In 2023, almost one out of three ever-partnered Turkish women had experienced domestic violence. In comparison, only 12 percent of women living in Switzerland had experienced domestic violence in their lifetime.

Domestic abuse numbers, prevalence, types and victim characteristics, based upon findings from the Crime Survey for England and Wales and police recorded crime.

As of 2024, Timor-Leste had the highest prevalence of domestic violence against women in the Asia-Pacific region, with ** percent of women having experienced physical or sexual violence in a partnership before. In contrast, approximately *** percent of women in Singapore had experienced domestic violence as of 2024.

Romania holds the lowest Gender Equality Index among EU member states in 2023, a position mirrored by alarming domestic violence statistics. In 2023 alone, there were 40,956 female victims of domestic violence. Since 2018, such crimes have consistently risen, with a notable 4.79% increase from 2022 to 2023.

In France, in 2022, around ******* women reported to the authorities physical, sexual, or psychological violence by their spouse or ex-spouse. The majority of these women were victims of psychological or verbal violence.

This study examined the often overlooked and under reported issue of elder abuse. The research focused on female victims of domestic abuse over 50 years of age. The data were also compared to similar data on women under the age of 50. The data were collected in Rhode Island for several reasons, including the state's relatively broad definition of domestic violence and the large number of reports. Researchers examined every domestic violence report made to state and local law enforcement across Rhode Island in 2002 involving women victims 50 years of age and older. These reports include every incident, whether or not police ultimately arrested the alleged suspect, that meets the statutory definition of "domestic violence." The source of the report information was the Domestic Violence and Sexual Assault Reporting Form (DV/SA). Data were also collected about the past criminal activity of the suspects and any charges made after the study incident(s) occurred. The data were found in the Rhode Island Courts' central repository called CourtConnect. The purpose of the study was to better understand the characteristics of the victims and their abusers, the circumstances of the incidences of abuse, and the police response to the reports of domestic abuse. Data collected consisted of independent variables which are organized into conceptual clusters including those relating to victim characteristics, abuser characteristics, the nature of the incident, and the state's response to the incident. The victim characteristics included demographics and abuse history, if any. Abuser characteristics included demographics and criminal history. Incident characteristics described the abuse incidence in detail. Criminal justice response variables outlined how police and courts responded and reacted to the abuse. There were two dependent outcome variables in this study consisting of re-victimization and re-abuse. The data were analyzed using descriptive statistics, bivariate relationships, and multiple logistic regression. This study primarily focused on the response of the criminal justice system to elder abuse, the effect of age of victim, and re-abuse and re-victimization in order to gain a clearer picture into the realities of domestic abuse of elderly women.

This study sought to understand perceived barriers to help-seeking for female victims of domestic abuse age 50 years and older (by a spouse, partner, adult child, grandchild, other relative or close friend) relative to the perceived barriers for women in the same age group who are not victims of such abuse. Additionally, the study explored the impact of key demographic variables of race and ethnicity, relationship to the presumed abuser, and age at the time of the survey on perceived barriers of victims. To address these research questions this study tested an empirical model that described relevant factors regarding perceived barriers to help-seeking and explored if and how this model changed based on the identified variables. Study participants represented a community sample of females age 50 years and older interested in participating in research regarding conflict in close personal relationships experienced by women in this target age range. Specific aims for the project were intended to lead to increased knowledge regarding perceived barriers to help-seeking among older women and, in particular, to develop a basis for describing (a) if and how these perceived barriers were unique to domestic abuse victims relative to non-victims in this age group and (b) how they varied based on selected variables.

An interactive Excel-based data tool for domestic abuse statistics. It allows users to explore data for their police force area in more detail and compare with other areas.

This study sought to examine the incidence and prevalence of domestic violence among female arrestees. The data for this research were collected in conjunction with the National Institute of Justice's Arrestee Drug Abuse Monitoring (ADAM) programs. Female arrestees in San Diego, California, who had completed the ADAM interview and provided a urine specimen were asked if they would be willing to answer an additional set of questions concerning their experience with domestic violence. Respondents were asked a series of questions about the types of abuse they experienced and a host of supplemental questions detailing the abusive incidents they experienced in their lifetime and in the last 12 months.

In 2019, over ** women out of every 100 thousand across India experienced domestic abuse in some form. In the past few years, the number of these cases went down gradually except in 2019. The Protection of Women from Domestic Violence Act was enacted by the Indian parliament in 2005 protects women from domestic violence. However, many varieties of crime go unreported.

