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Factors Influencing Frequency of Depressive Experiences Among Married Working Women in South Korea
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jeong, Se Hui | - |
| dc.contributor.author | Kang, Chan Mi | - |
| dc.contributor.author | Kang, Kyung Im | - |
| dc.date.accessioned | 2025-05-07T09:00:13Z | - |
| dc.date.available | 2025-05-07T09:00:13Z | - |
| dc.date.issued | 2025-03 | - |
| dc.identifier.issn | 2227-9032 | - |
| dc.identifier.issn | 2227-9032 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/78079 | - |
| dc.description.abstract | Background/Objectives: This study aimed to identify the factors influencing and predicting the frequency of depressive experiences among married working women in South Korea in the post-COVID-19 period (2022-2023). It examines how alterations in circumstances and the complex difficulties encountered by this demographic group may have shaped their depressive experiences. Through a comparative analysis of the group reporting depressive experiences and the group reporting no depressive experiences, the study delineates the factors influencing depressive experiences within the former group and the predictive factors within the latter group. The findings offer a comprehensive understanding of the factors that may contribute to mental health outcomes within this population. Methods: This study utilized data from the ninth wave (2022-2023) of the Korean Longitudinal Survey of Women and Families, conducted by the Korean Women's Development Institute. The study included a total of 1735 participants. A zero-inflated negative binomial regression model was applied to analyze the frequency of depressive experiences and the influencing and predictive factors. Results: Among the participants, 38.9% reported no depressive experiences. The count model analysis revealed that subjective health status, physical activity, thoughts about husband, family decision-making, and work-family balance were significant factors associated with the frequency of depressive experiences. In the logistic model, key predictors for those without depression included the spouse's education, physical activity, satisfaction with the spouse's housework, and happiness with marital life. Conclusions: These findings provide essential empirical evidence for the development of targeted policies and interventions aimed at mitigating and preventing depression problem among married working women. | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | MDPI AG | - |
| dc.title | Factors Influencing Frequency of Depressive Experiences Among Married Working Women in South Korea | - |
| dc.type | Article | - |
| dc.publisher.location | 스위스 | - |
| dc.identifier.doi | 10.3390/healthcare13050453 | - |
| dc.identifier.scopusid | 2-s2.0-86000490973 | - |
| dc.identifier.wosid | 001442335600001 | - |
| dc.identifier.bibliographicCitation | Healthcare, v.13, no.5 | - |
| dc.citation.title | Healthcare | - |
| dc.citation.volume | 13 | - |
| dc.citation.number | 5 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | ssci | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Health Care Sciences & Services | - |
| dc.relation.journalWebOfScienceCategory | Health Care Sciences & Services | - |
| dc.relation.journalWebOfScienceCategory | Health Policy & Services | - |
| dc.subject.keywordPlus | DECISION-MAKING POWER | - |
| dc.subject.keywordPlus | MARITAL SATISFACTION | - |
| dc.subject.keywordPlus | PHYSICAL-ACTIVITY | - |
| dc.subject.keywordPlus | SYMPTOMS | - |
| dc.subject.keywordPlus | HEALTH | - |
| dc.subject.keywordPlus | SUPPORT | - |
| dc.subject.keywordPlus | MOTHERS | - |
| dc.subject.keywordPlus | STRESS | - |
| dc.subject.keywordAuthor | depressive experiences | - |
| dc.subject.keywordAuthor | married working women | - |
| dc.subject.keywordAuthor | South Korea | - |
| dc.subject.keywordAuthor | zero-inflated negative binomial model | - |
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