Intimate Partner Violence and a New Screening Score - a Prospective Observational Study Over Eight Years

All cases with association to IPV during inclusion period. 40 individuals had to be excluded due to missing data resulting in 1.366 individuals that were included in our analysis. Patients were identified from hospital in-patient enquiry system and in-house screening service for IPV. The IPV in-house screening service was established in 2008, and our Department represents a leading figure in detection and servicing victims of domestic violence. Our IPV in-house screening service is a routine procedure established 24/7 at clinics for all admitted patients.

If the slightest suspicion rose up, patients were asked by the attending physician or nurse, in a private and respectful manner, if a certainty of IPV exists, related to the actual presentation. If the patient admits the fact of IPV, this is noted in the hospital in-patient enquiry system, and a notification is sent to the local police station - as required by Austrian law. Part of our IPV in-house screening service, is the admission to the victim protection program and photographic documentation for legal utilization on behalf of the victim in an upcoming law claim, both services can be joined voluntarily by the victims.

Classification of migration background Patients´ clinical and demographic data were retrieved from our database. Migration background was defined according to current law (MighEV §6, Sozialgesetzbuch). In detail this means that migration background is fulfilled, if (1) the person does not possesses the national citizenship, or (2) the origin of birth is outside the borders of the national country, and emigration to the national territory was after 1949, or (3) origin of birth of one of the two parents is outside the current borders of the national territory plus emigration of one of the two parents occured after 1949.

The reason for using German law in an Austrian study is justified by a more practical and veridical approach of the German law in this particular matter. The corresponding Austrian law for defining migration background is almost identical, except for (3), where compared to Germany both parents have to be affected instead of one. The reason for explaining this matter in such a detail is to avoid any misleading conclusions, based on false assumptions.

Study population was divided into the following sub-groups: patients with migration background (MB), and patients without migration background (NMB), according to data retrieved from patient's medical records and inclusion criteria.

Classification of lunar phases Adjustment of our dataset according to lunar phases was performed in collaboration with the Central Institute for Meteorology and Geodynamics (Zentralanstalt für Meteorologie und Geodynamik, ZAMG), Vienna, Austria.

Classification of socioeconomic status Socioeconomic status of the victim was assumed according to their zip code in correlation with a data adjustment with Statistics Austria, Vienna, Austria. The 23 districts of Vienna were subdivided in three groups: rich, middle class, and poor, according to data from Statistics Austria and government reports. Rich was defined as > 110% of average income; middle class 90-110% of average income; and poor <90% of average income; Districts for "rich" were considered: 1., 4., 7., 13., 18., 19., 23.; Middle class: 2., 3., 6., 9., 11., 14., 17., 21., 22.; Poor: 5., 10., 12., 15., 16., 20.; Outcome measurement The primary outcome measured was the association between migration background and IPV.

Acceptance of the victim protection program and photographic documentation, relationship between the occurrence of IPV and moon´s phase, significant linkage between poverty and IPV, and other epidemiological facts were also observed.

RIPV score implementation Based on our hypothesis for possible influencing factors and existing findings in the literature, we generated the RIPV score to detect possible IPV victims in the ED [5,9,11,35,38]. The score is characterised by 8 simple questions and covers the most prominent factors associated with IPV in women. Therefore the 8 questions are: 1. Is there any history of IPV? 2. Is there a substance abuse in your environment? 3. Is there a migration background? 4. Is there a poor socioeconomic status? 5. Absent moon? 6. Are you pregnant? /. Female gender? 8. Age below 35 years? This score was retrospectively utilized in our study population to proof its possible effectiveness. (Table 2)

Statistical analysis For statistical analyses we used the SPSS 16.0 software package (SPSS, Chicago, Ill., USA). Mean value and standard error of the mean were given unless otherwise indicated for continuous variables. Discrete data are presented as counts and percentages. A two-tailed p-value < 0.05 was considered statistically significant.