Female: <12 g/dL
Meanwhile, the life course survey also recorded whether the respondents had often been bullied by other classmates during their school days. Similar to domestic violence, campus bullying can also harm the physical and mental health of minors, so it is necessary to take campus bullying as a control variable. The control variable assignment method is shown in Table 3 .
Interpreted, explanatory and control variables.
Category | Variable | Symbol | Definition | |
---|---|---|---|---|
Interpreted variables | Education | 1. Uneducated (illiterate), 2. Uneducated primary school, 3. Private school, 4. Primary school, 5. Junior high school, 6. High school, 7. Technical secondary school (including secondary normal school and vocational high school), 8. Junior college, 9. Undergraduate, 10. Master, 11. Doctor | ||
Healthy | Self-rated health: SRH Blood test index: DM Risk score: Risk Depression score: Depr | Self-rated health: 1. Very bad, 2. Bad, 3. Average, 4. Good, 5. Very good; Blood test indicators: reduce the dimension of blood test indicators through Markov distance function; Risk score: judge whether the blood test indicators are normal according to the threshold, and add up the number of abnormal indicators; Depression score: calculated using depression scale | ||
Life satisfaction | 1. Not at all satisfied, 2. Not very satisfied, 3. Quite satisfied, 4. Very satisfied, 5. Extremely satisfied | |||
Explanatory variable | Domestic violence index | The score is calculated from the four dimensions of injury from violence, negligent care, emotional abuse and witnessing domestic violence | ||
Control variable | Campus bullying | When you were young, were you bullied by other students at school? 1. Never, 2. Rarely, 3. Sometimes, 4. Often | ||
Demography Statistics variable | Age | Age of the interviewee | ||
Gender | 1: Male, 0: female | |||
Registered residence | Respondent’s first household registration: 1: non-agricultural household registration, 0: agricultural household registration | |||
Nation | 1: Han nationality, 0: others | |||
Marriage | 1: Married, 0: unmarried | |||
Region | , central, east | The economic region of the interviewee—west: west, central: central, east: east | ||
Aboriginal family Court variable | Father’s education level | Consistent with the definition of respondents’ education level | ||
Education level of mother | Consistent with the definition of respondents’ education level | |||
Father’s mental health | Has your male caregiver ever been sad or depressed for two or more consecutive weeks? 1: Yes, 0: no | |||
Mother’s mental health | Has your female caregiver ever been sad or depressed for two or more consecutive weeks? 1: Yes, 0: no | |||
Father’s health | Does your male caregiver stay in bed for a long time? 1: Yes, 0: no | |||
Mother’s health | Does your female caregiver stay in bed for a long time? 1: Yes, 0: No | |||
Number of brothers and sisters | Number of brothers and sisters in the family | |||
Does my father drink too much? | 1: Yes, 0: no | |||
Whether the father takes drugs | 1: Yes, 0: no | |||
Does my father gamble? | 1: Yes, 0: no | |||
Family economic status | Before the age of 17, compared with the ordinary families in your community/village at that time, what was your family’s economic situation? 1. A lot worse than them, 2. A little worse than them, 3. The same as them, 4. A little better than them, 5. A lot better than them | |||
Community health | 1. Not clean and tidy at all, 2. Not very clean and tidy, 3. Quite clean and tidy, 4. Very clean and tidy | |||
Family Students Live mass | Living standard | Quantity of 18 kinds of household equipment, durable consumer goods and other valuables | ||
Toilet | 1: There is a flush toilet at home, 0: no | |||
Tap water | 1: There is tap water at home, 0: no | |||
Fuel | 1: The main fuels for cooking are straw and firewood, 0: others | |||
Internet | 1: The house you live in can have broadband internet access, 0: no |
As variables are exogenous, and education level is an ordered variable, linear model is used for estimation [ 31 ]. The empirical model of educational achievement is shown in Equation (2):
where the control variables X include campus bullying, demographic variables and native family variables. The empirical model of the self-assessment of health and life satisfaction is shown in Equation (3):
where the control variables X ′ include campus bullying, demographic statistics, native family variables and variables reflecting the quality of family life. Self-rated health and life satisfaction are both subjective indicators, and there is a causal relationship between them, so they are built into a simultaneous equation model. As self-rated health and life satisfaction are ordered variables, Equation (3) is a bivariate ordered variable model. Health is further divided into two dimensions: physical health and mental health. As physical health and mental health are mutually causal, a simultaneous equation model is also used to quantify the impact of domestic violence on health:
Different from Equation (3), the indicators reflecting physical health (DM), risk scores (Risk) and depression scores (Depr) can be regarded as continuous variables, while life satisfaction is an ordered variable, so Equation (4) is a mixed structure model. In quantitative research, the ordered probit/logit model and the simple linear regression model have consistency in the direction and significance of parameter estimates, with the latter being more intuitive and convenient to explain. Therefore, many studies directly use the OLS estimation ordered choice variable model [ 32 , 33 ], so they can also directly use the seemingly unrelated regression estimator (Equations (2)–(5)).
