A classification tree approach to the development of actuarial violence risk assessment tools

Interactions Between Offender and Crime Characteristics Leading to a Lethal Outcome in Cases of Sexually-Motivated Abductions

Despite the widespread public concern regarding abduction, research on this type of crime is scarce. This lack of research is even more pronounced when looking at cases that end with the death of the victim. In fact, all of the research looking at lethal outcomes in cases of abductions has focused exclusively on child victims and has failed to consider the interactions at the multivariate level between the factors related to the death of the victim. Therefore, the aim of the study is to identify offender and crime characteristics - as well as their interactions - associated with a lethal outcome in sexually-motivated abductions using a combination of logistic regression and neural network analyses on a sample of 281 cases (81 cases ending with a lethal outcome, random sample of 200 comparison cases). Findings show that sexually-motivated abductions ending with a lethal outcome are more likely to be characterized by an offender who is a loner, forensically aware, and who who uses a weapon and restraints, and who sexually penetrates and beats a known victim. The neural network analysis show that three different pathways lead to a lethal outcome in sexually-motivated abductions. Such findings are important for correctional practices.

How to get away with (sexual) murder? Unraveling cold cases in sexual homicide using a hybrid modeling probabilistic approach

This study examines Sexual Homicide (SH) cases, analyzing the transition to cold cases through a non-discretionary lens. Utilizing the SH International Database, it explores the interplay between offender behavior, victim characteristics, and crime context. Advanced methodologies, including sequential logistic regression and Artificial Neural Networks, identify key predictors of case resolution. Results highlight the critical influence of victim intoxication, high-risk activities, and the location of the victim's body on case solvability. The study also reveals the significant role of offender forensic awareness and the complexity of crime scenes in hindering case resolution. These findings underline the multifaceted nature of SH cases, emphasizing the importance of understanding the nuanced interplay between victim, offender, and contextual factors in solving these challenging cases.

Machine Learning and Risk Assessment: Random Forest Does Not Outperform Logistic Regression in the Prediction of Sexual Recidivism

Although many studies supported the use of actuarial risk assessment instruments (ARAIs) because they outperformed unstructured judgments, it remains an ongoing challenge to seek potentials for improvement of their predictive performance. Machine learning (ML) algorithms, like random forests, are able to detect patterns in data useful for prediction purposes without explicitly programming them (e.g., by considering nonlinear effects between risk factors and the criterion). Therefore, the current study aims to compare conventional logistic regression analyses with the random forest algorithm on a sample of N = 511 adult male individuals convicted of sexual offenses. Data were collected at the Federal Evaluation Center for Violent and Sexual Offenders in Austria within a prospective-longitudinal research design and participants were followed-up for an average of M = 8.2 years. The Static-99, containing static risk factors, and the Stable-2007, containing stable dynamic risk factors, were included as predictors. The results demonstrated no superior predictive performance of the random forest compared with logistic regression; furthermore, methods of interpretable ML did not point to any robust nonlinear effects. Altogether, results supported the statistical use of logistic regression for the development and clinical application of ARAIs.

Betting Against the Odds: The Mysterious Case of the Clinical Override in Risk Assessment of Adult Convicted Offenders

Various tools were designed to guide practitioners in the risk assessment of offenders, including the Level of Service and Case Management Inventory (LS/CMI). This instrument is based on risk assessment principles prioritizing the actuarial approach to clinical judgment. However, the tool's architects allowed subjective judgment from the practitioners-referred to as clinical override-to modify an offender's risk category under certain circumstances. Few studies, however, have examined these circumstances. Therefore, the current study used decision tree analyses among a quasi-population of Quebec offenders (n = 15,744) to identify whether there are offenders more likely to be subjected to this discretion based on their characteristics. The results suggest that, although the override is rare, it occurred under few specific combinations of circumstances. More precisely, these findings propose that the utilization of the clinical override stems from a perceived discrepancy between risk prediction and management.

Strangulation in sexual homicide: Is it opportunity, victim's vulnerability or sadism?

Although most homicides involve the use of a weapon, some offenders still prefer killing with their own hands, using strangulation. In fact, when disaggregating the various types of homicides, sexual homicide offenders appear as having a preference for "personal weapon" to kill the victim. Personal weapons, such as strangulation, asphyxiation, and beating, are the most commonly used killing methods in sexual homicide. Using a sample of 451 cases of sexual homicide of adult female, the current study examines three hypotheses as to why strangulation is the method of choice to kill in sexual homicide: 1) weapon of opportunity, 2) victim's vulnerability, and 3) sexual sadism. Results from logistic regressions and artificial neural network analysis show that all three hypotheses are supported, sexual homicide offenders using strangulation being less likely to target a victim with a strong build, to bring and use a weapon. However, strangulation is more likely to be used to kill the victim when the offender is characterized with sadism. Implications of the findings are discussed in light of our understanding of the crime-commission process involved in sexual homicide.

Psychopathic Traits Are Associated with Lifetime History of Nicotine Dependence among Incarcerated Offenders

Background: Individuals scoring high on psychopathy engage in problematic patterns of alcohol and illicit substance use. However, our understanding regarding the association between psychopathy and nicotine use remains limited, which is surprising, given the detrimental consequences associated with such use. Previous studies have observed significant correlations between psychopathic traits (particularly Factor 2 scores assessing lifestyle/behavioral and antisocial traits from the Psychopathy Checklist - Revised [PCL-R]) and increased frequency of nicotine use. However, no study has investigated whether individuals scoring high on psychopathy are characterized by problematic patterns of nicotine use, including lifetime history of nicotine dependence.Objectives: The current study aimed to address this gap, specifically investigating whether PCL-R scores were associated with higher total scores from the Fagerström Test for Nicotine Dependence (FTND).Results: Across both incarcerated men and women, PCL-R total, Factor 2, and Facet 3 (measuring lifestyle/behavioral psychopathic traits) scores were positively correlated with FTND total scores. Additionally, across both samples, hierarchical linear regression analyses revealed these same psychopathy scores remained associated with higher FTND total scores when controlling for additional covariate measures (e.g., age, severity of alcohol and illicit substance use, race, ethnicity, and IQ).Conclusions/Importance: Though associated with small effect sizes, our results support the notion that lifestyle/behavioral psychopathic traits represent a general risk factor for engaging in risky behavior associated with deleterious health consequences, including nicotine use. Our results hold implications for the development of treatment approaches, designed to reduce problematic levels of substance use among individuals scoring high on psychopathy.

Neural Correlates of Psychopathic Traits in Schizophrenia: fMRI Study of Response Inhibition in Persistently Violent Patients

Background and Hypothesis

Psychopathic traits play an important role in schizophrenia, particularly for violent behavior. There have been very few functional imaging studies (fMRI) examining the impact of brain dysfunction on psychopathic traits in schizophrenia. Our goal was to evaluate neural abnormalities underlying these traits through fMRI in violent subjects with schizophrenia (VS) and in 3 comparison groups: healthy controls (HC), nonviolent patients (NV), and nonpsychotic violent subjects (NPV).

