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Reducing Intersecting Stigmas in HIV Service Organizations: An Implementation Science Model.

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This study adapted implementation science (IS) to create a logic model for reducing HIV stigma in New York City organizations. The model offers tools to systematically plan and evaluate stigma reduction efforts.

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Area of Science:

  • Implementation Science
  • Public Health
  • HIV/AIDS Research

Background:

  • HIV-related and intersectional stigmas are significant barriers to service delivery.
  • Best practices for stigma reduction are emerging, especially in high-burden areas like New York City (NYC).
  • The STAR (Stigma Reduction and Resilience) project highlighted a need for a structured implementation science (IS) framework in HIV organizations.

Purpose of the Study:

  • To adapt implementation science (IS) principles and frameworks for stigma reduction within HIV organizations.
  • To develop a structured approach for addressing gaps in HIV stigma reduction efforts.
  • To empower HIV organizations to utilize IS for implementing effective stigma reduction strategies.

Main Methods:

  • An interagency team adapted the Implementation Research Logic Model.
  • IS concepts were defined and frameworks were adapted for stigma reduction.
  • Tools were developed to guide the application of IS in HIV organizations.

Main Results:

  • A Stigma Reduction Logic Model was created, incorporating questions, definitions, and tips.
  • The model includes tools for synthesizing IS components: interventions, determinants, strategies, mechanisms, and outcomes.
  • Features include a menu of stigma reduction options, an organizational readiness checklist, and an IS terminology guide.

Conclusions:

  • The Stigma Reduction Logic Model provides a methodology for planning, implementing, and evaluating stigma reduction activities.
  • It enables implementers, researchers, and stakeholders to build consensus and systematically address HIV stigma.
  • Future research will focus on testing the model's utility in practice.