Gender Differences Between Domestic Violent Men and Women: Criminogenic Risk Factors and Their Association With Treatment Dropout.

Although many studies have concluded that men and women engage in domestic violence at equal levels, existing studies have hardly focused on gender specific risk factors for domestic violence perpetration. Therefore, this study aimed to examine gender differences in criminogenic risk factors between Dutch male and female forensic outpatients who were referred to forensic treatment for domestic violence. Clinical structured assessments of criminogenic risk factors were retrieved for 366 male and 87 female outpatients. Gender differences were not only found in the prevalence and interrelatedness of criminogenic risk factors, but also in associations between criminogenic risk factors and treatment dropout. In men, risk factors related to the criminal history, substance abuse, and criminal attitudes were more prevalent than in women, whereas risk factors related to education/work, finances, and the living environment were more prevalent in women. Further, having criminal friends, having a criminal history, and drug abuse were associated with treatment dropout in men, whereas a problematic relationship with family members, housing instability, a lack of personal support, and unemployment were associated with treatment dropout in women. Finally, network analyses revealed gender differences in risk factor interrelatedness. The results provide important insights into gender specific differences in criminogenic risk factors for domestic violence, which support clinical professionals in tailoring treatment to the specific needs of male and female perpetrators of domestic violence.

Validation and further development of a risk assessment instrument for child welfare.

BACKGROUND: Although many child maltreatment risk assessment instruments have been implemented in child welfare organizations, thorough studies on their predictive validity are scarce. OBJECTIVE: To examine (1) the predictive validity of a risk assessment instrument that has been widely implemented in the Netherlands, and to examine (2) whether the actuarial risk estimation could be improved and simplified to widen the instrument's applicability to different organizations serving different populations. PARTICIPANTS AND SETTING: The sample comprised risk assessments (N = 3,681) performed for families enrolled at one of five child welfare agencies in the Netherlands between January 2015 and December 2017. METHODS: In a follow-up period of at least one year, child maltreatment was operationalized as whether or not child protection orders, residential care, or hotline reports occurred. Area Under the Curve values were calculated to determine the predictive accuracy of the risk classifications. Chi-square Automatic Interaction Detection was used to develop a new risk classification based on a new cumulative risk variable. RESULTS: The original risk classification and the newly developed and simplified risk classification showed a similar discriminative accuracy for the different outcome measures: Area Under the Curve values were .68 and .69 for child protection orders, .62 and .63 for residential care, and .58 and .60 for hotline reports, respectively. CONCLUSIONS: The original and new risk classification of the instrument had a medium predictive validity with the latter being simpler, more widely applicable, and based on more valid risk factors.

Exploring the interrelatedness of risk factors for child maltreatment: A network approach.

BACKGROUND: Theories on the etiology of child maltreatment generally focus on the interaction between multiple risk and protective factors. Moreover, the quadratic model of cumulative risk describes a threshold at which the risk of child maltreatment increases exponentially, suggesting a synergistic effect between risk factors. OBJECTIVE: This study explored the interrelatedness of risk factors for child maltreatment. PARTICIPANTS AND SETTING: The sample consisted of risk assessments performed for both high-risk families (n = 2,399; child protection services) and lower risk families (n = 1,904; community outreach services). METHODS: Network analyses were performed on parental risk factors. Three networks were constructed: a cross-sample network, a high-risk network, and a lower risk network. The relations between risk factors were examined, as well as the centrality of each risk factor in these networks. Additionally, the networks of the two samples were compared. RESULTS: The networks revealed that risk factors for child maltreatment were highly interrelated, which is consistent with Belsky's multi-dimensional perspective on child maltreatment. As expected, risk factors were generally stronger related to each other in the high-risk sample than in the lower risk sample. Centrality analyses showed that the following risk factors play an important role in the development of child maltreatment: "Caregiver was maltreated as a child", "History of domestic violence", and "Caregiver is emotionally absent". CONCLUSIONS: We conclude that studying the interrelatedness of risk factors contributes to knowledge on the etiology of child maltreatment and the improvement of both risk assessment procedures and interventions for child maltreatment.