Study Design

fMRI imaging was used to measure blood-oxygen-level-dependent activation in 95 subjects while they performed a Go/NoGo task: 26 VS, 25 NPV, 26 HC, and 18 NVS. Psychopathy was evaluated through the 2 factors of the Psychopathy Checklist (PCL:SV). The subjects were also evaluated for psychiatric symptoms and for educational achievement.

Study Results

Hypoactivation of brain areas involved in response inhibition was related to the severity of psychopathic traits in the violent patients with schizophrenia. These areas included frontal regions, cingulate cortex, insula, precuneus, and basal ganglia. This association was very strong for the first PCL:SV factor, the affective-interpersonal traits, and moderate for the second PCL:SV factor, the antisocial-impulsive traits. The latter traits were also linked to poor educational achievement.

Conclusions

The 2 psychopathic factors have different antecedents and are dissociable at the neural level in schizophrenia. Brain dysfunction is more strongly associated with the affective-interpersonal traits while the antisocial traits are associated with various factors. This has important implications for the conceptualization and treatment of violence in patients with schizophrenia.

Predicting criminal and violent outcomes in psychiatry: a meta-analysis of diagnostic accuracy

Although reducing criminal outcomes in individuals with mental illness have long been a priority for governments worldwide, there is still a lack of objective and highly accurate tools that can predict these events at an individual level. Predictive machine learning models may provide a unique opportunity to identify those at the highest risk of criminal activity and facilitate personalized rehabilitation strategies. Therefore, this systematic review and meta-analysis aims to describe the diagnostic accuracy of studies using machine learning techniques to predict criminal and violent outcomes in psychiatry. We performed meta-analyses using the mada, meta, and dmetatools packages in R to predict criminal and violent outcomes in psychiatric patients (n = 2428) (Registration Number: CRD42019127169) by searching PubMed, Scopus, and Web of Science for articles published in any language up to April 2022. Twenty studies were included in the systematic review. Overall, studies used single-nucleotide polymorphisms, text analysis, psychometric scales, hospital records, and resting-state regional cerebral blood flow to build predictive models. Of the studies described in the systematic review, nine were included in the present meta-analysis. The area under the curve (AUC) for predicting violent and criminal outcomes in psychiatry was 0.816 (95% Confidence Interval (CI): 70.57-88.15), with a partial AUC of 0.773, and average sensitivity of 73.33% (95% CI: 64.09-79.63), and average specificity of 72.90% (95% CI: 63.98-79.66), respectively. Furthermore, the pooled accuracy across models was 71.45% (95% CI: 60.88-83.86), with a tau squared (τ²) of 0.0424 (95% CI: 0.0184-0.1553). Based on available evidence, we suggest that prospective models include evidence-based risk factors identified in prior actuarial models. Moreover, there is a need for a greater emphasis on identifying biological features and incorporating novel variables which have not been explored in prior literature. Furthermore, available models remain preliminary, and prospective validation with independent datasets, and across cultures, will be required prior to clinical implementation. Nonetheless, predictive machine learning models hold promise in providing clinicians and researchers with actionable tools to improve how we prevent, detect, or intervene in relevant crime and violent-related outcomes in psychiatry.

Sexual homicide and the forensic process: The decision-making process of collecting and analyzing traces and its implication for crime solving

The focus of the current study is to examine the collection and analysis of traces that are related to crime scene behaviors in sexual homicide cases as well as the factors influencing the solving of these crimes. Using 230 sexual homicide cases from the SHielD database, we computed two neural network models based on the multi-layer perceptron algorithm. First, we determined whether certain crime scene characteristics predicted the collection and analysis of traces (dependent variable for Model 1). Not surprisingly, the results indicate that trace collection and analysis were more likely to occur in sexual homicide cases with crime scene behaviors exhibiting the highest risk for trace transfer (e.g. close interactions with the victim) as well as the best conditions for trace persistence (e.g. body is found indoors). Situational and physical aspects of the crime scene are thus taken into account when deciding on the collection and analysis of traces. Second, we examined the situations in which the collection and analysis of traces contributes to crime solving (dependent variable for Model 2). The results suggest that the collection and analysis of traces does not necessarily predict the resolution of the case. Specifically, the analyses show that the collection and analysis of traces is useful for crime solving when: (1) the offenders' behaviors increase the opportunities for leaving traces at the crime scene, and (2) when the environmental and temporal aspects are favorable to the collection of traces. The impact of trace collection and analysis on case resolution is thus depending on the context of the case. Furthermore, the subsequent steps, such as the result of the trace analysis, the introduction into a database, the obtention of a result from this comparison, etc. might also affect case resolution, and thus interfere in the link between trace collection and analysis and case resolution.

Identifying Predictors of Inpatient Verbal Aggression in a Forensic Psychiatric Setting Using a Tree-based Modeling Approach

Inpatient violence poses a great risk to the health and well-being of other patients and members of staff. Previous research has shown that prevalence rates of violent behavior are particularly high in forensic psychiatric settings. Thus, the reliable identification of forensic inpatients who are particularly at risk for violent behavior is an important aspect of risk management. In the present study, we analyzed clinicians' assessments of N = 504 male and female inpatients of German forensic mental health institutions in order to identify risk factors for verbal institutional violence. Using a tree-based modeling approach, we found the following variables to be predictors of verbal aggression: gender, insight into the illness, number of prior admissions to psychiatric hospitals, and insight into the iniquity of the offence. A high number of prior admissions to psychiatric hospitals seems to be a risk factor for verbal aggression amongst men whereas it showed the opposite effect amongst women. Our results highlight the importance of dynamic risk factors, such as poor insight into the own illness, in the prediction of violent incidents. With regard to future research, we argue for a stronger emphasis on nonparametric models as well as on potential interaction effects of risk and protective factors.

Differentiating Perpetrators of Intimate Partner Violence From Other Violent Offenders Using a Statistical Learning Model: The Role of Cognition and Life History Variables

Intimate partner violence (IPV) is a widespread crime that victimizes over 4-million women per year in the United States and results in significant monetary cost and unmeasured physical and psychological consequences for victims. Specialized IPV offender treatment programs demonstrate limited effectiveness, which may be due to an insufficient understanding of the factors that differentiate between IPV perpetrators and non-IPV violent offenders. In this study, we utilized classification and regression tree (CART) analysis to identify combinations of factors that best discriminate IPV perpetrators from non-IPV violent offenders. We also compared cognitive abilities between IPV perpetrators and non-IPV violent offenders using standardized neurocognitive tests. CART analysis presented two pathways for identifying offenders as IPV perpetrators: (a) extensive nonviolent criminal history and (b) moderate-to-severe expression of interpersonal traits of psychopathy without attentional deficits. In addition, a third pathway identified non-IPV violent offenders: (c) low levels of interpersonal psychopathic traits and no history of neurodevelopmental diagnosis. IPV perpetrators demonstrated intact cognition relative to test norms, and study groups did not significantly differ on cognitive performance. These findings suggest that individuals with multiple arrests for nonviolent crime or individuals with interpersonal traits of psychopathy without attentional difficulties may be at enhanced risk for IPV perpetration.