The empirical research includes three main parts: First, the 2018 cross-sectional data are taken as the sample to quantify the impact of domestic violence on personal educational achievements. For the middle-aged and elderly aged 45 and above, the education level was finalized, and the 2018 cross-sectional data can be used as the sample to retain the observation object to the maximum extent. Second, the seemingly unrelated regression model is used to estimate the simultaneous equation of the self-assessment of health and life satisfaction. The sample data are panel data composed of 2011, 2013, 2015 and 2018 survey data. Finally, health is refined into physical health and mental health dimensions, and simultaneous equations are estimated through seemingly unrelated regression. The sample data are panel data composed of 2011 and 2015 survey data.
Equation (2) is estimated based on sample data. The estimated results are shown in Table 4 , which lists the estimated results of the OLS and ordered probit/logit models at the same time. According to the estimation results of the three types of models, at the 1% significance level, domestic violence significantly reduces individual educational achievements. Taking the OLS estimation results as an example, if one unit is added to the domestic violence index, the education level of individuals will decrease by 0.1318 levels. The interpretation of the estimated results of the ordered probit model requires the help of marginal effects. Based on the estimated results of the ordered probit model, the marginal effects of education level on the average value of the domestic violence index ∂ P ( E d u = κ ) / ∂ V ¯ can be estimated, in turn. The estimated results are shown in Figure 3 .
Marginal effect and probability ratio of education level on domestic violence index.
(1) | (2) | (3) | |
---|---|---|---|
Ordered Probit Model | Ordered Logit Model | ||
Variable | |||
−0.1318 *** | −0.0951 *** | −0.1557 *** | |
(0.0307) | (0.0212) | (0.0368) | |
−0.0099 | −0.0047 | −0.0216 | |
(0.0232) | (0.0160) | (0.0281) | |
−0.0178 *** | −0.0129 *** | −0.0250 *** | |
(0.0018) | (0.0013) | (0.0021) | |
0.6911 *** | 0.4814 *** | 0.8277 *** | |
(0.0316) | (0.0221) | (0.0386) | |
−0.9048 *** | −0.6448 *** | −1.1659 *** | |
(0.0493) | (0.0345) | (0.0617) | |
0.0938 | 0.0613 | 0.1156 | |
(0.0634) | (0.0436) | (0.0779) | |
0.2589 *** | 0.1931 *** | 0.3401 *** | |
(0.0389) | (0.0268) | (0.0467) | |
0.1881 *** | 0.1360 *** | 0.2413 *** | |
(0.0384) | (0.0264) | (0.0460) | |
0.1564 *** | 0.1075 *** | 0.1845 *** | |
(0.0156) | (0.0106) | (0.0187) | |
0.1206 *** | 0.0842 *** | 0.1457 *** | |
(0.0103) | (0.0071) | (0.0124) | |
−0.1351 ** | −0.0864 ** | −0.1531 ** | |
(0.0634) | (0.0436) | (0.0756) | |
−0.1969 *** | −0.1342 *** | −0.2421 *** | |
(0.0595) | (0.0412) | (0.0724) | |
−0.0860 * | −0.0508 | −0.1063 * | |
(0.0516) | (0.0353) | (0.0617) | |
−0.0928 * | −0.0721 ** | −0.1287 ** | |
(0.0484) | (0.0336) | (0.0577) | |
−0.0113 | −0.0050 | −0.0068 | |
(0.0088) | (0.0060) | (0.0105) | |
−0.1007 * | −0.0577 | −0.1071 | |
(0.0593) | (0.0405) | (0.0700) | |
0.0298 | −0.0391 | −0.1376 | |
(0.3549) | (0.2225) | (0.3348) | |
−0.2785 ** | −0.2048 ** | −0.4052 *** | |
(0.1314) | (0.0897) | (0.1475) | |
0.2301 *** | 0.1631 *** | 0.2854 *** | |
(0.0172) | (0.0119) | (0.0208) | |
−0.0230 | −0.0203 | −0.0303 | |
(0.0209) | (0.0144) | (0.0250) | |
Constant term | 4.6869 *** | ||
(0.1794) | |||
Observation object | 9642 | 9642 | 9642 |
0.1808 |
Note: Robust standard deviation in brackets; *** p < 0.01, ** p < 0.05, * p < 0.1; the estimated result of the tangent point value is omitted.