Data Series: Existence of laws on domestic violence Indicator: QV.2 - Existence of laws on domestic violence Source year: 2024 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Human rights of women and girl children

This is the statistics of domestic violence cases from 2015 to 2023, explaining that the data is from the statistical charts from 2015 to 2023.

Domestic abuse numbers, prevalence, types and attitudes experienced by women and men aged between 16 and 59 years and 60 to 74 years, based upon annual findings from the Crime Survey for England and Wales.

The global market for domestic abuse safety apps is experiencing robust growth, projected to reach $222 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12.1% from 2025 to 2033. This expansion is fueled by several key factors. Increased awareness of domestic violence and improved access to smartphones are driving adoption. Users are increasingly seeking discreet, readily available tools for help, and the apps provide a critical safety net, offering features like silent alerts, GPS tracking, and secure communication channels. Furthermore, the evolving technological landscape, with advancements in location services and AI-powered threat detection, is further boosting the market's potential. The market also benefits from strong advocacy and support from government agencies and non-profit organizations. However, challenges remain. Concerns about data privacy and security are paramount, particularly given the sensitive nature of the information handled. Effective user education and trust-building initiatives are crucial for wider adoption. The market is also subject to fluctuations influenced by changes in funding for related support services and public awareness campaigns. Competition among a growing number of app providers, some offering niche features, necessitates continuous innovation and differentiation. Despite these hurdles, the long-term outlook remains positive, driven by technological advancements, increased user awareness, and growing governmental and societal support for victims of domestic violence. Segment-specific analysis (e.g., by app features, user demographics, or geographical region) would yield a more comprehensive understanding of the market landscape.

In the past few years it has become alarmingly clear that women with disabilities are at an extremely high risk for emotional, sexual, and physical assault. The Developmental Disabilities Institute at Wayne State University, in collaboration with the United Cerebral Palsy Association in Michigan, conducted a one-year study to investigate the prevalence and correlates of, and service system capacity related to, domestic abuse among women with physical disabilities in Michigan. The study aimed to address the following research questions: (1) What is the prevalence of domestic violence among a sample of women with physical disabilities? (2) What potential factors for domestic violence exist among women with physical disabilities? and (3) What is the capacity of existing support programs (e.g., safe houses, shelters, and service agencies) to assist women with physical disabilities? The population for this study was women over the age of 18 who had physical disabilities. Consistent with the work of other researchers, physical disabilities in this study were defined as those disabilities that result in functional impairment, such as cerebral palsy, post-polio syndrome, spina bifida, amputation, rheumatic conditions, multiple sclerosis, spinal cord injury, traumatic brain injury, visual impairment, hearing impairment, and stroke. A sample of 177 women was recruited through several mechanisms. To address the question of domestic abuse prevalence, the women participating in the study were first asked to complete a brief questionnaire addressing demographic characteristics and their experience with domestic violence (Part 1, Screening Interview Data). Fifty-six percent (100) of the 177 women interviewed indicated a positive history of abuse at their initial screening. In order to address the second research question about the correlates of abuse, this subsample of 100 women was invited and encouraged to participate in the second phase of the research, which involved a more extensive interview (Part 2, Abuse Interview Data). The interview used was based on a protocol developed by Nosek (1995) that addressed demographic characteristics, social networks, and abuse history. Variables in Parts 1 and 2 include type of disability, type of personal assistance needed, and whether the respondent was ever physically, emotionally, or sexually abused. Part 2 also contains variables on sources of monthly income, who perpetrated the abuse, the abuser's gender, how long the victim knew the abuser, whether the victim sought assistance from a domestic violence program or shelter, and a description of the worst incident of physical abuse. Demographic variables in Parts 1 and 2 include ethnicity, age, employment status, and marital status.