Exploring working memory, self-criticism, and rumination as factors related to self-harm

The prevalence of self-harm and the relative emotional influences are well understood, but certain cognitive factors such as working memory, rumination, and self-criticism are not fully explored. The aim of the current study is to examine specific aspects of cognition to explore their influence on self-harming behaviors. Participants included 101 undergraduates from a British University. Factors were measured using the Centre for Epidemiological Studies Depression Scale, the Depressive Experiences Questionnaire, Ruminative Response Scale, and the Automated Working Memory Assessment. Findings indicated a greater incidence of self-harming behaviors among those who demonstrated higher depressive symptoms, but depression scores were not significantly related to self-harm. Additionally, a binary logistic regression indicated that self-criticism was associated with the presence of self-harming behavior, and a Classification and Regression Trees found that the single strongest predictor of self-harming behavior was a belief that love needs to be continually earned from others. Incorporating treatments that reduce self-criticism, such as improving self-compassion with Compassionate Mind Training, may address underlying mechanisms that trigger self-harm behavior. Keywords: rumination, depression, self-criticism, working memory, self-harm.

The empirical evidence base for the use of the HCR-20: A narrative review of study designs and transferability of results to clinical practice

The HCR-20, a widely used method of assessing and managing risk, relies on the structured professional judgement approach. This paper reports a narrative literature review of the HCR-20 studies to explore the applicability of the study results to the use of the HCR-20 in clinical practice. From a literature search using terms "HCR-20" and "HCR 20", 206 papers were included. Of studies using the HCR-20 version 2 (n = 191), 92% (n = 176) relied on variables based on scores derived by adding item scores, and 50% (n = 95) tested the HCR-20 using predictive validity methodology. Of the HCR-20 version 3 studies (n = 21), the "presence of risk factors" step was the most commonly examined (n = 18, 86%), but 2 of the 7 steps ("scenario planning" and "management") were not examined at all. Amongst those studies whose primary focus was on the HCR-20, 67% (n = 64/95) did so by assessing the predictive validity of the tool. Only one employed a design to test whether the use of the HCR-20 affected violence rates. The predominant study design provides support for the use of the HCR-20 as an actuarial tool, and there is limited empirical evidence in support of its effectiveness as a structured professional judgement approach to the assessment and management of the risk of violence.

Forensic psychiatry services in Nunavut

There is a paucity of research on forensic psychiatry patients from Nunavut, including no published data concerning the prevalence and characterisation of patients in this territory. The lack of basic information hinders the evaluation of services and establishing best practices. The current paper aims to characterise forensic psychiatry patients from Nunavut and further the understanding of the challenges in organising forensic psychiatry healthcare in Nunavut. A retrospective chart review design was used to examine individuals from Nunavut who are engaged with the Ontario forensic psychiatry system. The sample included all Unfit to Stand Trial (26.7%) and Not Criminally Responsible (73.3%) patients (N = 15) under the jurisdiction of the Nunavut Review Board in a one-year period. The average distance between the patient’s place of residence in Nunavut and the Ontario facilities was 2,517 km. Overall, 26.7% were living in Nunavut, 60.0% remained in Ontario, and 13.3% resided in Alberta. Results are presented for sociodemographics, forensic status, personal and familial history, psychiatric and criminal history, diagnoses, index offence characteristics, treatment, assessment tools, and aggression. The prevalence and many characteristics of forensic psychiatry patients from Nunavut differ from the rest of Canada and have important implications for the delivery of services.

Early expressions of psychopathology and risk associated with trans-diagnostic transition to mood and psychotic disorders in adolescents and young adults

OBJECTIVES

The heterogeneity and comorbidity of major mental disorders presenting in adolescents and young adults has fostered calls for trans-diagnostic research. This study examines early expressions of psychopathology and risk and trans-diagnostic caseness in a community cohort of twins and non-twin siblings.

METHODS

Using data from the Brisbane Longitudinal Twin Study, we estimated median number of self-rated psychiatric symptoms, prevalence of subthreshold syndromes, family history of mood and/or psychotic disorders, and likelihood of subsequent trans-diagnostic caseness (individuals meeting diagnostic criteria for mood and/or psychotic syndromes). Next, we used cross-validated Chi-Square Automatic Interaction Detector (CHAID) analyses to identify the nature and relative importance of individual self-rated symptoms that predicted trans-diagnostic caseness. We examined the positive and negative predictive values (PPV; NPV) and accuracy of all classifications (Area under the Curve and 95% confidence intervals: AUC; 95% CI).

RESULTS

Of 1815 participants (Female 1050, 58%; mean age 26.40), more than one in four met caseness criteria for a mood and/or psychotic disorder. Examination of individual factors indicated that the AUC was highest for subthreshold syndromes, followed by family history then self-rated psychiatric symptoms, and that NPV always exceeded PPV for caseness. In contrast, the CHAID analysis (adjusted for age, sex, twin status) generated a classification tree comprising six trans-diagnostic symptoms. Whilst the contribution of two symptoms (need for sleep; physical activity) to the model was more difficult to interpret, CHAID analysis indicated that four self-rated symptoms (sadness; feeling overwhelmed; impaired concentration; paranoia) offered the best discrimination between cases and non-cases. These four symptoms showed different associations with family history status.

CONCLUSIONS

The findings need replication in independent cohorts. However, the use of CHAID might provide a means of identifying specific subsets of trans-diagnostic symptoms representing clinical phenotypes that predict transition to caseness in individuals at risk of onset of major mental disorders.

Psychopathy and Associated Factors Among Newly Admitted Prisoners in Correctional Institution Located in Bench Sheko and West Omo Zone, South West Ethiopia: A Cross-Sectional Study

Background

Psychopathy is an emerging health and behavioral problem worldwide. Psychopathy is linked to risk substance use, maltreatment, violence, crime, and reoffending, but little is known about psychopathy in low income countries like Ethiopia. Therefore, we assessed the prevalence and factors associated with psychopathy among newly-admitted prisoners in Bench Sheko and West Omo zone correctional center, Mizan Aman, Ethiopia.

