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Virginia Tech

Gender and the Subjective Well-being of Widowed Elders

Abstract

dc:description.abstract

Many studies suggest that aging women have unique experiences in widowhood, which are different from those of aging men because of gender inequality. This study explored the 2014 Health and Retirement Study (HRS) to discover whether gender influences the factors that affect subjective well-being of elderly widows and widowers (aged 65 and over). To look at subjective well-being, I used a feminist gerontological approach to explore possible gender differences and examined life satisfaction, a life satisfaction scale, and happiness, their corresponding predictive factors, and their importance for each of the measures of subjective well-being. This study found that there were gender differences in total household income and social support from friends. Although gender did not affect subjective well-being directly, there were gender differences in the ways that education, total household income, total wealth, and social support from children and friends affected the subjective well-being of widows and widowers.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Sociology
Department dc:contributor.department
Sociology
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Geng, Jing
Chair dc:contributor.committeechair
  • Calasanti, Toni M.
Committee members dc:contributor.committeemember
  • Kiecolt, K. Jill
  • Zhu, Haiyan

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:21335
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/101093

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Geng, Jing. Gender and the Subjective Well-being of Widowed Elders. masters thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/101093