This data is about female domestic violencecrimes (2018-2020) recopiled by CEAD-SPD

The study set out to test the question of whether more efficacious outcomes would be gained the closer that a second response by police officers occurs to an actual domestic violence event. Researchers conducted a randomized experiment in which households that reported a domestic incident to the police were assigned to one of three experimental conditions: (a) second responders were dispatched to the crime scene within 24 hours, (b) second responders visited victims' homes one week after the call for service, or (c) no second response occurred. Beginning January 1, 2005, and continuing through December 3, 2005, incidents reported to the Redlands Police Department were reviewed each morning by a research assistant to determine whether the incidents involved intimate partners. Cases were determined to be eligible if the incident was coded as a misdemeanor or felony battery of a spouse or intimate partner. Eighty-two percent of the victims were females. For designated incidents, a team of officers, including a trained female domestic violence detective, visited households within either twenty-four hours or seven days of a domestic complaint. A written protocol guided the officer or officers making home visits. Officers also asked the victim a series of questions about her relationship with the abuser, history of abuse, and the presence of children and weapons in the home. In Part 1 (Home Visit Data), six months after the reporting date of the last incident in the study, Redlands Police crime analysis officers wrote a software program to search their database to determine if any new incidents had been reported. For Part 2 (New Incident Data), the search returned any cases associated with the same victim in the trigger incident. For any new incidents identified, information was collected on the date, charge, and identity of the perpetrator. Six months following the trigger incident, research staff attempted to interview victims about any new incidents of abuse that might have occurred. These interview attempts were made by telephone. In cases where the victim could not be reached by phone, an incentive letter was sent to the victim's home, offering a $50 stipend to call the research offices. Part 1 (Home Visit Data) contains 345 cases while Part 2 (New Incident Data) contains 344 cases. The discrepancy in the final number across the two parts is due to cases randomized into the sample that turned out to be ineligible or had been assigned previously from another incident. Part 1 (Home Visit Data) contains 63 variables including basic administrative variables such as date(s) of contact and group assignment. There are also variables related to the victim and the perpetrator such as their relationship, whether the perpetrator was arrested during the incident, and whether the perpetrator was present during the interview. Victims were also asked a series of questions as to whether the perpetrator did such things as hit, push, or threatened the victim. Part 2 (New Incident Data) contains 68 variables including dates and charges of previous incidents as well as basic administrative and demographic variables.

In 1996 the Institute for Law and Justice (ILJ) began an evaluation of the law enforcement and prosecution components of the "STOP Violence Against Women" grant program authorized by the Violence Against Women Act of 1994. This data collection constitutes one component of the evaluation. The researchers chose to evaluate two specialized units and two multi-agency team projects in order to study the local impact of STOP on victim safety and offender accountability. The two specialized units reflected typical STOP funding, with money being used for the addition of one or two dedicated professionals in each community. The Dane County, Wisconsin, Sheriff's Office used STOP funds to support the salaries of two domestic violence detectives. This project was evaluated through surveys of domestic violence victims served by the Dane County Sheriff's Office (Part 1). In Stark County, Ohio, the Office of the Prosecutor used STOP funds to support the salary of a designated felony domestic violence prosecutor. The Stark County project was evaluated by tracking domestic violence cases filed with the prosecutor's office. The case tracking system included only cases involving intimate partner violence, with a male offender and female victim. All domestic violence felons from 1996 were tracked from arrest to disposition and sentence (Part 2). This pre-grant group of felons was compared with a sample of cases from 1999 (Part 3). In Hillsborough County, New Hampshire, a comprehensive evaluation strategy was used to assess the impact of the use of STOP funds on domestic violence cases. First, a sample of 1996 pre-grant and 1999 post-grant domestic violence cases was tracked from arrest to disposition for both regular domestic violence cases (Part 4) and also for dual arrest cases (Part 5). Second, a content analysis of police incident reports from pre- and post-grant periods was carried out to gauge any changes in report writing (Part 6). Finally, interviews were conducted with victims to document their experiences with the criminal justice system, and to better understand the factors that contribute to victim safety and well-being (Part 7). In Jackson County, Missouri, evaluation methods included reviews of prosecutor case files and tracking all sex crimes referred to the Jackson County Prosecutor's Office over both pre-grant and post-grant periods (Part 8). The evaluation also included personal interviews with female victims (Part 9). Variables in Part 1 (Dane County Victim Survey Data) describe the relationship of the victim and offender, injuries sustained, who called the police and when, how the police responded to the victim and the situation, how the detective contacted the victim, and services provided by the detective. Part 2 (1996 Stark County Case Tracking Data), Part 3 (1999 Stark County Case Tracking Data), Part 4 (Hillsborough County Regular Case Tracking Data), Part 5 (Hillsborough County Dual Arrest Case Tracking Data), and Part 8 (Jackson County Case Tracking Data) include variables on substance abuse by victim and offender, use of weapons, law enforcement response, primary arrest offense, whether children were present, injuries sustained, indictment charge, pre-sentence investigation, victim impact statement, arrest and trial dates, disposition, sentence, and court costs. Demographic variables include the age, sex, and ethnicity of the victim and the offender. Variables in Part 6 (Hillsborough County Police Report Data) provide information on whether there was an existing protective order, whether the victim was interviewed separately, severity of injuries, seizure of weapons, witnesses present, involvement of children, and demeanor of suspect and victim. In Part 7 (Hillsborough County Victim Interview Data) variables focus on whether victims had prior experience with the court, type of physical abuse experienced, injuries from abuse, support from relatives, friends, neighbors, doctor, religious community, or police, assistance from police, satisfaction with police response, expectations about case outcome, why the victim dropped the charges, contact with the prosecutor, criminal justice advocate, and judge, and the outcome of the case. Demographic variables include age, race, number of children, and occupation. Variables in Part 9 (Jackson County Victim Interview Data) relate to when victims were sexually assaulted, if