Methods

A cross-sectional study was conducted from April 20 to July 19, 2019, among 411 (N=422) newly-admitted Bench Sheko and West Omo zone correctional center prisoners by using a consecutive sampling technique. A semi-structured and interviewer administered psychopathy checklist revised tool was used for screening psychopathy. WHO, ASSIST tool was used for screening risk use of khat, tobacco, and alcohol. Trauma, maltreatment, and social support were assessed with a life event checklist, adverse life experience screening tool, and Oslo social support scale, respectively. In addition, Criminal and clinical history of the prisoner was also assessed. The data was entered into Epi-data 3.1 and exported to Statistical Package for Social Science (SPSS) Version 21 for statistical analysis. A logistic regression model was used. Variables with a p-value less than 0.05 in the final fitting model were declared as independent predictors of psychopathy.

Results

The prevalence of psychopathy was 24.3%. Childhood maltreatment (AOR=6, 95% CI=2.2–17.5), risky khat use (AOR=4.6, 95% CI=2.4–8.7), poor social support (AOR=3.5, 95% CI=1.9–6.6), family history of imprisonment (AOR=3, 95% CI=1.5–6), history of trauma (AOR=2.3, 95% CI=1.1–4.8), and reoffending (AOR=2, 95% CI=1.1–3.8) were positively associated variables with psychopathy.

Conclusion

Psychopathy is highly prevalent among newly-admitted prisoners. Integrated efforts involving relevant stakeholders are needed to design strategies for early screening of psychopathy to prevent reoffending, and management of risk substance use at admission is crucial.

Incipient offending among schizophrenia patients after first contact to the psychiatric hospital system

The study examines how age, sex and substance use disorder are associated with the risk of committing a criminal offence. The study explicitly examines the risk after the first contact to the psychiatric hospital system and after the diagnosis of schizophrenia for those with no previous criminal record; the association between previous non-violent criminality and later violent criminality is also analysed. The study sample comprised 4619 individuals ever diagnosed with schizophrenia. All solved offences were accessible. Data were analysed using Cox's regression. Schizophrenic men had twice the risk of schizophrenic women of committing both violent and non-violent offences. A registered substance use disorder increased the risk 1.9- to 3.7-fold, depending on the starting point for the analyses, while increasing age on first contact or when diagnosed with schizophrenia diminished the risk. Previous non-violent criminality increased the risk for later violent criminality 2.5- to 2.7-fold, depending on the starting point for the analyses. The results suggest that the psychiatric treatment system can play an active role in preventing criminality among individuals with schizophrenia. The preventive measures should be based on a thorough assessment including criminal history at intake and alertness toward young psychotic men with substance use disorders and especially if they also have a criminal history.

A cross-sectional study of psychopathy and khat abuse among prisoners in the correctional institution in Jimma, Ethiopia

Background

Khat abuse and psychopathy are both strongly related to criminal activity. Higher rates of substance use in people with psychopathy are hypothesized to be related to psychopathic personality traits, which include high sensation seeking, low conscientiousness and neuroticism, impulsivity, and irresponsibility. Little is known, however, about the association between psychopathy and khat abuse among prisoners in Ethiopia. Therefore, we evaluated the presence of these two factors in prisoners in the correctional institution in Jimma, Southwest Ethiopia.

Materials and methods

We used a cross-sectional study design to collect data from 336 prisoners from June 5 to July 5, 2017. Study participants were selected by a systematic random sampling technique. Khat abuse was assessed with the Drug Abuse Screening Tool and psychopathy with the Psychopathy Checklist: Screening Version. We also assessed nicotine dependence with the Fagerstrom Test for Nicotine Dependence; alcohol use disorder, with the alcohol use disorder identification test; adverse traumatic life events, with the Life Events Checklist; and social support, with the Oslo 3-Item Social Support Scale. Data were entered into EpiData version 3.1 and analyzed in bivariate and multivariable logistic regression models. Variables with a P value < 0.05 in the final fitted model were declared to be significantly associated with the outcome variable.

Results

The overall prevalence of lifetime khat use was 59.9%, and the prevalence of khat abuse in prisoners with psychopathy was 78.0%. Prisoners with psychopathy had a three times higher odds ratio of abusing khat than those without psychopathy (AOR = 3.00 [1.17–7.67]). Among the confounders, a family history of substance use (AOR = 2.50 [1.45–4.31]), poor support (AOR = 2.28 [1.11–4.67]), alcohol use disorder (AOR = 7.78 [4.16–14.53]), and suicidal ideation and suicide attempts (AOR = 2.26 [1.45–4.31]) were also positively associated with khat abuse.

Conclusions

The prevalence of khat abuse was higher in prisoners with possible or probable psychopathy.

The Classification of Violence Risk

(Reprinted with permission from Behav. Sci. Law 24: 721-730, 2006).

Callous-Unemotional Traits Modulate Brain Drug Craving Response in High-Risk Young Offenders

Adults with psychopathy have a high propensity for substance abuse, generally starting from a young age. This investigation tested hypotheses about differences in the neural responses associated with drug craving among high-risk young offenders with histories of abuse of stimulants and other drugs as a function of psychopathic traits. Fifty-four male adolescents (44 with a history of stimulant abuse and 10 controls) incarcerated at a maximum-security facility (M age = 17.08 years) completed a drug-cue exposure task while brain hemodynamic activity was monitored using functional magnetic resonance imaging (fMRI) with a mobile MRI scanner stationed at the facility. Psychopathic traits were assessed using the Hare Psychopathy Checklist: Youth Version (PCL:YV). In the stimulant abuser group, drug cues elicited activity in classic reward circuitry. Consistent with studies of adult psychopathic traits and substance abuse, there was a negative association between PCL-YV scores and hemodynamic response related to drug craving in the amygdala and ACC in youth with a history of stimulant abuse. However, there were considerably more negative associations between the PCL:YV and hemodynamic response among youth than adults and this was primarily due to callous-unemotional traits rather than interpersonal or behavioral traits. The implications for how personality traits modulate motivations for drug-seeking behavior among adolescent offenders are discussed.

A retrospective analysis of determinants of involuntary psychiatric in-patient treatment

BACKGROUND

The purpose of our study was to identify predictors of a high risk of involuntary psychiatric in-patient treatment.

METHODS

We carried out a detailed analysis of the 1773 mental health records of all the persons treated as in-patients under the PsychKG NRW (Mental Health Act for the state of North Rhine-Westphalia, Germany) in a metropolitan region of Germany (the City of Cologne) in 2011. 3991 mental health records of voluntary in-patients from the same hospitals served as a control group. We extracted medical, sociodemographic and socioeconomic data from these records. Apart from descriptive statistics, we used a prediction model employing chi-squared automatic interaction detection (CHAID).

RESULTS

Among involuntary patients, organic mental disorders (ICD10: F0) and schizophrenia and other psychotic disorders (ICD10: F2) were overrepresented. Patients treated as in-patients against their will were on average older, they were more often retired and had a migratory background. The Exhaustive CHAID analysis confirmed the main diagnosis to be the strongest predictor of involuntary in-patient psychiatric treatment. Other predictors were the absence of outpatient treatment prior to admission, admission outside of regular service hours and migratory background. The highest risk of involuntary treatment was associated with patients with organic mental disorders (ICD 10: F0) who were married or widowed and patients with non-organic psychotic disorders (ICD10: F2) or mental retardation (ICD10: F7) in combination with a migratory background. Also, referrals from general hospitals were frequently encountered.

