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Classifying Changes to Preventive Interventions: Applying Adaptation Taxonomies.

Joseph N Roscoe1, Valerie B Shapiro2, Kelly Whitaker3

  • 1Center for Prevention Research in Social Welfare, University of California Berkeley School of Social Welfare, 120 Haviland Hall, Berkeley, CA, 94720, USA. joe.n.roscoe@berkeley.edu.

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Summary
This summary is machine-generated.

This study evaluated four adaptation taxonomies for classifying changes in a social emotional learning program. Findings reveal variations in taxonomy coverage and clarity, impacting consistent assessment of intervention adaptations.

Keywords:
AdaptationImplementationMeasurementPreventionSocial and emotional learning

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Area of Science:

  • Implementation Science
  • Preventive Intervention Research
  • Educational Psychology

Background:

  • High-quality implementation is crucial for preventive intervention effectiveness.
  • While fidelity to a practice model is ideal, some adaptation of interventions is often necessary or beneficial in real-world settings.
  • Existing adaptation taxonomies aim to standardize the study of intervention modifications and their impact on outcomes.

Purpose of the Study:

  • To retrospectively classify adaptations made during the implementation of a social emotional learning program using four distinct taxonomies.
  • To assess the coverage (ability to classify adaptations) and clarity (inter-rater agreement on classifications) of each taxonomy.
  • To identify tensions between taxonomy coverage and clarity.

Main Methods:

  • Utilized teacher-reported adaptation descriptions from the implementation of the TOOLBOX™ social emotional learning program across 11 elementary schools.
  • Four raters applied four published taxonomies (Ecological Validity Framework, Hybrid Prevention Program Model, Moore et al., Stirman et al.) to classify 98 adaptation descriptions.
  • Assessed inter-rater reliability for coverage and clarity of classifications for each taxonomy.

Main Results:

  • Significant variance was observed among the four taxonomies in their ability to classify intervention adaptations.
  • Tensions emerged between the coverage of a taxonomy (classifying more adaptations) and its clarity (achieving higher inter-rater agreement).
  • No single taxonomy demonstrated optimal performance across both coverage and clarity metrics.

Conclusions:

  • The study highlights the challenges in consistently assessing intervention adaptations using existing taxonomies.
  • Further refinement and validation of adaptation taxonomies are needed to improve their utility as coding instruments.
  • Improved taxonomies will enable more reliable assessment of adaptations and their effects on preventive intervention outcomes.