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Updated: May 24, 2025

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
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Understanding Who Benefits the Most from Interventions: Implications for Baseline Target Moderated Mediation Analysis

Matthew J Valente1, Jinyong Pang2, Biwei Cao2

  • 1Department of Biostatistics and Data Science, University of South Florida, 13201 Bruce B. Downs Blvd., MDC 56, Tampa, FL, 33612, USA. mjvalente@usf.edu.

Prevention Science : the Official Journal of the Society for Prevention Research
|March 4, 2025
PubMed
Summary

Baseline Target Moderated Mediation (BTMM) helps understand intervention effectiveness by examining how and for whom it works. This study addresses challenges in identifying subgroups benefiting most from interventions using multiple moderators.

Keywords:
Baseline Target Moderated MediationModerated mediationTreatment-mediator interaction

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Area of Science:

  • Prevention Science
  • Biostatistics
  • Psychology

Background:

  • Baseline Target Moderated Mediation (BTMM) is gaining traction in prevention science.
  • BTMM investigates intervention effects, detailing how and for whom interventions are most effective.
  • Challenges exist in incorporating multiple moderators and interpreting subgroup effects within BTMM.

Purpose of the Study:

  • To describe methodological challenges and interpretation of mediation effects with multiple moderators.
  • To present two statistical methods for estimating conditional mediation effects with multiple moderators.
  • To apply these methods to an empirical example from the ATLAS study and discuss implications for BTMM.

Main Methods:

  • Description of methodological challenges in BTMM with multiple moderators.
  • Introduction of two statistical methods for estimating conditional mediation effects.
  • Application of methods to the ATLAS study data.

Main Results:

  • The study outlines challenges in identifying intervention subgroups using multiple moderators.
  • Two statistical methods are presented to address these challenges.
  • The methods are demonstrated using the ATLAS study, providing empirical insights.

Conclusions:

  • Addressing multiple moderators and treatment-by-mediator interactions is crucial for BTMM.
  • The proposed methods offer a way to assess BTMM with complex interactions.
  • This work advances the understanding and application of BTMM in prevention science.