Examination of National Crime and Gang Prevention Programs Using the Clegu and Lemas Datasets

Introduction: Community-related efforts to prevent crime and gang activity include police-led programming. Previous research has indicated a lack of gang-related prevention efforts at the police level, yet a gap remains as to the clustering of prevention efforts and that relationship to various crime types on a national level. This study seeks to answer two research questions: How is crime and gang prevention categorized according to police-led efforts, and how are crime prevention categories distributed according to crime type and community locality?

Methods: Two datasets were case-matched and utilized (N = 405): The 2007 Census for Law Enforcement Gang Units (CLEGU) and the 2007 Law Enforcement Administrative Management Statistics (LEMAS). Latent Class Analysis was performed on eight gang prevention variables from the CLEGU dataset to identify initial categories of prevention activities. Covariates from the LEMAS dataset included crime prevention activities, locality of police department, and types of crime reported from departments.

Results: The majority of departments reported few gang-related prevention activities, and only 32% reported implementation of a nationally-recommended gang prevention program (GREAT). Around 30 to 40 percent included youth in their prevention activities. LCA showed two categories of gang prevention activities, one targeting youth and one targeting other types of prevention, also separated into low and high prevention. LCA will also incorporate covariaties from the LEMAS dataset.

Conclusions: Understanding how crime prevention programs are combined with each other and incorporated may help to identify ways to maximize the benefits of police-led prevention in communities. Further data needs to examine how police and communities can combine prevention activities to prevent crime and gang activity, particularly among youth, particularly on a local level that may be disseminated in similar communities.