Evidence map›Paper›PMID 37139227›Full record

ArticleFrontiers in sociology2023

Domestic violence victimization among Chinese women and its relevance to their economic power.

Zixuan Wang, Takashi Sekiyama

Abstract read
In one paragraph

Article in Frontiers in sociology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Zixuan WangGraduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan.
Takashi SekiyamaGraduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study conducted a survey of domestic violence victimization among women in China. Previously little research has been conducted on the subject of domestic violence against Chinese women as well as its relevance to their own economic power. Methods: Using online questionnaires, this study collected data about 412 women with current or previous marital status who came from four income brackets in Beijing and Shanghai. Results: It revealed that the proportions of physical, emotional, economic, and sexual violence they experienced were about 27.91%, 62.38%, 21.12%, and 30.10%, respectively. Women belonging to the highest income bracket faced almost the same risk of domestic violence compared with other income groups. Furthermore, there was a slight upward tendency in physical and emotional violence victimization in the highest-income group. The binary logistic regression analysis showed that adverse childhood experiences, arguments between couples due to different opinions regarding gender ideologies, and the approval level for specific gender ideologies were common significant factors across different income brackets. When all income brackets were considered, a higher income was tested as a protective factor with regard to sexual violence. As for the income gap between couples, women whose incomes were "once higher than that of the husband but now lower/almost the same" or "always higher than that of the husband" faced a higher risk of physical violence than women whose incomes were "always lower than/almost the same as that of the husband." Discussion: This study not only revealed the reality of domestic violence victimization in China but also suggested that more attention should be paid to high-income women's domestic violence victimization as well as the importance of helping them both through academia and domestic violence support institutions.

Indexed as

Chinadomestic violenceincome levelinfluencing factorswomen

Identifiers

PMID37139227
PMCPMC10149660

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.