The goal of this study was to compile and analyze data about incidents of domestic violence in San Diego County, California, in order to enhance understanding of the nature and scope of violence against women. The following objectives were set to achieve this goal: (1) to develop a standardized interview instrument to be used by all emergency shelters for battered women in the region, and (2) to conduct interviews with shelter staff. For this study, the San Diego Association of Governments (SANDAG) collected information about domestic violence in San Diego County from clients admitted to battered women's shelters. The Compilation of Research and Evaluation (CORE) intake interview (Part 1) was initiated in March of 1997. Through this interview, researchers gathered data over a 22-month period, through December 1998, for 599 clients. The CORE discharge interview (Part 2) was theoretically completed at the time of exit with each client who completed the CORE intake interview in order to document the services received. However, data collection at exit was not reliable, due to factors beyond the researchers' control, and thus researchers did not receive a discharge form for each individual who had an intake form. For Part 1 (Intake Data), demographic variables include the client's primary language, and the client and batterer's age, education, race, how they supported themselves, their annual incomes, and their children's sex, age, and ethnicity. Other variables cover whether the client had been to this shelter within the last 12 months, the kind of housing the client had before she came to the shelter, person's admitted along with the client, drug and alcohol use by the client, the batterer, and the children, relationship between the client and the batterer (e.g., spouse, former spouse), if the client and batterer had been in the military, if the client or children were military dependents, the client's citizenship, if the client and batterer had any physical/mental limitations, abuse characteristics (e.g., physical, verbal, sexual, weapon involved), and the client's medical treatment history (e.g., went to hospital, had been abused while pregnant, witnessed abuse while growing up, had been involved in other abusive relationships, had attempted suicide). Additional variables provide legal information (number of times police had been called to the client's household as a result of domestic violence, if anyone in the household had been arrested as a result of those calls, if any charges were filed, if the client or batterer had been convicted of abuse), if the client had a restraining order against the batterer, how the client found out about the shelter, the number of times the client had been admitted to a domestic violence shelter, the client's assessment of her needs at the time of admittance, and the interviewer/counselor's assessment of the client's needs at the time of admittance. Part 2 (Discharge Data) provides information on services the client received from the shelter during her stay (food, clothing, permanent housing, transitional housing, financial assistance, employment, education, medical help, assistance with retrieving belongings, assistance with retrieving/replacing legal documents, law enforcement, temporary restraining order), and services this client received as a referral to another agency (attorney, divorce, child care, counseling, transportation, safety plan, victim/witness funds, mental health services, department of social services, Children's Services Bureau, help with immigration, drug treatment).

Abstract This article aims to estimate the prevalence and factors associated with intimate partner violence among primary care users. Cross-sectional study with women aged 20 to 59 years. Physical, sexual and psychological violence was screened by the World Health Organization instrument. Poisson regression was used for crude and adjusted analysis. Nine hundred ninety-one women participated in the study. The prevalence of violence throughout the lifespan was: psychological 57.6% (95%CI 54.6-60.7); physical 39.3% (95%CI 36.2-42.3) and sexual 18.0% (95%CI 15.7-20.5). Women with up to eight years of schooling, divorced or separated, whose mothers suffered intimate partner violence, who reported drug use and experienced sexual violence in childhood showed a higher prevalence of the three types of violence. Religion was associated with psychological and sexual violence and the use of cigarettes to physical and psychological violence. Participants with lower household income had a higher prevalence of physical violence. A high prevalence of intimate partner violence was identified among users. Worse socioeconomic conditions, risk behaviors and a history of assault are associated with greater occurrence of this problem.