Determinants of domestic violence against women in Ghana

listen audio

Study Justification:
– The prevalence of domestic violence against women in Ghana is unacceptably high.
– Domestic violence has numerous consequences, including psychological, maternal, and neonatal mortality and morbidity outcomes.
– Understanding the factors that contribute to domestic violence is crucial for developing effective interventions and policies.
Study Highlights:
– The study analyzed data from the 2008 Ghana Demographic and Health Survey.
– Of the 1524 ever married women in the study, 33.6% had experienced domestic violence.
– Risk factors for domestic violence included place of residence, husband’s history of witnessing violence, mother’s history of violence, husband’s education level, and husband’s alcohol use.
– Women whose husbands had higher than secondary education were less likely to experience domestic violence.
– The study highlights the need for a multi-stakeholder approach and stricter punishments for perpetrators to address domestic violence.
Study Recommendations:
– Greater efforts should be made to curtail domestic violence against women in Ghana.
– A multi-stakeholder approach involving government agencies, NGOs, community leaders, and healthcare providers should be implemented.
– Stricter punishments should be enforced for perpetrators of domestic violence.
Key Role Players:
– Government agencies responsible for women’s rights and social welfare
– Non-governmental organizations (NGOs) working on gender-based violence
– Community leaders and traditional authorities
– Healthcare providers, including doctors, nurses, and counselors
Cost Items for Planning Recommendations:
– Awareness campaigns and public education materials
– Training programs for healthcare providers and law enforcement personnel
– Support services for survivors of domestic violence, including shelters and counseling services
– Legal aid services for survivors seeking justice
– Monitoring and evaluation of interventions
– Research and data collection on domestic violence prevalence and trends

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is a nationally representative cross-sectional survey, which adds to the strength of the evidence. The sample size is also adequate. However, the abstract could benefit from providing more information on the statistical analysis methods used, such as the specific logistic model and the criteria for variable selection. Additionally, it would be helpful to include the effect sizes or odds ratios for the identified risk factors. These suggestions would further enhance the clarity and robustness of the evidence.

Background: The prevalence of domestic violence remains unacceptably high with numerous consequences ranging from psychological to maternal and neonatal mortality and morbidity outcomes in pregnant women. The aim of this study was to identify factors that increased the likelihood of an event of domestic violence as reported by ever married Ghanaian women. Methods: Data from the 2008 Ghana Demographic and Health Survey (GDHS) was analysed using a multivariate logistic model and risk factors were obtained using the forward selection procedure. Results: Of the 1524 ever married women in this study, 33.6 % had ever experienced domestic violence. The risk of ever experiencing domestic violence was 35 % for women who reside in urban areas. Risk of domestic violence was 41 % higher for women whose husbands ever experienced their father beating their mother. Women whose mother ever beat their father were three times more likely to experience domestic violence as compared to women whose mother did not beat their father. The risk of ever experiencing domestic violence was 48 % less likely for women whose husbands had higher than secondary education as compared to women whose husbands never had any formal education. Women whose husbands drink alcohol were 2.5 times more likely to experience domestic violence as compared to women whose husbands do not drink alcohol. Conclusion: Place of residence, alcohol use by husband and family history of violence do increase a woman’s risk of ever experiencing domestic violence. Higher than secondary education acted as a protective buffer against domestic violence. Domestic violence against women is still persistent and greater efforts should be channelled into curtailing it by using a multi-stakeholder approach and enforcing stricter punishments to perpetrators.

