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A strategy for optimizing and evaluating behavioral interventions

  • Published:
Annals of Behavioral Medicine

Abstract

Background: Although the optimization of behavioral interventions offers the potential of both public health and research benefits, currently there is no widely agreed-upon principled procedure for accomplishing this.Purpose: This article suggests a multiphase optimization strategy (MOST) for achieving the dual goals of program optimization and program evaluation in the behavioral intervention field.Methods: MOST consists of the following three phases: (a) screening, in which randomized experimentation closely guided by theory is used to assess an array of program and/or delivery components and select the components that merit further investigation; (b) refining, in which interactions among the identified set of components and their interrelationships with covariates are investigated in detail, again via randomized experiments, and optimal dosage levels and combinations of components are identified; and (c) confirming, in which the resulting optimized intervention is evaluated by means of a standard randomized intervention trial. To make the best use of available resources, MOST relies on design and analysis tools that help maximize efficiency, such as fractional factorials.Results: A slightly modified version of an actual application of MOST to develop a smoking cessation intervention is used to develop and present the ideas.Conclusions: MOST has the potential to husband program development resources while increasing our understanding of the individual program and delivery components that make up interventions. Considerations, challenges, open questions, and other potential benefits are discussed.

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Author information

Authors and Affiliations

  1. The Methodology Center Department of Human Development and Family Studies, The Pennsylvania State University, USA

    Linda M. Collins Ph.D.

  2. Institute for Social Research Department of Statistics, University of Michigan, USA

    Susan A. Murphy Ph.D.

  3. Department of Statistics Department of Industrial and Operations Engineering, University of Michigan, USA

    Vijay N. Nair Ph.D.

  4. Department of Health Behavior and Health Education, University of Michigan, USA

    Victor J. Strecher Ph.D.

Authors
  1. Linda M. Collins Ph.D.
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  2. Susan A. Murphy Ph.D.
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  3. Vijay N. Nair Ph.D.
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  4. Victor J. Strecher Ph.D.
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Corresponding author

Correspondence to Linda M. Collins Ph.D..

Additional information

This work has been supported by National Institute on Drug Abuse Grants P50 DA10075 (Dr. Collins and Dr. Murphy) and K02 DA15674 (Dr. Murphy), National Cancer Institute Grant P50 CA 101451 (Dr. Strecher, Dr. Murphy, and Dr. Nair), and National Science Foundation Grant DMS 0204247 (Dr. Nair). This article has benefited from discussion at the 2003 Snowbird Conference and the 2003 Society for Prevention Research Conference, particularly the comments of Gilbert Botvin, Richard Clayton, Delbert Eliot, Brian Flay, David Hawkins, Elizabeth Robertson, and Richard Spoth. It has also benefited from the comments of John Graham and many other colleagues at Penn State’s Methodology Center and Prevention Center.

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Collins, L.M., Murphy, S.A., Nair, V.N. et al. A strategy for optimizing and evaluating behavioral interventions. ann. behav. med. 30, 65–73 (2005). https://doi.org/10.1207/s15324796abm3001_8

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  • DOI: https://doi.org/10.1207/s15324796abm3001_8

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