CONCLUSIONS

We identified modifiable risk factors for involuntary psychiatric in-patient treatment. This implies that preventive measures may be feasible and should be implemented to reduce the rate of involuntary psychiatric in-patient treatment. This may include efforts to establish crisis resolution teams to improve out-patient treatment, train general hospital staff in deescalation techniques, and develop special programs for patients with a migratory background.

Testing the properties of the triarchic model of psychopathy in a community sample: Self-reported trait aggression and drug consumption associations

The triarchic model of psychopathy encompasses different conceptions of psychopathic personality characterized by three phenotypic components: boldness, disinhibition, and meanness. Psychopathy is a complex construct at both emotional and behavioral level. The aim of this study was to determine the core elements of psychopathic personality in a community sample and analyze the relation between these elements and other personality traits such as aggression, and certain specific behavioral manifestations such as substance use. The study sample comprised 1,159 participants aged between 17 and 74 years, who were administered the Triarchic Psychopathy Questionnaire, the Impulsive-Premeditated Aggression Scale, and the Aggression Questionnaire. The results show that the constructs of meanness and disinhibition are more highly associated with different forms of both impulsive and premeditated aggression. Furthermore, men scored higher on all three components of the triarchic model compared to women. Finally, higher substance use (tobacco and drugs) was associated with higher scores in meanness, boldness, and disinhibition. These findings demonstrate the importance of assessing psychopathy in a community sample, and the detection of possible risk factors for the disorder.

Optimizing predictive performance of criminal recidivism models using registration data with binary and survival outcomes

In a recidivism prediction context, there is no consensus on which modeling strategy should be followed for obtaining an optimal prediction model. In previous papers, a range of statistical and machine learning techniques were benchmarked on recidivism data with a binary outcome. However, two important tree ensemble methods, namely gradient boosting and random forests were not extensively evaluated. In this paper, we further explore the modeling potential of these techniques in the binary outcome criminal prediction context. Additionally, we explore the predictive potential of classical statistical and machine learning methods for censored time-to-event data. A range of statistical manually specified statistical and (semi-)automatic machine learning models is fitted on Dutch recidivism data, both for the binary outcome case and censored outcome case. To enhance generalizability of results, the same models are applied to two historical American data sets, the North Carolina prison data. For all datasets, (semi-) automatic modeling in the binary case seems to provide no improvement over an appropriately manually specified traditional statistical model. There is however evidence of slightly improved performance of gradient boosting in survival data. Results on the reconviction data from two sources suggest that both statistical and machine learning should be tried out for obtaining an optimal model. Even if a flexible black-box model does not improve upon the predictions of a manually specified model, it can serve as a test whether important interactions are missing or other misspecification of the model are present and can thus provide more security in the modeling process.

Characteristics of a suicide attempt predict who makes another attempt after hospital discharge: A decision-tree investigation

The year following discharge from psychiatric hospitalization is a high-risk period for suicidal behavior, particularly among patients initially hospitalized after a suicide attempt. Demographic and clinical correlates have been identified; however, characteristics of the initial attempt may provide insight into risk for subsequent attempts as well. This investigation examined whether individual or a combination of suicide attempt characteristics predicted future attempts. Two hundred and eighteen psychiatric inpatients from the MacArthur Violence Risk Assessment Study with a recent suicide attempt were administered items from the Suicide Intent Scale and followed one year after discharge. Sixty-nine (31.65%) made a subsequent attempt. Data were analyzed by a stepwise logistic regression, followed by an iterative receiver operator curve (IROC) analysis, a recursive partitioning classification tree. The cross-validated IROC, but not logistic regression, predicted subsequent suicide attempts. Furthermore, the IROC found that participants who made definite plans and underwent extensive preparation were at highest risk for subsequent attempts. These findings suggest that suicide attempt characteristics preceding psychiatric hospitalization can help identify patients at elevated risk for another attempt post-discharge.

Hopelessness, life dissatisfaction and boredom among older people

Identifying frail older people, and in particular, people who are psychologically frail in a community setting is difficult. This article investigates predictors of psychological frailty and constructs a short and effective pre-detection tool for highly psychologically frail older people. The Belgian Ageing Studies, a cross-sectional study (n=28.245) was used. Measures included four items of the Geriatric Depression Scale, the psychological domain of the Comprehensive Frailty Assessment Instrument. First bivariate analyses were used. Afterwards, Chi-squared automatic interaction detector (CHAID) analysis was applied to gain an insight into the hierarchical order of predictors for high psychological frailty. Findings indicate that the combination of hopelessness and life dissatisfaction predicts high psychological frailty in 68.4% of cases. Early detection of frailty offers opportunities to start early interventions, and can delay or reduce frailty. In order to detect older people who are psychologically frail, a simple two question pre-detection tool was developed. To conclude: if a patient answers 'yes' to feeling hopeless and 'no' to having life satisfaction, this predicts with great probability (68.4%) high psychological frailty.

Effects of social support and resilient coping on violent behavior in military veterans

Violence toward others has been identified as a serious postdeployment adjustment problem in a subset of Iraq- and Afghanistan-era veterans. In the current study, we examined the intricate links between posttraumatic stress disorder (PTSD), commonly cited psychosocial risk and protective factors, and violent behavior using a national randomly selected longitudinal sample of Iraq- and Afghanistan-era United States veterans. A total of 1,090 veterans from the 50 United States and all United States military branches completed 2 waves of self-report survey-data collection 1 year apart (retention rate = 79%). History of severe violent behavior at Wave 1 was the most substantial predictor of subsequent violence. In bivariate analyses, high correlations were observed among risk and protective factors, and between risk and protective factors and severe violence at both time points. In multivariate analyses, baseline violence (OR = 12.43, p < .001), baseline alcohol misuse (OR = 1.06, p < .05), increases in PTSD symptoms between Waves 1 and 2 (OR = 1.01, p < .05), and decreases in social support between Waves 1 and 2 (OR = .83, p < .05) were associated with increased risk for violence at Wave 2. Our findings suggest that rather than focusing specifically on PTSD symptoms, alcohol use, resilience, or social support in isolation, it may be more useful to consider how these risk and protective factors work in combination to convey how military personnel and veterans are managing the transition from wartime military service to civilian life, and at what point it might be most effective to intervene. (PsycINFO Database Record

The use of model based recursive partitioning as an analytic tool in child welfare

Child welfare agencies are tasked with investigating allegations of child maltreatment and intervening when necessary. Researchers are turning to the field of predictive analytics to optimize data analysis and data-driven decision making. To demonstrate the utility of statistical algorithms that preceded the current predictive analytics, we used Model Based (MOB) recursive partitioning, a variant of regression analysis known as decision trees, on a dataset of cases and controls with a binary outcome of serious maltreatment (defined as hospitalization or death). We ran two models, one which split a robust set of variables significantly correlated with the outcome on the partitioning of a proxy variable for environmental poverty, and one which ran the same variable set partitioned on a variable representing confirmed prior maltreatment. Both models found that what most differentiated children was spending greater than 2% of the timeframe of interest in foster care, and that for some children, lack of Medicaid eligibility almost doubled or tripled the odds of serious maltreatment. We find that decision trees such as MOB can augment risk assessment tools and other data analyses, informing data-driven program and policy decision making. We caution that decision trees, as with any other predictive tool, must be evaluated for inherent biases that may be contained in the proxy variables and the results interpreted carefully. Predictive analytics, as a class, should be used to augment, but not replace, critical thinking in child welfare decision making.

