Risk factors for elder abuse severity: findings from the Canadian longitudinal study on aging.
Academic Article
Overview
abstract
BACKGROUND AND OBJECTIVES: Elder abuse (EA) conceptualizations are evolving from conventional binary understandings toward a severity lens that more accurately captures the spectrum of victim experiences and complexity of EA intervention. Although momentum behind a focus on severity has grown, our understanding of EA severity risk factors is methodologically limited by studies using clinical convenience samples and/or cross-sectional designs. Informed by the Contextual Theory of Elder Abuse, this article sought to advance the state of science surrounding EA severity risk factors using data from a longitudinal, population-based design and examining factors from several levels of ecological influence. RESEARCH DESIGN AND METHODS: Using the Canadian Longitudinal Study on Aging, this study analyzed a sample of EA victims (n = 2,364) reporting past-year emotional/psychological, physical, and/or financial abuse, who completed baseline and follow-up waves of data collection. EA victimization was assessed using validated tools and behaviorally defined items describing specific mistreatment behaviors. Calculation of EA severity for each subtype combined dimensions of behavioral multiplicity (number of mistreatment behaviors) and frequency. Independent change variables were used to confirm the direction of change underlying potential risk factors prior to EA victimization. Multinomial logistic regression was used to identify factors associated with increased levels of EA severity. RESULTS: Across subtypes, the most consistent risk factors for heightened EA severity were perpetrator cohabitation and the older adult's experience of child maltreatment. Other risk factors were identified across physical, psycho-emotional, social, and sociocultural domains. Risk profiles varied across mistreatment subtypes. DISCUSSION AND IMPLICATIONS: This study represents the most methodologically rigorous examination of EA severity risk conducted to date. Findings will enhance our capacity to identify EA victims in particularly harmful scenarios and inform mechanistically driven interventions designed to reduce the magnitude of the problem, as well as practice decisions related to case prioritization, triaging, and risk assessment.