This is a secondary data analysis from the household questionnaire of the 2008 GDHS. A detailed description of the GDHS study design and methods is available elsewhere [7]. Notably, this study was a nationally representative cross-sectional survey that sampled about 12,000 households using a weighted approach. Half of these households were selected for individual interviews and the domestic violence module was administered to women in two-thirds of households selected for the individual interview. Subsequently, only one person was administered the domestic violence module in each selected household. Informed consent was obtained at the beginning of the individual interview and at the beginning of the domestic violence module and additional information was given for domestic violence. Access to demographic and health survey data is managed and provided by MEASURE DHS following an online registration (http://www.dhsprogram.com). Of the households selected for individual interview, 2,563 women were eligible for the domestic violence module, 17 women were excluded because of lack of privacy, 23 women refused to be interviewed with the domestic violence module and 81 women were not interviewed for other reasons. A total of 2442 (unweighted) women agreed to be interviewed. We excluded never married women as well as participants with missing data (n = 765) on covariates included in the multivariable model such as partner’s education level, respondent’s alcohol use, husband’s alcohol use, history of mother beating father and vice versa. This resulted in a sample size of 1524 women for analysis of risk factors for intimate partner violence against ever married women after sampling weight was applied. The outcome variable, domestic violence, as defined for this study included violence perpetrated by intimate partners against women and manifested through acts of physical, sexual, and emotional violence. The following seven (7) questions were used to create the variable for physical violence: (Did) your (last) husband/partner ever i. Slapped you? ii. Twisted your arm or pulled your hair? iii. Pushed you, shook you, or threw something at you? iv. Punched you with his fist or with something that could hurt you? v. Kicked you, dragged you or did beat you up? vi. Tried to choke you or burned you on purpose? vii. Threatened or attacked you with a knife, gun, or any other weapon [7]. A “yes = 1” to any of these questions constituted physical violence. If a woman scores from 1 to 7 then physical violence was coded as “1” to represent an event of “physical violence” and if a woman scores “0” then physical violence was coded as “0” to represent an event of “no physical violence”. Furthermore, sexual violence was measured using the following set of questions for women: (Did) your (last) husband/partner ever i. physically forced you to have sexual intercourse with him even when you did not want to? ii. Forced you to perform any sexual acts you did not want to? [7]. A “yes = 1” to either questions constituted sexual violence; as such if a woman gets a score of “1” or “2”, then a code of “1” was assigned to represent an event of “sexual violence”. If a woman scores “0”, then a code of “0” was assigned to represent the event of “no sexual violence”. Subsequently, spousal violence was created as per its definition in the GDHS report by combining physical and sexual violence [7]. Emotional violence was measured in a similar way, using the following set of questions: (Did) your (last) husband ever: i. Said or did something to humiliate you in front of others? ii. Threatened to hurt or harm you or someone close to you? iii. Insulted you or made you feel bad about yourself? [7]. A “yes = 1” to any of these questions constituted emotional violence. Scoring from 1 to 3 was coded as “1” to represent the event “emotional violence”. Otherwise, a code of “0” was assigned to represent the event of “no emotional violence”. The outcome variable, domestic violence was then created as per the definition of domestic violence for this study by combining spousal violence and emotional violence. The event of “no domestic violence” was coded as “0” for participants who did not experience either spousal or emotional violence. For those who experienced only emotional violence, only spousal violence and both spousal and emotional violence, a code of “1” was assigned to represent the event of “ever experienced domestic violence”. Covariates considered as risk factors were selected on the basis of causal assumption derived from subject matter knowledge. These included age of respondent, place of residence, educational level of respondent and partner, religion, wealth index, marital status, employment status of both responded and partner and alcohol use by both respondent and partner [1, 4, 14, 17]. Distribution of categorical variables were reported as frequency counts whilst associations were tested using chi-square or fisher’s exact test. Univariate logistic regression analysis was initially performed to evaluate the ability of each covariate to predict the event “ever experienced domestic violence”. Predictors with some degree of association from the univariate analyses (p < 0.25) were entered into a preliminary multivariate logistic model [18] either as continuous variables or categorized as quartiles and those that showed some degree of association (p < 0.25) were added one by one until no remaining variable produces a significant F statistic (forward selection). The forward selection model was chosen over simultaneous model as this study was designed to select from a group of independent variables, the one variable at each stage which makes the largest contribution to R2. To ensure that the predictor variables included in the model were independent of each other, variance inflation factor was used as a measure colinearity and none of the predictor variables in final model was highly associated with each other. Data were analysed using SAS version 9.2 (SAS Institute) and all statistical tests were two tailed and a p < 0.05 was considered statistically significant.

N/A

Based on the information provided, here are some potential innovations that could improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and resources on maternal health, including access to prenatal care, nutrition, and emergency services. These apps can also provide reminders for appointments and medication, as well as educational materials for expectant mothers.

2. Telemedicine: Implement telemedicine services that allow pregnant women in remote or underserved areas to consult with healthcare professionals through video calls. This can help address the lack of healthcare providers in certain regions and improve access to prenatal care and medical advice.

3. Community Health Workers: Train and deploy community health workers who can provide basic prenatal care, education, and support to pregnant women in their communities. These workers can also help identify and refer high-risk pregnancies to appropriate healthcare facilities.

4. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with financial assistance to access maternal health services, such as prenatal check-ups, delivery, and postnatal care. These vouchers can be distributed to low-income women or those in remote areas to reduce financial barriers to care.

5. Transportation Support: Develop transportation initiatives that provide pregnant women with affordable and reliable transportation to healthcare facilities. This can include partnerships with local transportation providers or the use of innovative transportation solutions like ambulances or mobile clinics.

6. Maternal Health Education: Implement comprehensive maternal health education programs that target women, families, and communities. These programs can focus on raising awareness about the importance of prenatal care, nutrition, and safe delivery practices, as well as addressing cultural beliefs and practices that may hinder access to care.

