Eitle, D., & Eitle, T. M. (2016). General strain theory and delinquency: Extending a popular explanation to American Indian youth. Youth & Society, 48(4), 470-495.

Abstract

According to several indicators, American Indians (AIs) have among the highest rates of crime and delinquency of any racial/ethnic group in America (Pridemore, 2004; Greenfield & Smith, 1999). AIs have a violent crime rate that is 2.5 times greater than the national average (Greenfield & Smith, 1999) and their rate of violent crime victimization is more than twice the national average (Perry, 2004). AI women are at greater risk of rape and sexual assault than the average American (Perry, 2004) and studies have found that AIs are at a heightened risk of physical and sexual assault victimization (Tjaden & Thoennes, 2000; Malcoe, Duran, & Montgomery, 2004; Yuan, Koss, Polacca, & Goldman, 2006; Beals, Klein, & Croy, 2005). Self-report studies suggest that AI teens are also disproportionately involved in delinquency (e.g., McNulty & Bellair, 2003). Indeed, AIs comprise approximately sixty percent of the young prisoners in the federal system (U.S. Department of Justice, 2006).

Despite this evidence, there has been a dearth of studies that have attempted to explain AI delinquency (Morris & Wood, 2010), with most examining only substance use (e.g., Plunkett & Mitchell, 2000; Beauvais, 1996; Oetting et al., 1988; Oetting et al., 1989). Among the studies that have attempted to explain AI substance use, many have focused on the loss of Native traditionalism (Morris & Wood 2010; Herring, 1994), despite mixed evidence that traditionalism plays a meaningful role in explaining AI substance use. As noted by Morris and Wood, “Criminology has long neglected indigenous minorities” (2010, p. 248).

This study serves to further attend to this neglected topic. Using a sub-sample of AIs from a nationally representative sample of American high school students, we explore whether Agnew’s (1992) General Strain Theory (GST) can adequately explain AI self-reported delinquent acts. Our study represents the first systematic examination of GST extended to an AI sample.