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Single-case synthesis tools II: Comparing quantitative outcome measures.

Kathleen N Zimmerman1, James E Pustejovsky2, Jennifer R Ledford1

  • 1Vanderbilt University, USA.

Research in Developmental Disabilities
|March 12, 2018
PubMed
Summary
This summary is machine-generated.

Evaluating sensory-based interventions (SBI) using different single-case design (SCD) analysis methods reveals that conclusions on effectiveness vary. The choice of quantitative measures significantly impacts the interpretation of behavior change in SCD meta-analyses.

Keywords:
Meta-analysisOverlap measuresSingle case research designWithin-case effect sizes

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Area of Science:

  • Psychology
  • Intervention Science
  • Research Methodology

Background:

  • Single-case design (SCD) research is crucial for evaluating interventions, especially for young children.
  • Current reviews and meta-analyses employ diverse methods for assessing SCD outcomes.
  • Quantitative effect size measures are frequently used alongside visual analysis.

Purpose of the Study:

  • To compare six quantitative effect size measures across two classes (overlap and parametric) for evaluating SCD effectiveness.
  • To determine how the choice of synthesis method impacts conclusions on intervention effectiveness.
  • To assess the effectiveness of sensory-based interventions (SBI) for young children using these measures.

Main Methods:

  • Compared six effect size measures: percentage non-overlapping data, improvement rate difference, Tau, standardized mean difference, and log response ratio (increasing/decreasing).
  • Evaluated behavior change between baseline and SBI conditions in studies of young children.
  • Conducted subgroup analyses to explore variability in conclusions.

Main Results:

  • Sensory-based interventions (SBI) showed limited effectiveness across most measures, with improvement rate difference being an exception.
  • Subgroup analyses yielded inconsistent conclusions regarding SBI effectiveness.
  • The selection of specific measures for SCD meta-analyses significantly influenced the interpretation of results.

Conclusions:

  • The choice of quantitative measures in single-case design meta-analyses can substantially alter conclusions about intervention effectiveness.
  • Further research is needed to refine methods for SCD meta-analyses.
  • Considerations for using the log response ratio and understanding variability in SCD meta-analysis conclusions are discussed.