LEADER 04415oam 2200493I 450 001 9910705717003321 005 20240408222538.0 035 $a(CKB)5470000002453240 035 $a(OCoLC)990778556 035 $a(EXLCZ)995470000002453240 100 $a20170622j201705 ua 0 101 0 $aeng 135 $aurnn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExploring elder financial exploitation victimization $eidentifying unique risk profiles and factors to enhance detection, prevention and intervention /$fJason Burnett [and three others] 210 1$a[Washington, D.C.] :$cNational Criminal Justice Reference Service, Office of Justice Programs,$d[May 2017]. 215 $a1 online resource (65 unnumbered pages) $cillustrations 300 $a"Document Number: 250756" -- Grant transmittal document. 300 $a"Date Received: May 2017" -- Grant transmittal document. 320 $aIncludes bibliographical references. 330 3 $aStatement of Purpose: Explore risk factors across the socioecological framework (i.e. individual, perpetrator and community-levels) to identify the most important factors that differentiate elder financial exploitation (FE) from other forms of abuse as well as pure FE from hybrid FE. Description of Research Subjects: Older adults 65 years and older with a confirmed case of abuse (i.e. financial exploitation, caregiver neglect, physical abuse, emotional abuse) by Texas Adult Protective Services between the years 2009-2014.^Methods: Secondary data analysis of a 5-year statewide aggregated cohort of Texas Adult Protective Services confirmed cases of abuse between the years 2009-2014.^Case investigation data such as demographics, reported and confirmed abuse types, victim and perpetrator mental and physical health, substance use, social and financial factors along with community-level data (Geographic Information Systems) were analyzed.^Supervised Learning, which provides a step-by-step statistical decision-making process was used to identify the most reliable, interpretive and predictive risk factor models. Training and test sampling was included for replication purposes. Results: Financially-based variables are the best predictors of FE versus other forms of abuse, but apparent injury appears to be the most important indicator of other forms of abuse even in the presence of FE.^Hybrid FE may be strongly related to poorer outcomes compared to pure FE however, the most predictive model found negative effects of others, alcohol and substance use by others as well as foreclosure and inadequate medical supplies to be the most important predictors of hybrid FE.^Models that accounted for less linearity between the variables resulted in greater accuracy in group classification indicating the need to account for complex interactions across the socioecological context.^Conclusion: Different factors across the socioecological context are needed to reliably differentiate between elder FE and other forms of abuse as well as pure versus hybrid FE. These factors will also vary depending on the perspective one takes regarding the linearity of the interactions between the different factors.^The findings provide support for the need to differentiate between types of abuse and subtypes of elder FE and the need for frontline workers and social service agencies and researchers to account for variables across the socioecological context when developing surveillance, intervention and prevention programs. 517 $aExploring elder financial exploitation victimization 606 $aOlder people$xAbuse of$zTexas$vCase studies 606 $aOlder people$xCrimes against$zTexas 606 $aSwindlers and swindling$zTexas$xPrevention 606 $aAbused older people$zTexas$vCase studies 606 $aFraud$zTexas$vCase studies 615 0$aOlder people$xAbuse of 615 0$aOlder people$xCrimes against 615 0$aSwindlers and swindling$xPrevention. 615 0$aAbused older people 615 0$aFraud 700 $aBurnett$b Jason$g(Jason L.),$01733832 712 02$aNational Criminal Justice Reference Service (U.S.), 801 0$bZCY 801 1$bZCY 801 2$bSTF 801 2$bGPO 906 $aBOOK 912 $a9910705717003321 996 $aExploring elder financial exploitation victimization$94149742 997 $aUNINA