Methods: Social network surveys were completed by 9th and 10th graders (N = 263) at three high schools on a Northern Plains reservation. Social network measures were adapted for reservation-based AI youth. Following an explanatory sequential mixed methods design, qualitative interviews were conducted with a subsample of participants (n = 16) to interpret findings from their individual and school networks. Participants for the qualitative interviews were randomly selected after stratifying by gender and risk levels for substance use, violence, and suicidality.
Results: Dominant theories suggest network formation and maintenance tied to racial homophily, but in our study 93% of networks were Native and tie formation was not significantly related to race. Youth nominated more family members than what has been found among non-Native adolescents. Students demonstrated similar in-degree centrality, a measure of how many times an individual was nominated by someone in their school network. And school networks varied by size and density. We observed a direct association between the number of peers in a student's social network who use alcohol, tobacco, or marijuana and the likelihood of the student engaging in such activities. Conversely, a higher number of individuals in a student's network who discourage substance use correlated with a lower likelihood of the student engaging in such activities. Notably, marijuana exhibited the most robust influence on the likelihood of substance use. Results suggest that having a higher proportion of family in a youth’s network was a protective factor against suicide ideation. For some, having a higher proportion of family members or more school-based peers in a network was protective against exposure to violence.
Implications: Variation in networks across schools suggests unique community contexts that may make a universal approach to prevention development and implementation less effective. Findings also suggest that ways of defining family relations varied across students. This has implications for future measurement of family networks with this population. And finally, similar in-degree within networks suggests that prevailing key opinion leader social network interventions may not work in this population. Historical and environmental factors contribute to health inequities in this population, but an aggravating factor is the lack of prevention strategies that leverage contextual and cultural strengths of AI communities to optimize effectiveness and sustainability. This presentation aligns with the conference theme by centering Indigenous communities within an innovative mixed methods social network study and implications for prevention programming to promote health equity with this population.