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dc.creatorDaley, Dyann
dc.creatorBachmann, Michael
dc.date.accessioned2017-07-03T16:19:33Z
dc.date.available2017-07-03T16:19:33Z
dc.date.issued2016-12-01
dc.identifier.urihttps://doi.org/10.1016/j.chiabu.2016.09.014
dc.identifier.urihttps://repository.tcu.edu/handle/116099117/19954
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0145213416301922
dc.description.abstractAs indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.
dc.language.isoenen_US
dc.publisherElsevier
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceChild Abuse and Neglect
dc.subjectRisk terrain modeling
dc.subjectGeospatial
dc.subjectPredictive analytics
dc.subjectChild maltreatment
dc.subjectPrevention
dc.subjectRisk factors
dc.titleRisk terrain modeling predicts child maltreatment
dc.typeArticle
dc.rights.holder2016 Daley et al
dc.rights.licenseCC BY-NC-ND 4.0
local.collegeAddRan College of Liberal Arts
local.departmentCriminal Justice
local.personsBachmann (CRJU)


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