Predicting childhood sexual or physical abuse: a logistic regression geo-mapping approach to prevention.
This study investigates the degree to which gender, ethnicity, relationship to perpetrator, and geomapped socio-economic factors significantly predict the incidence of childhood sexual abuse, physical abuse and non- abuse. These variables are then linked to geographic identifiers using geographic information system (GIS) technology to develop a geo-mapping framework for child sexual and physical abuse prevention.
Tadoum
Roland K
RK
University of Texas at Houston - School of Health Information Sciences, USA.
Smolij
Kamila
K
Lyn
Michelle A
MA
Johnson
Craig W
CW
D002648:Child; D002649:Child Abuse / Q000208:ethnology / Q000517:prevention & control*; D002650:Child Abuse, Sexual / Q000517:prevention & control; D005191:Family Characteristics; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D016015:Logistic Models; D008297:Male; D012189:Retrospective Studies; D012307:Risk Factors; D014481:United States