Dyadic Associations Between Division of Household Labor and Marital Satisfaction Among Chinese Married Couples
Authors
Jiaxin Zhou1, 2, Yuan Chang1, Zhiyan Chen1, *
1CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
2Department of Psychology, University of Chinese Academy of Sciences, Chaoyang District, Beijing, 100101, China
*Corresponding author.
Email: chenzy@psych.ac.cn
Corresponding Author
Zhiyan Chen
Available Online 13 November 2024.
- DOI
- 10.2991/978-94-6463-562-1_12How to use a DOI?
- Keywords
- Numerical analysis; Mathematical models; Big Data analysis; Game theory; Psychology
- Abstract
In the study with a sample of heterosexual couples living in China (N = 409), husbands and wives reported their division of household labor (i.e., domestic chores contribution rate and household economy contribution rate) and marital satisfaction. The results indicated a partial gender effect within the division of household labor and marital satisfaction. There is a gender effect on household economic contribution rate, but not on domestic chores contribution rate. These findings result in the comprehension of the impact of a partner’s division of household labor on marital satisfaction within Chinese married couples.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jiaxin Zhou AU - Yuan Chang AU - Zhiyan Chen PY - 2024 DA - 2024/11/13 TI - Dyadic Associations Between Division of Household Labor and Marital Satisfaction Among Chinese Married Couples BT - Proceedings of the 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024) PB - Atlantis Press SP - 122 EP - 128 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-562-1_12 DO - 10.2991/978-94-6463-562-1_12 ID - Zhou2024 ER -