Delinquent youth are at risk for early violent death after release from detention. However, few studies have examined risk factors for mortality. Previous investigations studied only serious offenders (a fraction of the juvenile justice population) and provided little data on females.
The legalization of American Indian casino gaming in the late 1980s allows examination of the relationship between income and health in a quasi-experimental way. Revenue from gaming accrues to individual tribes and has been used both to supplement tribe members income and to finance tribal infrastructure. We assembled annual data from 1988-2003 on tribal gaming, health care access (from the Area Resource File), and individual health and socioeconomic characteristics data (from the Behavioral Risk Factors Surveillance System). We use this information within a structural, difference-in-differences framework to study the effect of casino gaming on tribal members income, health status, access to health care, and health-related behaviors. Our difference-in-differences framework relies on before-after comparisons among American Indians whose tribe has at some time operated a casino and with-without comparisons between American Indians whose tribe has and those whose tribe has not initiated gaming. Our results provide identified estimates of the positive effect of gaming on American Indian income and on several indicators of American Indian health, health-related behaviors, and access to health care.
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
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We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.