Psychopathy, Antisocial Personality Disorder, and Reconviction in an Australian Sample of Forensic Patients

This study identified the presence of psychopathy (as measured by the PCL-R/PCL:SV instruments) and antisocial personality disorder (APD) and their relationship with future reconviction in an Australian forensic sample ( N = 136) of patients with a mental disorder. Patients were tracked for over 4 years postrelease to determine associations between a diagnosis of APD/psychopathy and reoffense. Patients with higher psychopathy scores were found to have an increased likelihood of reincarceration, a higher rate of reconviction, and were reconvicted earlier compared with patients with lower psychopathy scores. Patients with APD were more likely to be reconvicted and reincarcerated during the follow-up period than patients without an APD diagnosis. Despite demonstrating associations with general reconviction, the PCL instruments did not exhibit statistically significant relationships with violence. Implications for the clinical identification of personality disordered patients in forensic settings are discussed.

Probability and loss: two sides of the risk assessment coin

Risk assessment has been widely adopted in mental health settings in the hope of preventing harms such as violence to others and suicide. However, risk assessment in its current form is mainly concerned with the probability of adverse events, and does not address the other component of risk – the extent of the resulting loss. Although assessments of the probability of future harm based on actuarial instruments are generally more accurate than the categorisations made by clinicians, actuarial instruments are of little assistance in clinical decision-making because there is no instrument that can estimate the probability of all the harms associated with mental illness, or estimate the extent of the resulting losses. The inability of instruments to distinguish between the risk of common but less serious harms and comparatively rare catastrophic events is a particular limitation of the value of risk categorisations. We should admit that our ability to assess risk is severely limited, and make clinical decisions in a similar way to those in other areas of medicine – by informed consideration of the potential consequences of treatment and non-treatment.

Categorization and Prediction of Crimes of Passion Based on Attitudes Toward Violence

The present study explored implicit and explicit attitudes toward violence in crimes of passion. Criminals ( n = 96) who had perpetrated crimes of passion and students ( n = 100) participated in this study. Explicit attitudes toward violence were evaluated using the Abnormal Personality Risk Inventory (APRI), and implicit attitude toward violence was evaluated using the Implicit Association Test (IAT). Results indicated that APRI scores of the perpetrators were significantly higher than that of the control group ( p < .05), suggesting that explicit attitudes toward violence could discriminate between the criminals and the control group. There was a significant IAT effect demonstrating a negative implicit attitude toward violence in both the control group and in the criminals ( n = 68); whereas there was a significant IAT effect manifesting a positive implicit attitude toward violence in the criminals ( n = 16) only. These results suggest that combining explicit and implicit attitudes could provide an empirical classification of crimes of passion.

Psychopathological features in a sample of substance-abusing individuals with criminal history: Towards a definition of a personality prototype of an 'Addict with Criminal Conduct'

BACKGROUND

The relationship between substance use disorders and criminal activity is strong, and one that is not easily resolved in the criminal justice system. A better understanding of personality traits among substance misusers who commit offences could support better treatment efforts.

AIMS

The aim of this study is to explore associations between the psychopathology of people addicted to substances who have also committed crimes.

METHODS

We recruited 263 substance-dependent individuals (80% male, 20% female) from a cohort of people attending regional community services in Italy. They all completed an extensive evaluation of their current mental health and personality traits. Their official criminal records were obtained, and the psychopathology of those who had a criminal record compared with those who did not.

RESULTS

The criminal group was more likely to perceive the external world as hostile and to consider others as responsible for their own problems and difficulties; in addition, substance-dependent individuals with criminal records showed more personality traits within the psychopathy range and fewer in the dependent personality range than the substance abusers who had never committed crimes.

CONCLUSIONS

These findings allow us to hypothesise that substance abusers who also have criminal convictions may have a specific personality profile. If further research were to confirm this, then it could have important implications for identifying people for particular treatment pathways and developing more effective treatments. Copyright © 2016 John Wiley & Sons, Ltd.

Traumatic Brain Injury in Iraq and Afghanistan Veterans: New Results From a National Random Sample Study

This study randomly sampled post-9/11 military veterans and reports on causes, predictors, and frequency of traumatic brain injury (TBI) (N=1,388). A total of 17.3% met criteria for TBI during military service, with about one-half reporting multiple head injuries, which were related to higher rates of posttraumatic stress disorder, depression, back pain, and suicidal ideation. The most common mechanisms of TBI included blasts (33.1%), objects hitting head (31.7%), and fall (13.5%). TBI was associated with enlisted rank, male gender, high combat exposure, and sustaining TBI prior to military service. Clinical and research efforts in veterans should consider TBI mechanism, effects of cumulative TBI, and screening for premilitary TBI.

China PEACE risk estimation tool for in-hospital death from acute myocardial infarction: an early risk classification tree for decisions about fibrinolytic therapy

OBJECTIVES

As the predominant approach to acute reperfusion for ST segment elevation myocardial infarction (STEMI) in many countries, fibrinolytic therapy provides a relative risk reduction for death of ∼16% across the range of baseline risk. For patients with low baseline mortality risk, fibrinolytic therapy may therefore provide little benefit, which may be offset by the risk of major bleeding. We aimed to construct a tool to determine if it is possible to identify a low-risk group among fibrinolytic therapy-eligible patients.

DESIGN

Cross-sectional study.

SETTING

The China Patient-centered Evaluative Assessment of Cardiac Events (PEACE) study includes a nationally representative retrospective sample of patients admitted with acute myocardial infarction (AMI) in 162 hospitals.

PARTICIPANTS

3741 patients with STEMI who were fibrinolytic-eligible but did not receive reperfusion therapy.

MAIN OUTCOME MEASURES

In-hospital mortality, which was defined as a composite of death occurring within hospitalisation or withdrawal from treatment due to a terminal status at discharge.

RESULTS

In the study cohort, the in-hospital mortality was 14.7%. In the derivation cohort and the validation cohort, the combination of systolic blood pressure (≥100 mm Hg), age (<60 years old) and gender (male) identified one-fifth of the cohort with an average mortality rate of <3.0%. Half of this low risk group-those with non-anterior AMI-had an average in-hospital death risk of 1.5%.

