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When Is It Time to Revise or Adapt Our Prevention Programs? Introduction to Special Issue on Using Baseline Target

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Identifying subgroups that benefit most from prevention programs helps tailor interventions. This research uses baseline target moderated mediation (BTMM) to find effect heterogeneity and guide program adaptation for greater impact.

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Area of Science:

  • Prevention Science
  • Health Psychology
  • Intervention Research

Background:

  • Adapting preventive interventions is key to maximizing their impact.
  • Identifying subgroups or contexts with stronger/weaker program effects is crucial for successful adaptation.
  • Baseline Target Moderated Mediation (BTMM) designs offer a framework for detecting effect heterogeneity.

Purpose of the Study:

  • To introduce a special issue focused on using BTMM designs to identify effect heterogeneity in prevention programs.
  • To guide the adaptation of established prevention programs based on subgroup or contextual differences.
  • To synthesize findings from diverse prevention science sub-disciplines utilizing BTMM.

Main Methods:

  • Analysis of randomized trial data using Baseline Target Moderated Mediation (BTMM) models.
  • Evaluation of intervention impact variation across different health outcomes, developmental periods, and social units.
  • Application of BTMM to detect patterns of intervention effect heterogeneity.

Main Results:

  • The most common pattern observed was compensatory effects, where individuals with higher risk or fewer protective factors benefited most.
  • Other detected patterns included "rich-get-richer" effects and partially iatrogenic effects.
  • Evidence for intervention impact variation was found across various health outcomes, developmental stages, and social units.

Conclusions:

  • BTMM designs are effective tools for detecting effect heterogeneity in prevention science.
  • Understanding these patterns of effect is vital for informing the successful adaptation of preventive interventions.
  • Findings have significant implications for future prevention research and the design of next-generation prevention trials.