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Ko: Predictors of Intention to Report Elder Abuse among Elderly Women
Original Article
Korean Journal of Women Health Nursing

Korean Journal of Women Health Nursing 2010; 16(3): 245-254.

Published online: 30 September 2010

DOI: https://doi.org/10.4069/kjwhn.2010.16.3.245

Predictors of Intention to Report Elder Abuse among Elderly Women

Chung Mee Ko

1Associate Professor, College of Nursing, Sungshin Women's University, Korea.

Address reprint requests to: Ko, Chung Mee, College of Nursing, Sungshin Women's University, 249-1 Dongsun-dong 3-ga, Seongbuk-gu, Seoul 136-742, Korea. Tel: 82-2-920-7725, Fax: 82-2-920-2091, cmklee@sungshin.ac.kr

Received 31 July 2010       Accepted 20 August 2010

Copyright © 2010 Korean Academy of Women's Health Nursing

Abstract

Purpose

This study was designed to identify the predictors of elderly women's intention to report elder abuse.

Methods

A cross-sectional survey design was used. The participants were 204 elderly women aged over 60 living in Seoul. Data were collected using self-reported questionnaires by convenience sampling. Data were analyzed with frequencies, χ2 test, t-test and binary logistic regression.

Results

Logistic regression analyses showed perception of elderly welfare law, perception of seriousness of elder abuse, subjective economic status, and exposure to elder abuse information were significant predictors of elderly women's intention to report elder abuse.

Conclusion

The results of study suggest that the provision of information related to elder abuse including elderly welfare law is crucial toward elderly women in preventing elder abuse.

Keywords: Elder abuse, Report, Intention, Elderly, Women

Figures and Tables

Table 1
Frequency of Intention to Report (N=204)
kjwhn-16-245-i001
Table 2
Differences in Intention to Report by Sociodemographic Characteristics of Participants (N=204)
kjwhn-16-245-i002

Note. % of valid n for each variable(missing excluded).

Table 3
Differences in Intention to Report by Elder Abuse-related Characteristics (N=204)
kjwhn-16-245-i003

Note. % of valid n for each variable(missing excluded).

Table 4
Predictive Factors of Intention to Report by Logistic Regression
kjwhn-16-245-i004

CI=confidence interval.

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