It can be seen from the estimation results of the marginal effect that when the domestic violence index takes the average value, the marginal effect of the probability value P ( E d u = 4 ) (being educated to graduate from primary school) on the domestic violence index is 0.0056, and for other levels of education, the marginal effect is significantly less than 0. Therefore, it can be seen that domestic violence significantly reduces educational achievements after primary school graduation.
To intuitively explain the estimation results of the ordered logit model, we can also use the generalized ordered logit model in addition to the probability ratio. The generalized ordered logit model converts the ordered logit model into several logit models, which is consistent with the above. Typical primary school graduation, junior high school graduation, senior high school graduation, technical secondary school graduation, junior college graduation and undergraduate graduation are selected as the threshold for model transformation; that is, the impact of the domestic violence index on the probability value P ( E d u ≥ k | X ) ( k = 4 , 5 , ⋯ , 9 ) is mainly examined, with the estimation results of the probability ratio shown in Figure 3 . It can be seen from the estimated results of the probability ratio that, if the domestic violence index increases by 1 unit, the probability ratio of attaining primary school graduation and above will decrease by 13.42%, the probability ratio of attaining junior high school graduation and above will decrease by 13.72% and the probability ratios of attaining high school graduation, technical secondary school graduation, junior college graduation, undergraduate graduation and above will decrease by 21.11, 16.94, 14.45 and 17.61%, respectively. According to the estimation results of the OLS estimation, the ordered probit/logit model and the generalized logit model, domestic violence significantly reduces the educational achievements of respondents.
The domestic violence index is composed of four dimensions, and the impact of each dimension on educational achievements may be inconsistent. In view of this, in the heterogeneity analysis, the domestic violence index is subdivided into four dimensions, and the corresponding estimation results are shown in Table 5 . It can be seen from the above estimation results that the OLS estimation and the coefficient estimation of the ordered probit/logit model are consistent in significance and sign, so the OLS estimation results of the linear model are used to explain the practical meaning of the model. At the 1% confidence level, among the four dimensions, only the emotional abuse dimension has a significant negative impact on educational achievement; that is, compared with the other three dimensions, emotional abuse has the most prominent negative impact on educational achievement. Specifically, if the emotional abuse index increased by 1 unit, the education level decreased by 0.0759. This is because emotional abuse will affect children’s cognitive development and impair their memory and cognitive ability to a certain extent, making them likely to encounter difficulties in learning, thus affecting their academic performance and then their education level. From another perspective, scholars have found that the level of education will adjust the impact of domestic violence on individuals, so the level of education is an important factor to consider the impact of domestic violence on individuals [ 34 ].
Results of the dimensional heterogeneity analysis.
Variable | (1) | (2) | (3) |
---|---|---|---|
Ordered Probit Model | Ordered Logit Model | ||
0.0288 | 0.0238 | 0.0506 * | |
(0.0229) | (0.0158) | (0.0277) | |
−0.0228 | −0.0159 | −0.0254 | |
(0.0178) | (0.0122) | (0.0212) | |
−0.0759 *** | −0.0565 *** | −0.0970 *** | |
(0.0162) | (0.0112) | (0.0193) | |
−0.0283 | −0.0217 | −0.0399 | |
(0.0347) | (0.0240) | (0.0419) | |
Constant term | 4.6315 *** | ||
(0.1818) | |||
Observation object | 9642 | 9642 | 9642 |
0.1819 | |||
Control variable | √ | √ | √ |
Note: Robust standard deviation in brackets; *** p < 0.01, * p < 0.1; the estimated results of control variables and tangent point values are omitted.
