This article presents a theoretical framework for the study of social and behavioral factors associated with elder self-neglect. The model presented reflects the authors' beliefs that a risk-vulnerability model offers a useful framework from which to study all forms of elder mistreatment, as well as elder self-neglect. This model has particular utility, because it can begin to define the elements of risk and vulnerability that may be addressed using preventative measures as opposed to solely addressing intervention, which is often the case when addressing elder mistreatment and self-neglect. The authors then address a method for using the Consortium for Research in Elder Self-neglect of Texas data as currently constructed and adding to that database to effectively study risks and vulnerabilities in the elder self-neglect population. These additional data would greatly expand the scope of the study. The discussant adds his perspective to the ideas proposed by the authors.

Download full-text PDF

Source
http://dx.doi.org/10.1111/j.1532-5415.2008.01980.xDOI Listing

Publication Analysis

Top Keywords

elder self-neglect
20
framework study
8
self-neglect model
8
elder mistreatment
8
elder
7
self-neglect
5
self-neglect discussion
4
discussion social
4
social typology
4
typology article
4

Similar Publications

The prevalence of self-neglect among older adults: A systematic review and meta-analysis.

Int J Nurs Knowl

January 2025

The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Purpose: To quantitatively pool the overall prevalence of self-neglect in older adults and provide evidence-based information for healthcare professionals to develop preventive measures.

Methods: Systematically and thoroughly searched ten databases from inception to September 1, 2024 and we pooled the prevalence of self-neglect in older adults using a random-effects model based on the Stata 15.0 software.

View Article and Find Full Text PDF

Purpose: To report the prevalence and risk factors of elder self-neglect (ESN) among community-dwelling older adults ( = 604).

Method: The current cross-sectional study was conducted from July 2019 to October 2020 in Lanzhou City, China. ESN was determined by the Scale of Elderly Self-Neglect, which evaluates five dimensions: (a) medical health and care, (b) environmental sanitation and personal hygiene, (c) mental health, (d) safety, and (e) social engagement.

View Article and Find Full Text PDF

Background: Self-neglect is a serious public health problem affecting older people. This study was conducted to determine the prevalence of self-neglect and related factors in the elderly, which has become more important with the increase in the elderly population.

Methods: The cross-sectional study included individuals aged 65 years and over.

View Article and Find Full Text PDF

This study was conducted to examine the relationship between self-neglect and spiritual well-being in older adults. This descriptive, cross-sectional and correlational study was conducted with 232 older adults. Data were collected using the "Elder Self-Neglect Scale (ESNS)" and "Spiritual Well-Being Scale (FACIT Sp-12).

View Article and Find Full Text PDF
Article Synopsis
  • This systematic review investigated how different types of elder abuse—neglect, physical abuse, and financial abuse—affect the mental health of older adults in the U.S. and identified gaps in existing research.
  • A total of 23 relevant studies were analyzed, revealing that physical abuse is linked to higher risks of depression and anxiety, while financial abuse contributes to emotional distress and social isolation, and neglect is associated with loneliness.
  • The review highlighted the need for more longitudinal studies to understand causal relationships better, and recommended effective prevention strategies like caregiver support and financial education to protect the mental health of older adults.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!