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Related Experiment Videos

Mounting a community-randomized trial: sample size, matching, selection, and randomization issues in PRISM.

Lyndsey Watson1, Rhonda Small, Stephanie Brown

  • 1Centre for the Study of Mothers' and Children's Health, La Trobe University, Bundoora Victoria, 3083, Australia. l.watson@latrobe.edu.au

Controlled Clinical Trials
|May 26, 2004
PubMed
Summary

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Establishing a large cluster-randomized trial for maternal depression support in Victoria, Australia, required careful community selection and matching. The study aimed to detect a 3% reduction in maternal depression using a matched-pair design.

Area of Science:

  • Public Health
  • Clinical Trials Methodology
  • Community Interventions

Background:

  • Community and primary care interventions are crucial for maternal well-being.
  • Large-scale trials are needed to evaluate the effectiveness of community-based support programs.
  • The Program of Resources, Information and Support for Mothers (PRISM) aimed to support mothers in the first year postpartum.

Purpose of the Study:

  • To describe the processes for establishing a large cluster-randomized trial in Victoria, Australia.
  • To detail the design factors, including sample size estimation and community randomization.
  • To outline the methods for community selection, matching, and allocation for the PRISM intervention.

Main Methods:

  • A cluster-randomized trial utilizing a matched-pair design with eight pairs of communities.

Related Experiment Videos

  • Sample size calculations adjusted for cluster randomization and matched pairs, requiring approximately 800 responses per community.
  • Data collection on birth numbers, LGA size, and community capacity for intervention implementation.

    • Main Results:

    • The study details the complex process of selecting and matching 16 local government areas (LGAs).
    • Sample size estimates indicated the need for substantial participant response to detect a 3% reduction in maternal depression.
    • Methods for managing boundary issues and potential contamination between communities were addressed.

    Conclusions:

    • Establishing large community-based trials involves balancing the need for statistical power with resource limitations.
    • Careful planning in community selection, matching, and randomization is essential for trial validity.
    • The described processes provide a framework for implementing similar community-level intervention trials.