Similar to the above, this part also uses the linear model for empirical research. The Breusch–Pagan test shows that the residual terms of the simultaneous equations are correlated, so the seemingly uncorrelated panel model is used to estimate the simultaneous equations. The estimation results are shown in Table 6 . At the 1% confidence level, the domestic violence index has a significant negative impact on the self-assessment health level and life satisfaction. If the domestic violence index increases by 1 unit, the self-assessment health level decreases by 0.0320, and life satisfaction decreases by 0.0948. Furthermore, the domestic violence index is divided into four levels. For health self-evaluation, at the 1% confidence level, only the emotional abuse dimension has a significant negative impact on the health self-evaluation level, which increases by 1 unit, while the self-evaluation health level decreases by 0.0267. In the life satisfaction equation, at the 1 or 5% confidence level, injury from violence, negligent care, emotional abuse and witnessing domestic violence all have significant negative impacts on life satisfaction. For each increase in the index of each dimension, life satisfaction decreases by 0.0240, 0.0189, 0.0314, and 0.0216 levels, in turn. In general, domestic violence significantly reduces the self-rated health level and life satisfaction. This is because domestic violence causes great harm to the victims, directly damages the physical and mental health of the victims and causes long-term mental tension, anxiety and fear in the victims. At the same time, because domestic violence makes it difficult for victims to feel warmth from family, life satisfaction will be greatly reduced.
Estimated results of domestic violence, health and life satisfaction.
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Variable | ||||
0.5700 *** | 0.5681 *** | |||
(0.0079) | (0.0079) | |||
0.3444 *** | 0.3434 *** | |||
(0.0048) | (0.0048) | |||
−0.0320 *** | −0.0948 *** | |||
(0.0116) | (0.0090) | |||
−0.0005 | −0.0240 *** | |||
(0.0087) | (0.0067) | |||
0.0078 | −0.0189 *** | |||
(0.0066) | (0.0051) | |||
−0.0276 *** | −0.0314 *** | |||
(0.0061) | (0.0048) | |||
−0.0050 | −0.0216 ** | |||
(0.0129) | (0.0100) | |||
Constant term | 1.5371 *** | 1.6178 *** | 1.5406 *** | 1.6256 *** |
(0.0755) | (0.0582) | (0.0760) | (0.0586) | |
Sample size | 23,861 | 23,861 | 23,861 | 23,861 |
0.0903 | 0.0779 | 0.0914 | 0.0786 | |
Control variable | √ | √ | √ | √ |
Time-fixed effect | √ | √ | √ | √ |
Note: Robust standard deviation in brackets; *** p < 0.01, ** p < 0.05; the estimated results of other control variables and tangent point values are omitted.
On the basis of the above, health is further divided into physical health and mental health, characterized by biomarker indicators and depression score indicators. The corresponding estimation results are shown in Table 7 . At the 1% confidence level, the domestic violence index has a significant positive impact on depression scores; at the 5% confidence level, the domestic violence index significantly increases the abnormal frequency of blood test indicators. Specifically, in the simultaneous equation of DM and depression scores, if the domestic violence index increased by 1 unit, the depression score increased by 0.6591 points; in the simultaneous equation of the abnormal frequency of blood test index and depression scores, if the domestic violence index increased by 1 unit, the abnormal frequency of blood test index increased by 0.0532 units, and the depression score increased by 0.6617 points. Furthermore, the domestic violence index is divided into four dimensions. At the 1% confidence level, the three indexes of injury from violence, emotional abuse and witnessing domestic violence significantly improved the depression score but have no significant impact on the two health risk indicators based on blood test indicators. Therefore, on the whole, it can be determined that domestic violence increases the subjective mental health risk.
Estimated results of domestic violence and physical and mental health.
