Abstract: Delinquency, School Context, and Risk Factors in Mumbai, India, Victoria, Australia, and Washington State, United States: Implications for Cross-National Prevention (Society for Prevention Research 27th Annual Meeting)

416 Delinquency, School Context, and Risk Factors in Mumbai, India, Victoria, Australia, and Washington State, United States: Implications for Cross-National Prevention

Schedule:
Thursday, May 30, 2019
Pacific B/C (Hyatt Regency San Francisco)
* noted as presenting author
Michael J. Parks, PhD, Research Scientist, Minnesota Department of Health, Saint Paul, MN
Introduction: There is a dearth of research on delinquency and risk factors across developed and developing nations. There is also limited research that focuses particularly on how school context relates to problem behaviors across nations. Guided by assumptions from social disorganization theory and other prevention models, we examined how school context and risk factors relate to delinquency across three nations.

Methods: Using representative samples and matched surveys, we examined delinquency among cohorts of 7th- and 9th-grade students in Mumbai, India (N = 3,717); Victoria, Australia (N = 1,842); and Washington State (WA), United States (N = 1,828). We examined delinquency and risk factors via descriptive analyses and ANOVAs, consisting of all three cities combined into a single dataset. We also used multivariate Poisson hierarchical linear modeling to assess (1) clustering of problem behaviors within schools, and (2) the relationships between risk factors and delinquency (at both individual and school levels) within each country.

Results: Risk factor and delinquency levels varied across sites. Mean scores on delinquent behavior were lower in Mumbai compared to Melbourne and Seattle. Delinquent behavior clustered within certain schools, particularly in Mumbai. Community disorganization exhibited a strong association with delinquent behavior as a school-level context effect in Mumbai and Melbourne (event rate ratio [ERR]: 7.92, 95% CI = 3.55, 17.66; ERR = 3.42, 95% CI = 1.41, 8.29, respectively). Other risk factors, such as peer delinquency, low school commitment, and poor family management exhibited cross-nationally consistent associations with delinquency. The relationships between these risk factors and delinquency significantly varied across schools in all locations.

Conclusions: Programs that target schools, the clustering of problem behaviors, and cross-nationally consistent risk factors should be considered internationally. School contexts, and particularly the contextual factor of community disorganization, relate to delinquency across all three sites included in the current study. Mumbai had the highest level of community disorganization, which related to delinquency as a context effect and an individual-level risk factor. Targeted programs that carefully assess different schools could address the impact of community disorganization and pronounced clustering of problem behaviors in Mumbai. That is, even if delinquency is generally lower in Mumbai, there are certain areas that have elevated levels of delinquency and risk factors associated with delinquency. In sum, findings suggests that a targeted prevention approach would be optimal in Mumbai, whereas more universal strategies would be more appropriate in Washington State and Victoria.