of Statistics and The Institute for Social Research, University of Michigan 2 The Methodology Center and Department of Human Development and Family Studies, Pennsylvania State University 3 Center for Health Communications Research, University of Michigan |
AuthorAffiliation_xml | – name: 3 Center for Health Communications Research, University of Michigan – name: 2 The Methodology Center and Department of Human Development and Family Studies, Pennsylvania State University – name: 1 Department of Statistics and The Institute for Social Research, University of Michigan |
Author_xml | – sequence: 1 givenname: Bibhas surname: Chakraborty fullname: Chakraborty, Bibhas email: bibhas@umich.edu organization: Department of Statistics and The Institute for Social Research, University of Michigan, Ann Arbor, MI, U.S.A – sequence: 2 givenname: Linda M. surname: Collins fullname: Collins, Linda M. organization: The Methodology Center and Department of Human Development and Family Studies, Pennsylvania State University, University Park, U.S.A – sequence: 3 givenname: Victor J. surname: Strecher fullname: Strecher, Victor J. organization: Center for Health Communications Research, University of Michigan, Ann Arbor, MI, U.S.A – sequence: 4 givenname: Susan A. surname: Murphy fullname: Murphy, Susan A. organization: Department of Statistics and The Institute for Social Research, University of Michigan, Ann Arbor, MI, U.S.A |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19575485$$D View this record in MEDLINE/PubMed |
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Snippet | Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health... Abstract Multicomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common... |
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SubjectTerms | experimental design Factor Analysis, Statistical Factorial experiments Follow-Up Studies fractional factorial design Health sciences Humans Intervention Mass Screening Models, Statistical multicomponent intervention Research Design screening Simulation Smoking cessation Smoking Cessation - methods Smoking Cessation - statistics & numerical data |
Title | Developing multicomponent interventions using fractional factorial designs |
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