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
---|---|---|---|---|---|---|---|---|
Simultaneous Equation (1) | Simultaneous Equation (2) | Simultaneous Equation (3) | Simultaneous Equation (4) | |||||
Variable | ||||||||
0.0147 *** | 0.0063 *** | 0.0148 *** | 0.0061 ** | |||||
(0.0029) | (0.0024) | (0.0029) | (0.0024) | |||||
0.2004 *** | 0.2014 *** | |||||||
(0.0395) | (0.0395) | |||||||
0.1291 *** | 0.1252 ** | |||||||
(0.0487) | (0.0486) | |||||||
0.0400 | 0.6591 *** | 0.0532 ** | 0.6617 *** | |||||
(0.0329) | (0.1210) | (0.0267) | (0.1210) | |||||
0.0184 | 0.2255 ** | 0.0265 | 0.2264 ** | |||||
(0.0249) | (0.0918) | (0.0203) | (0.0919) | |||||
0.0240 | 0.0562 | 0.0192 | 0.0588 | |||||
(0.0186) | (0.0687) | (0.0151) | (0.0687) | |||||
−0.0018 | 0.1838 *** | −0.0031 | 0.1842 *** | |||||
(0.0174) | (0.0640) | (0.0141) | (0.0640) | |||||
−0.0054 | 0.4847 *** | 0.0428 | 0.4793 *** | |||||
(0.0366) | (0.1348) | (0.0298) | (0.1349) | |||||
Constant term | 2.6178 *** | 18.4491 *** | 0.0666 | 19.0057 *** | 2.6204 *** | 18.1320 *** | 0.0401 | 18.6963 *** |
(0.2124) | (0.7650) | (0.1726) | (0.7566) | (0.2139) | (0.7710) | (0.1738) | (0.7627) | |
Sample size | 8698 | 8698 | 8698 | 8698 | 8698 | 8698 | 8698 | 8698 |
0.0200 | 0.1255 | 0.0162 | 0.1255 | 0.0201 | 0.1267 | 0.0165 | 0.1267 | |
Control variable | √ | √ | √ | √ | √ | √ | √ | √ |
Time-fixed effect | √ | √ | √ | √ | √ | √ | √ | √ |
Calculating the domestic violence index through dimension reduction can quantify the degree of domestic violence experienced by the interviewees in general, but it will also lose some of the indicator information. In view of this, in the robustness test, directly using the secondary indicators as explanatory variables is proposed, with the estimated results shown in Table 8 . In the education decision equation, at the 1% confidence level, only the relationship with the mother has a significant negative impact on education level. In the simultaneous equation of self-rated health and life satisfaction, for self-rated health, at the 5% confidence level, only the relationship with the mother has a significant negative impact. For life satisfaction, at the 1% confidence level, whether the father has injuries from violence, whether the mother has invested enough in taking care of herself and the relationship with the father have significant negative effects. In the two simultaneous equations of health risk, seven secondary indicators have no significant impact on the health risk indicators based on blood test indicators. For subjective mental health, at the 1 or 5% confidence level, whether the mother behaved violently, the relationship with the mother and whether domestic violence was witnessed have significant positive effects on the depression score. In general, the secondary indicators in the dimension of emotional abuse have a particularly prominent impact on educational achievement, life satisfaction and mental health, which verifies the main conclusions of the empirical study.
Estimation results of the robustness test.
Variable | (1) | (2) | (3) | (4) | (5) | (6) | (7) |
---|---|---|---|---|---|---|---|
Equation (2) | Equation (3) | Equation (4) | Equation (5) | ||||
0.0271 | −0.0071 | −0.0065 | −0.0119 | 0.1874 ** | 0.0105 | 0.1841 ** | |
(0.0203) | (0.0076) | (0.0059) | (0.0216) | (0.0797) | (0.0176) | (0.0797) | |
−0.0009 | 0.0079 | −0.0184 *** | 0.0342 | 0.0179 | 0.0170 | 0.0228 | |
(0.0227) | (0.0086) | (0.0067) | (0.0247) | (0.0909) | (0.0201) | (0.0909) | |
−0.0189 | 0.0083 | −0.0198 *** | 0.0247 | 0.0391 | 0.0190 | 0.0418 | |
(0.0179) | (0.0066) | (0.0052) | (0.0188) | (0.0693) | (0.0153) | (0.0693) | |
−0.0825 *** | −0.0178 ** | −0.0086 | 0.0006 | 0.2280 *** | 0.0002 | 0.2286 *** | |
(0.0225) | (0.0083) | (0.0064) | (0.0235) | (0.0867) | (0.0191) | (0.0867) | |
0.0051 | −0.0100 | −0.0227 *** | −0.0023 | −0.0394 | −0.0034 | −0.0395 | |
(0.0219) | (0.0080) | (0.0062) | (0.0229) | (0.0843) | (0.0186) | (0.0843) | |
−0.0114 | −0.0129 | −0.0099 | −0.0132 | 0.4454 *** | 0.0141 | 0.4419 *** | |
(0.0272) | (0.0101) | (0.0079) | (0.0288) | (0.1061) | (0.0234) | (0.1061) | |
−0.0366 | 0.0218 | −0.0124 | 0.0154 | −0.1544 | 0.0529 | −0.1583 | |
(0.0490) | (0.0187) | (0.0145) | (0.0539) | (0.1986) | (0.0438) | (0.1987) | |
