Pathways to care: Narratives of American Indian adolescents entering substance abuse treatment

Abstract

Using data from 89 American Indian adolescents and guided by the Network Episode Model, this paper analyses pathways to residential substance abuse treatment and their correlates. These adolescents were recruited at admission to a tribally-operated substance abuse treatment program in the southern United States from October 1998 to May 2001. Results from the qualitative analyses of these adolescent's pathways to care narratives indicated that 35% ultimately agreed with the decision for their entry into treatment; 41% were Compelled to enter treatment by others, usually by their parents, parole officers, and judges; and 24% did not describe a clear pathway to care. In the multinomial logistic regression model examining correlates of these pathways to care classifications, adolescents who described pathways indicative of agreement also reported greater readiness for treatment than the adolescents who described compelled or no clear pathways to care. Adolescents who described a Compelled pathway were less likely to meet diagnostic criteria for Conduct Disorder and described fewer social network ties. We were unable to find a relationship between pathways classifications and referral source, suggesting these narratives were subjective constructions of pathways to care rather than a factual representation of this process. In the final logistic regression model examining correlates of treatment completion, articulating a pathway to care, whether it was one of agreement or of being compelled into treatment, predicted a greater likelihood of completing treatment. Overall, these narratives and their correlates are highly consistent with the Network-Episode Model's emphasis on the interaction of self, situation, and social network in shaping the treatment seeking process, demonstrating the applicability of this model to understanding the treatment seeking process in this special population and suggests important considerations for understanding the dynamics of service utilization across diverse communities.