Leveraging AI in Community-Based Participatory Research: Strengthening the Research-Education-Outcome Connection through Community Involvement and Actionable Solutions

Document Type

Conference Proceeding

Publication Date

4-14-2025

Publication Title

West J Nurs Res

Keywords

Nursing

Abstract

Background: Community-Based Participatory Research (CBPR) promotes equitable collaboration between researchers and communities, addressing local priorities while fostering shared decision-making. Integrating artificial intelligence (AI) into CBPR has the potential to enhance research efficiency, community engagement, and the development of actionable solutions. This proposed study explores how AI-enabled CBPR strengthens the connection between research, education, and outcomes through active community involvement. Theoretical/conceptual framework utilized to form the basis of the study include Black Feminist Thought and Roy’s Adaptation Model. Methods: Using a CBPR approach, a multidisciplinary team, including nurse scientists, community members and AI specialists, co-designed and will implement the study. Workshops identified community priorities surrounding stress, coping and its effects on mental health in African American women, while AI tools facilitated data collection, thematic analysis, and predictive modeling. Community members received training to build AI literacy and contribute to decision-making processes. Outcomes will be assessed through pre- and post-intervention surveys and focus groups. Results: AI integration will improve efficiency in prioritizing community needs, enhance educational outcomes by empowering participants with AI knowledge, and support the development of tailored interventions addressing health disparities and resource allocation. Challenges will include addressing digital literacy gaps and ensuring ethical AI use. Conclusions: The findings will highlight AI’s transformative potential in CBPR, fostering equitable partnerships, actionable insights, and sustainable community-driven solutions.

Volume

47

Issue

1_SUPPL

First Page

57S

Last Page

58S

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