0.5682 *** | |||||||
(0.0079) | |||||||
0.3434 *** | |||||||
(0.0048) | |||||||
0.0149 *** | 0.0061 *** | ||||||
(0.0029) | (0.0024) | ||||||
0.2027 *** | |||||||
(0.0395) | |||||||
0.1265 *** | |||||||
(0.0486) | |||||||
Constant term | 4.6471 *** | 1.5254 *** | 1.6271 *** | 2.6113 *** | 18.3200 *** | 0.0161 | 18.8899 *** |
(0.1851) | (0.0770) | (0.0594) | (0.2166) | (0.7802) | (0.1760) | (0.7720) | |
Sample size | 9642 | 23,861 | 23,861 | 8698 | 8698 | 8698 | 8698 |
0.1824 | 0.0915 | 0.0787 | 0.0202 | 0.1275 | 0.0166 | 0.1275 | |
Control variable | √ | √ | √ | √ | √ | √ | √ |
Fixed-time effect | √ | √ | √ | √ | √ | √ | √ |
Domestic violence includes not only physical violence but also mental violence with regard to neglect, emotional abuse, etc. Therefore, this study estimates a domestic violence index from the four aspects of injury from violence, negligent care, emotional abuse and witnessing domestic violence, and then takes the CHARLS (2011, 2013, 2015, 2018) and the “life course” survey as sample data to assess the impact of domestic violence on personal education, health and life satisfaction, in turn. The main conclusions are as follows: (1) Domestic violence significantly reduced the respondents’ educational achievements. Compared with the three dimensions of injury from violence, negligent care and witnessing domestic violence, emotional abuse had the most significant negative impact on educational achievements. (2) Domestic violence significantly reduced the self-rated health level and life satisfaction and significantly increased the mental health risk of the respondents.
The above conclusions have important policy implications for optimizing social governance strategies. Domestic violence has far-reaching negative impacts on personal education, health and life satisfaction. To prevent domestic violence and heal the trauma caused, based on its complexity and concealment, we believe that its long-term impact on individuals should be approached from the following four perspectives.
First, a domestic violence monitoring system should be built. Domestic violence has the characteristics of being long-term and repeated, so it is necessary to find the families involved and prevent recurrence in a timely manner. On one hand, the tracking mechanism should be strengthened: for people with low educational achievements and low physical and mental satisfaction (especially young people), society, schools and families should be vigilant in tracing domestic violence back to the source to prevent long-term negative impacts. On the other hand, the feedback mechanism should be strengthened: for those who have suffered from domestic violence, the probability of being subjected to repeated domestic violence is greatly increased. Therefore, they should be encouraged to express their concerns freely, and in the future, a “one-to-one” follow-up mechanism, and a “fixed + random” feedback mechanism should be established to strengthen the ability of victims to provide feedback and communicate with the relevant departments.
Second, the harm caused by emotional abuse and other mental abuse should be confronted. On one hand, the consciousness of the victims needs to be awakened. Domestic violence refers not only to physical violence but also emotional abuse, neglect and other spiritual mistreatment. However, compared with physical violence, the biggest dilemma surrounding domestic psychological abuse is that the victims do not comprehend it themselves but instead feel extreme emotional pain and depression. Therefore, it is necessary to make the content and methods of domestic psychological abuse known, so that the parties who are unknowingly experiencing it will become aware and safeguard their rights. On the other hand, we should establish a working mechanism for linking the authorities that deal with domestic violence. The difficulty in determining if domestic violence is occurring is that it is not easy to obtain evidence, and many victims are unable to enter the judicial process. Therefore, the judicial department should link with women’s federations, neighborhood committees, village committees and other departments to deal with cases of psychological abuse flexibly and quickly, integrating evidence collection, assistance and protection.
