000			04336nam a2200421Ii 4500
999			_c261278 _d261278
001			ocn990778556
003			BD
005			20171113123758.0
006			m o d f
007			cr nn|||||||||
008			170622e201705 dcua obt f000 0 eng d
040			_aPUCPR _beng _erda _epn _cZCY _dSTF _dGPO _dMvI
043			_an-us-tx
049			_aOnline
074			_a0717 (online)
086	0		_aJ 1.2:EL 2/7
099			_aJ 1.2:EL 2/7
100	1		_aBurnett, Jason, _eauthor.
245	1	0	_aExploring elder financial exploitation victimization : _bidentifying unique risk profiles and factors to enhance detection, prevention and intervention / _cJason Burnett [and three others].
246	1		_iAt head of title: _aNational Institute of Justice final technical report
264		1	_a[Washington, D.C.] : _bNational Criminal Justice Reference Service, Office of Justice Programs, _c[May 2017]
300			_a1 online resource ([65] pages) : _billustrations
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_a"Document Number: 250756" -- Grant transmittal document.
500			_a"Date Received: May 2017" -- Grant transmittal document.
500			_aCRDP Program record.
504			_aIncludes bibliographical references.
520	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.
536			_c2013-IJ-CX-0050
588	0		_aDescription based on online resource ; title from PDF (NCJRS, viewed on June 22, 2017).
650		0	_aOlder people _xAbuse of _zTexas _vCase studies.
650		0	_aOlder people _xCrimes against _zTexas.
650		0	_aSwindlers and swindling _zTexas _xPrevention.
650		0	_aAbused elderly _zTexas _vCase studies.
650		0	_aFraud _zTexas _vCase studies.
710	2		_aNational Criminal Justice Reference Service (U.S.), _eissuing body.
856	4	0	_uhttp://purl.fdlp.gov/GPO/gpo81669
942			_2sudocs _c8