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Related Experiment Videos

Probing the effects of individual components in multiple component prevention programs

S G West1, L S Aiken, M Todd

  • 1Department of Psychology, Arizona State University, Tempe 85287-1104.

American Journal of Community Psychology
|October 1, 1993
PubMed
Summary

This study reviews methods for evaluating multi-component interventions in prevention research. It explores designs and analyses to determine component contributions, program optimization, and underlying processes for better scientific insights.

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Area of Science:

  • Prevention Science
  • Intervention Research
  • Research Methodology

Background:

  • Assessing individual component contributions in multi-component interventions presents significant challenges.
  • Understanding how each part of a program works is crucial for effective prevention.
  • Existing methods may not fully address the complexity of evaluating combined interventions.

Purpose of the Study:

  • To review and evaluate designs and analyses for assessing multi-component interventions.
  • To address key questions regarding component contributions, program optimization, and process.
  • To offer design enhancements for strengthening evaluation techniques.

Main Methods:

  • Factorial and fractional factorial designs for assessing individual component contributions.

Related Experiment Videos

  • Response surface designs for quantitatively scaling components and optimizing programs.
  • Mediational analysis as a hybrid approach to explore intervention processes.
  • Main Results:

    • Factorial designs help determine if individual components contribute to outcomes.
    • Response surface designs aid in optimizing program composition.
    • Mediational analysis illuminates the processes through which interventions achieve effects.

    Conclusions:

    • Specific designs and analyses can effectively address complex questions in multi-component intervention research.
    • Enhancements to these techniques can further improve their utility.
    • These methods promise to advance both basic and applied prevention science.