Assessment of Media Influence on Youth Participation in Self-Help Community Development Project in Jalingo Metropolis

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Abstract

Youth participation is essential to the sustainability of self-help community development initiatives, yet the extent to which media coverage facilitates such engagement remains insufficiently understood in Jalingo Metropolis, Taraba State, Nigeria. This study examines the influence of media coverage on youth awareness, motivation, and participation in grassroots community development projects. Anchored in Participatory Development Theory and Agenda-Setting Theory, the study employed a survey research design. A sample of 399 respondents was determined using the Taro Yamane formula, of whom 381 provided valid responses for analysis. The findings indicate that exposure to radio, television, newspapers, and social media significantly enhances youths’ awareness of, perceived relevance of, and motivation to participate in self-help community development initiatives. Social media emerged as the most influential platform because of its interactive features and youth-oriented content formats. The results further show that consistent media messaging and success narratives strengthen sustained youth engagement across different phases of community development projects. However, inconsistent messaging and limited development-focused programming constrain the capacity of the media to promote optimal participation. The study concludes that strategic and coordinated multi-platform media engagement is critical to strengthening youth involvement in community-driven development. It contributes to development communication scholarship by demonstrating how media exposure and message consistency shape grassroots participation and recommends stronger collaboration between media institutions and development stakeholders.

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Article Details

How to Cite
Siman, L., & Dorcas, A. S. (2026). Assessment of Media Influence on Youth Participation in Self-Help Community Development Project in Jalingo Metropolis. African Multidisciplinary Journal of Sciences and Artificial Intelligence, 3(3), 355-374. https://doi.org/10.58578/amjsai.v3i3.11643

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