Third, attention should be paid to the long-term impact of domestic violence on individuals. On one hand, many perpetrators do not realize that domestic violence is a crime; on the other hand, they ignore the long-term harm to individuals caused by domestic violence. Therefore, we should not only enhance the public’s legal understanding of domestic violence but also use new media to publicize the serious harm that can be caused to individuals as a result of domestic violence. Furthermore, family moral education needs to be strengthened, and the establishment of harmonious families advocated.
Fourth, it is necessary for domestic violence to be prevented at the source. Accordingly, we must go deep into communities to facilitate an understanding of the legal issues related to family disputes [ 35 , 36 ], not only to issue personal safety protection orders to the victims but also to use laws and regulations to intervene and correct the behavior of the perpetrators [ 37 ]. Finally, we need to fully investigate and establish a family violence litigation protection base and form a “one-stop” litigation processing procedure that is simple and smooth, with privacy protections.
This research was funded by the Hunan Health Economics and Information Society, grant number 2022B07.
L.B. and P.Y. generated the idea and study design, collected data, and carried out the data analysis and write up. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Data availability statement, conflicts of interest.
The authors declare that they have no conflict of interest.
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DOI link for Quantitative methods for researching domestic violence and abuse
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Quantitative methods are increasingly being used in domestic violence and abuse (DVA) settings to build evidence that can affect meaningful change. Ideally resulting in processes that are reproducible and results that can be comparable, quantitative methods are highly valued by many stakeholders, making them particularly useful to inform DVA practice, policy, and research. In essence, quantitative methods produce numerical estimates. When done well, these estimates provide insightful, precise, and valid scientific conclusions. This chapter provides an overview of common quantitative research approaches and methods, with salient examples interspersed throughout. The focus begins on important underlying principles, such as statistical significance, typologies of analysis, basic statistics, types of variables, association of variables, and levels of measurement. From there, the discussion proceeds to an overview of commonly used univariate and bivariate statistical methods. Next, more various advanced multivariable modelling methods such as regression analysis, multilevel regression analysis, factor analysis, and structural equation modelling are covered. Finally, limitations of quantitative methods are reviewed to provide important context for those conducting and interpreting the results of such analyses. Overall, readers will find this chapter to be an easy-to-digest and non-technical reference. For those who are somewhat familiar with quantitative research, the chapter will serve as a useful refresher. Moreover, for those new to quantitative methods, this chapter will provide a starting point for further exploration. In all, the chapter expertly weaves together a multitude of useful content for many stakeholders, and will hopefully inform future DVA-focused work.
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Domestic Violence - Science topic. Deliberate, often repetitive, physical abuse by one family member against another: marital partners, parents, children, siblings, or any other member of a ...
The purpose of creating this list is for students to have available a comprehensive, state-of-the-research, easy-to-read compilation of a wide variety of domestic violence topics and provide research paper examples on those topics.
Answer. In recent times, people undergoing gender transformation/transition had been reportedly abused. GBV is a storm in a tea cup. Researchers are working tirelessly to stem the tide. View. 0...
By considering diverse variables encompassing mood, depression, health consciousness, social media engagement, household chores, density, and religious affiliation, the study aims to comprehend the underlying dynamics influencing domestic violence.
Research, evidence, and evaluation help foster a deeper understanding of domestic violence and intersecting issues and strengthen our ability to develop services, programs, and policies that meet survivors’ needs.
The goal of this review is to provide an updated synthesis of qualitative research identifying barriers and facilitators, advice, and positive and negative outcomes of adult victims' disclosure of domestic violence to healthcare professionals (HCPs). A systematic search of PsychINFO, CINAHL and Web of Science was conducted in January 2018.
This study was conducted as mixed research (cross-sectional descriptive and phenomenological qualitative methods) to investigate domestic violence against women, and some related factors (quantitative) and experiences of such violence (qualitative) simultaneously in Semnan.
Starting with education, health and life satisfaction, the long-term impact of domestic violence experiences on individuals is quantitatively assessed, providing empirical evidence for preventing and curing domestic violence and healing trauma.
The following chapters present a broad overview of domestic violence research findings that may be of use to justice professionals as they initiate, improve, and revamp domestic violence policies and practices. The research in each chapter is organized by purpose, findings, implications, methods, and limitations.
In essence, quantitative methods produce numerical estimates. When done well, these estimates provide insightful, precise, and valid scientific conclusions. This chapter provides an overview of common quantitative research approaches and methods, with salient examples interspersed throughout.