CONCLUSIONS

Nearly, one in five patients with STEMI who are eligible for fibrinolytic therapy are at a low risk for in-hospital death. Three simple factors available at the time of presentation can identify these individuals and support decision-making about the use of fibrinolytic therapy.

TRIAL REGISTRATION NUMBER

NCT01624883.

Assessing Recidivism Risk Among Young Offenders

The development of a recidivism risk index for use with young offenders is described. A construction sample was drawn from the first 458 incarcerated youths in South Australia approached to undertake a routine standardised psychosocial screening. Items that met the selection criteria for the risk index were number of prior proven offences, current age, age at first offence, alcohol and inhalant use frequencies, and ADHD signs. The resulting index had significant correlations (.28–.53) with 6-month postrelease recidivism status among various assessment, age, gender and ethnic subgroups. A correlation of .36 was obtained between the index and 6-month postrelease recidivism status with an independent sample of 149 incarcerated youths. The results compare well with the predictive validities reported elsewhere for other risk instruments. An important use for the index could be to guide more intensive services toward those who are at highest risk of reoffending.

Identifying Risk and Protective Factors in Recidivist Juvenile Offenders: A Decision Tree Approach

Research on juvenile justice aims to identify profiles of risk and protective factors in juvenile offenders. This paper presents a study of profiles of risk factors that influence young offenders toward committing sanctionable antisocial behavior (S-ASB). Decision tree analysis is used as a multivariate approach to the phenomenon of repeated sanctionable antisocial behavior in juvenile offenders in Spain. The study sample was made up of the set of juveniles who were charged in a court case in the Juvenile Court of Almeria (Spain). The period of study of recidivism was two years from the baseline. The object of study is presented, through the implementation of a decision tree. Two profiles of risk and protective factors are found. Risk factors associated with higher rates of recidivism are antisocial peers, age at baseline S-ASB, problems in school and criminality in family members.

A Literature Review of the Utility of Selected Violence and Sexual Violence Risk Assessment Instruments

The rationale for this article is to comprehensively outline and describe the strengths and weaknesses of various risk assessment instruments/tools relevant to the evaluation of sexually violent and violent offenders. The author will briefly discuss ethical obligations the forensic mental health professional (FMHP) must consider when conducting risk assessments.

An Actuarial Model for Assessment of Prison Violence Risk Among Maximum Security Inmates

An experimental scale for the assessment of prison violence risk among maximum security inmates was developed from a logistic regression analysis involving inmates serving parole-eligible terms of varying length (n = 1,503), life-without-parole inmates (n = 960), and death-sentenced inmates who were mainstreamed into the general prison population (n = 132). Records of institutional violent misconduct of these 2,595 inmates were retrospectively examined for an 11-year period (1991 to 2002). Predictors affecting the likelihood of such misconduct included age, type and length of sentence, education, prior prison terms, prior probated sentences, and years served. The scale was modestly successful, as demonstrated by an overall omnibus area under the curve of .719. Double cross-validation demonstrated minimal shrinkage. The authors have termed this experimental scale the Risk Assessment Scale for Prison.

The Development and Validation of an Actuarial Risk Assessment Tool for the Prediction of First-Time Offending

For prevention purposes, it is important that police officers can estimate the risk for delinquency among juveniles who were involved in a criminal offense, but not in the role of a suspect. In the present study, the Youth Actuarial Risk Assessment Tool for First-Time Offending (Y-ARAT-FO) was developed based solely on police records with the aim to enable Dutch police officers to predict the risk for first-time offending. For the construction of this initial screening instrument, an Exhaustive Chi-squared Automatic Interaction Detector (Exhaustive CHAID) analysis was performed on a data set that was retrieved from the Dutch police system. The Y-ARAT-FO was developed on a sample of 1,368 juveniles and validated on a different sample of 886 juveniles showing moderate predictive accuracy in the validation sample (area under the receiver operating characteristic curve [AUC] = .728). The predictive accuracy of the Y-ARAT-FO was considered sufficient to justify its use as an initial screening instrument by the Dutch police.

A decision-tree approach to the assessment of posttraumatic stress disorder: Engineering empirically rigorous and ecologically valid assessment measures

Structured diagnostic interviews are widely considered to be the optimal method of assessing symptoms of posttraumatic stress; however, few clinicians report using structured assessments to guide clinical practice. One commonly cited impediment to these assessment approaches is the amount of time required for test administration and interpretation. Empirically keyed methods to reduce the administration time of structured assessments may be a viable solution to increase the use of standardized and reliable diagnostic tools. Thus, the present research conducted an initial feasibility study using a sample of treatment-seeking military veterans (N = 1,517) to develop a truncated assessment protocol based on the Clinician-Administered Posttraumatic Stress Disorder (PTSD) Scale (CAPS). Decision-tree analysis was utilized to identify a subset of predictor variables among the CAPS items that were most predictive of a diagnosis of PTSD. The algorithm-driven, atheoretical sequence of questions reduced the number of items administered by more than 75% and classified the validation sample at 92% accuracy. These results demonstrated the feasibility of developing a protocol to assess PTSD in a way that imposes little assessment burden while still providing a reliable categorization.

Detection of unsafety in families with parental and/or child developmental problems at the start of family support

BACKGROUND

Risk assessment is crucial in preventing child maltreatment as it can identify high-risk cases in need of child protection intervention. Despite this importance, there have been no validated risk assessment instruments available in the Netherlands for assessing the risk of child maltreatment. Therefore, the predictive validity of the California Family Risk Assessment (CFRA) was examined in Dutch families who received family support. In addition, the added value of a number of experimental items was examined. Finally, it was examined whether the predictive value of the instrument could be improved by modifying the scoring procedure.

METHODS

Dutch families who experienced parenting and/or child developmental problems and were referred by the Centres for Youth and Family for family support between July 2009 and March 2011 were included. This led to a sample of 491 families. The predictive validity of the CFRA and the added value of the experimental items were examined by calculating AUC values. A CHAID analysis was performed to examine whether the scoring procedure could be improved.

RESULTS

About half of the individual CFRA items were not related to future reports of child maltreatment. The predictive validity of the CFRA in predicting future reports of child maltreatment was found to be modest (AUC = .693). The addition of some of the experimental items and the modification of the scoring procedure by including only items that were significantly associated with future maltreatment reports resulted in a 'high' predictive validity (AUC = .795).

CONCLUSIONS

This new set of items might be a valuable instrument that also saves time because only variables that uniquely contribute to the prediction of future reports of child maltreatment are included. Furthermore, items that are perceived as difficult to assess by professionals, such as parental mental health problems or parents' history of abuse/neglect, could be omitted without compromising predictive validity. However, it is important to examine the psychometric properties of this new set of items in a new dataset.