7. Strengthening Healthcare Infrastructure: Invest in improving healthcare infrastructure, particularly in underserved areas, by building or upgrading maternal health facilities. This includes ensuring the availability of essential equipment, supplies, and skilled healthcare professionals to provide quality maternal care.

It’s important to note that the specific context and needs of Ghana should be taken into consideration when implementing these innovations. Additionally, a multi-stakeholder approach involving government, healthcare providers, NGOs, and communities is crucial for the successful implementation and sustainability of these initiatives.
AI Innovations Description
The study you described focuses on the determinants of domestic violence against women in Ghana. While the study does not directly address access to maternal health, it provides valuable insights into the factors that contribute to violence against women, which can have significant implications for maternal health outcomes.

Based on the findings of the study, here is a recommendation that can be developed into an innovation to improve access to maternal health:

1. Multi-stakeholder approach: Given that domestic violence is a complex issue with multiple underlying factors, it is important to adopt a multi-stakeholder approach to address it. This approach should involve collaboration between government agencies, healthcare providers, community organizations, and civil society groups. By working together, these stakeholders can develop comprehensive strategies to prevent domestic violence and improve access to maternal health services.

2. Awareness and education: One key aspect of addressing domestic violence and improving access to maternal health is raising awareness and providing education. This can be done through community outreach programs, workshops, and campaigns that aim to educate both women and men about their rights, the consequences of domestic violence, and the importance of seeking maternal health services. By increasing awareness and knowledge, individuals are more likely to recognize and address domestic violence, leading to improved access to maternal health.

3. Strengthening healthcare systems: To improve access to maternal health services for women experiencing domestic violence, it is crucial to strengthen healthcare systems. This can be achieved by training healthcare providers on identifying and responding to domestic violence, integrating domestic violence screening into routine maternal health services, and establishing referral pathways to support services for survivors of domestic violence. By ensuring that healthcare providers are equipped to address domestic violence, women can receive the necessary support and care during pregnancy and childbirth.

4. Enforcing stricter punishments: To deter perpetrators of domestic violence and protect women, it is important to enforce stricter punishments for those who commit acts of violence. This can be achieved through legislative measures that criminalize domestic violence and ensure that perpetrators are held accountable for their actions. By creating a legal framework that prioritizes the safety and well-being of women, it sends a strong message that domestic violence will not be tolerated, ultimately improving access to maternal health by reducing the prevalence of violence.

In summary, by adopting a multi-stakeholder approach, raising awareness and providing education, strengthening healthcare systems, and enforcing stricter punishments, it is possible to develop an innovation that improves access to maternal health for women experiencing domestic violence in Ghana.
AI Innovations Methodology
Based on the information provided, it seems that you are looking for innovations to improve access to maternal health. Unfortunately, the given text does not directly address maternal health or provide specific recommendations for improving access to maternal health. However, I can provide you with a general methodology to simulate the impact of recommendations on improving access to maternal health.

Methodology to Simulate the Impact of Recommendations on Improving Access to Maternal Health:

1. Define the recommendations: Identify specific recommendations that can potentially improve access to maternal health. These recommendations could include interventions such as increasing the number of healthcare facilities, improving transportation infrastructure, implementing telemedicine services, or providing financial incentives for healthcare providers.

2. Identify relevant data: Gather data on the current state of maternal health and access in the target population. This may include information on maternal mortality rates, healthcare infrastructure, transportation availability, and socio-economic factors that affect access to healthcare.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and relevant data. The model should simulate the impact of the recommendations on improving access to maternal health. This can be done using statistical modeling techniques or simulation software.

4. Define outcome measures: Determine the outcome measures that will be used to evaluate the impact of the recommendations. These may include indicators such as the number of maternal deaths prevented, the increase in the number of women accessing prenatal care, or the reduction in travel time to healthcare facilities.

5. Run simulations: Use the simulation model to run multiple simulations with different scenarios. This can involve varying the implementation of recommendations, such as different levels of investment or different combinations of interventions. Each simulation should generate results based on the defined outcome measures.

6. Analyze results: Analyze the results of the simulations to assess the impact of the recommendations on improving access to maternal health. Compare the outcomes of different scenarios to identify the most effective interventions or combinations of interventions.

7. Validate and refine the model: Validate the simulation model by comparing the simulated results with real-world data, if available. Refine the model based on feedback and further analysis to improve its accuracy and reliability.

8. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community organizations. Use the results to advocate for the implementation of effective recommendations and inform decision-making processes.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and available data. Additionally, the success of any recommendations will depend on various factors, including the local healthcare system, cultural norms, and resource availability.

Share this:
Facebook
Twitter
LinkedIn
WhatsApp
Email
Chat Icon DIMA AI Care
×