## 4 Discussion  
The purpose of this study was to identify the factors that distinguish between offender patients with SSD who show aggressive behavior within a hospitalized setting and those who do not. The idea was to exploratively identify the most predictive factors in inpatient violence. By applying ML algorithms to a large database, we were able to create an appropriate model consisting of nine factors. With a balanced accuracy of 73.5 and an AUC of 0.84, the model was able to correctly identify aggressive patients in nearly three-quarters of events and non-aggressive patients in two-thirds of events. The variables related to psychopathology and antisocial behavior proved to be the most predictive regarding inpatient aggression. The aggressive patients in our population showed an increased occurrence of _negative behavior toward other patients_. Patient/patient interaction is known to trigger aggressive events on general psychiatric wards in about a quarter of cases [16; 17; 18]. It seems obvious that this factor is all the more important in a forensic psychiatric hospital, where severely ill patients with a high potential for violence come together in a confined space with little opportunity for avoidance. This finding emphasizes the importance of de-escalating skills among staff. Remarkably, in contrast to previous results regarding acute general psychiatric wards, _negative behavior toward staff_ was not identified as one of the ten most predictive parameters [19; 20; 21; 22]. This seems somewhat contradictory to the fact that both _failure to comply with the ward rules_ and _complains about hospital staff_ were highly relevant in distinguishing aggressive from non-aggressive patients: Pointing out or insisting on adherence to ward rules and disciplining noncompliance often causes friction between staff and patients. While such situations arise on a regular basis within a highly institutionalized setting, such as forensic psychiatry, they do not seem to be obligatorily linked to the development of a negative attitude toward the staff and may be tolerated in the presence of a sustainable therapeutic relationship. _Poor impulse control, tension, hostility,  
Figure 2: Importance of variable of final model “aggression” vs. “no aggression”: DZ2 = patient showed negative behavior toward other patients; DZ10 = patient broke ward rules; PA_A = PANSS score at admission; PA28 = Adapted PANSS at admission: poor impulse control; PA7 = Adapted PANSS at admission: hostility; DZ1 = patient complained about the hospital staff; DZ7 = Patient showed dis/antisocial utterances or attitudes; PA18 = Adapted PANSS at admission: tension; PA22 = Adapted PANSS at admission: uncooperativeness. and uncooperativeness_, measured using the corresponding PANSS scales, as well as the overall _PANSS score at admission_, were also identified as key factors related to inpatient aggression. While the results regarding a lack of impulse control, tension, and hostility are in line with previous findings regarding inpatient aggression in SSD patients as well as aggressive events prior to hospitalization, the link between overall symptomatology represented by the total PANSS score and aggression remains controversial [10; 23; 24; 25]. This suggests that it is not the severity of disease alone that determines the development of aggression, but rather the interplay of the various factors present [23; 25]. In summary, the factors that constitute aggression during hospitalization can be reduced to two domains, psychopathology, and antisocial behavior. Interestingly, these two domains outweighed all the other factors, for example, the parameters related to child development, social contacts, and family situation. This was surprising as childhood poverty, for instance, has been previously identified as a risk factor for violent offending [10; 26; 27].