Using Latent Class Analysis to Identify Profiles of Elder Abuse Perpetrators

Marguerite Deliema, Jeanine Yonashiro-Cho, Zach D. Gassoumis, Yongjie Yon, Ken J. Conrad

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


Objectives Research suggests that abuser risk factors differ across elder mistreatment types, but abuse interventions are not individualized. To move away from assumptions of perpetrator homogeneity and to inform intervention approaches, this study classifies abusers into subtypes according to their behavior profiles. Method Data are from the Older Adult Mistreatment Assessment administered to victims by Adult Protective Service (APS) in Illinois. Latent class analysis was used to categorize abusers (N = 336) using victim and caseworker reports on abusers' harmful and supportive behaviors and characteristics. Multinomial logistic regression was then used to determine which abuser profiles are associated with 4 types of mistreatment - neglect, physical, emotional, and financial - and other sociodemographic characteristics. Results Abusers fall into 4 profiles descriptively labeled "Caregiver," "Temperamental," "Dependent Caregiver," and "Dangerous." Dangerous abusers have the highest levels of aggression, financial dependency, substance abuse, and irresponsibility. Caregivers are lowest in harmful characteristics and highest in providing emotional and instrumental support to victims. The 4 profiles significantly differ in the average age and gender of the abuser, the relationship to victims, and types of mistreatment committed. Discussion This is the first quantitative study to identify and characterize abuser subtypes. Tailored interventions are needed to reduce problem behaviors and enhance strengths specific to each abuser profile.

Original languageEnglish (US)
Pages (from-to)e49-e58
JournalJournals of Gerontology - Series B Psychological Sciences and Social Sciences
Issue number5
StatePublished - Jun 14 2018
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by the National Institute on Aging (grant number T32AG000037); development and testing of the Elder Abuse Decision Support System was supported by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice (grant number 2011-IJ-CX-0014).

Publisher Copyright:
© The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail:


  • Abuse intervention
  • Abuser
  • Elder mistreatment
  • Stress and burden
  • Typology


Dive into the research topics of 'Using Latent Class Analysis to Identify Profiles of Elder Abuse Perpetrators'. Together they form a unique fingerprint.

Cite this