Posttraumatic Stress Disorder, Hostile Cognitions and Aggression in Iraq/Afghanistan Era Veterans

OBJECTIVE

Most veterans with posttraumatic stress disorder (PTSD) are not violent, yet research has demonstrated that there is a substantial minority who are at increased risk. This study tested hypotheses regarding hyperarousal symptoms and hostile cognitions (i.e., "hostility") as potential mechanisms of the association between PTSD and physical aggression in a longitudinal sample of Iraq/Afghanistan era veterans.

METHOD

The sample included U.S. veterans between the ages of 18 and 70 who served in the military after September 11, 2001. At baseline, 301 veterans were evaluated for PTSD and completed self-report measures of hostility. At six-month follow-up 275 veterans and their family members or friends reported on the veterans' physical aggression over the preceding interval. Regression models were used to evaluate relationships among PTSD status, hyperarousal cluster symptoms, and hostility at baseline, and physical aggression at six months. Bootstrapping was used to test for the mediation of baseline PTSD and six-month aggression by hostility.

RESULTS

PTSD significantly predicted physical aggression over six months, but hyperarousal cluster symptoms did not account for unique variance among the three clusters in the longitudinal model. Hostility partially mediated the association of PTSD at baseline and physical aggression at six months.

CONCLUSIONS

Hostility may be a mechanism of the association of PTSD and physical aggression in veterans, suggesting the potential utility of targeting hostile cognitions in therapy for anger and aggression in veterans with PTSD.

Inpatient aggression in community hospitals

Physical violence is a frequent occurrence in acute community psychiatry units worldwide. Violent acts by patients cause many direct injuries and significantly degrade quality of care. The most accurate tools for predicting near-term violence on acute units rely on current clinical features rather than demographic risk factors. The efficacy of risk assessment strategies to lower incidence of violence on acute units is unknown. A range of behavioral and psychopharmacologic treatments have been shown to reduce violence among psychiatric inpatients.

The development and validation of the Youth Actuarial Care Needs Assessment Tool for Non-Offenders (Y-ACNAT-NO)

BACKGROUND

In The Netherlands, police officers not only come into contact with juvenile offenders, but also with a large number of juveniles who were involved in a criminal offense, but not in the role of a suspect (i.e., juvenile non-offenders). Until now, no valid and reliable instrument was available that can be used by Dutch police officers for estimating the risk for future care needs of juvenile non-offenders. In the present study, the Youth Actuarial Care Needs Assessment Tool for Non-Offenders (Y-ACNAT-NO) was developed for predicting the risk for future care needs that consisted of (1) a future supervision order as imposed by a juvenile court judge and (2) future worrisome incidents involving child abuse, domestic violence/strife, and/or sexual offensive behavior at the juvenile's living address (i.e., problems in the child-rearing environment).

METHODS

Police records of 3,200 juveniles were retrieved from the Dutch police registration system after which the sample was randomly split in a construction (n = 1,549) and validation sample (n = 1,651). The Y-ACNAT-NO was developed by performing an Exhaustive CHAID analysis using the construction sample. The predictive validity of the instrument was examined in the validation sample by calculating several performance indicators that assess discrimination and calibration.

RESULTS

The CHAID output yielded an instrument that consisted of six variables and eleven different risk groups. The risk for future care needs ranged from 0.06 in the lowest risk group to 0.83 in the highest risk group. The AUC value in the validation sample was .764 (95% CI [.743, .784]) and Sander's calibration score indicated an average assessment error of 3.74% in risk estimates per risk category.

CONCLUSIONS

The Y-ACNAT-NO is the first instrument that can be used by Dutch police officers for estimating the risk for future care needs of juvenile non-offenders. The predictive validity of the Y-ACNAT-NO in terms of discrimination and calibration was sufficient to justify its use as an initial screening instrument when a decision is needed about referring a juvenile for further assessment of care needs.

Screening for violence risk in military veterans: predictive validity of a brief clinical tool

OBJECTIVE

Violence toward others is a serious problem among a subset of military veterans. The authors evaluated the predictive validity of a brief decision support tool to screen veterans for problems with violence and identify potential candidates for a comprehensive risk assessment.

METHOD

Data on risk factors at an initial wave and on violent behavior at 1-year follow-up were collected in two independent sampling frames: a national random-sample survey of 1,090 Iraq and Afghanistan veterans and in-depth assessments of 197 dyads of veterans and collateral informants. Risk factors (lacking money for basic needs, combat experience, alcohol misuse, history of violence and arrests, and anger associated with posttraumatic stress disorder) were chosen based on empirical support in published research. Scales measuring these risk factors were examined, and items with the most robust statistical association with outcomes were selected for the screening tool. Regression analyses were used to derive receiver operating characteristic curves of sensitivities and specificities, with area under the curve providing an index of predictive validity.

RESULTS

The resultant 5-item screening tool, called the Violence Screening and Assessment of Needs (VIO-SCAN), yielded area-under-the-curve statistics ranging from 0.74 to 0.78 for the national survey and from 0.74 to 0.80 for the in-depth assessments, depending on level of violence analyzed.

CONCLUSIONS

Although the VIO-SCAN does not constitute a comprehensive violence risk assessment and cannot replace fully informed clinical decision making, it is hoped that the screen will provide clinicians with a rapid, systematic method for identifying veterans at higher risk of violence, prioritizing those in need a full clinical workup, structuring review of empirically supported risk factors, and developing plans collaboratively with veterans to reduce risk and increase successful reintegration in the community.

Violent behaviour and post-traumatic stress disorder in US Iraq and Afghanistan veterans

BACKGROUND

Violence towards others in the community has been identified as a significant problem for a subset of Iraq and Afghanistan veterans.

AIMS

To investigate the extent to which post-traumatic stress disorder (PTSD) and other risk factors predict future violent behaviour in military veterans.

METHOD

A national, multiwave survey enrolling a random sample of all US veterans who served in the military after 11 September 2001 was conducted. A total of 1090 veterans from 50 US states and all military branches completed two survey waves mailed 1 year apart (retention rate = 79%).

RESULTS

Overall, 9% endorsed engaging in severe violence and 26% in other physical aggression in the previous year, as measured at Wave 2. Younger age, financial instability, history of violence before military service, higher combat exposure, PTSD, and alcohol misuse at Wave 1 were significantly associated with higher severe violence and other physical aggression in the past year at Wave 2. When combinations of these risk factors were present, predicted probability of violence in veterans rose sharply. Veterans with both PTSD and alcohol misuse had a substantially higher rate of subsequent severe violence (35.9%) compared with veterans with alcohol misuse without PTSD (10.6%), PTSD without alcohol misuse (10.0%) or neither PTSD nor alcohol misuse (5.3%). Using multiple regression, we found that veterans with PTSD and without alcohol misuse were not at significantly higher risk of severe violence than veterans with neither PTSD nor alcohol misuse. There was a trend for other physical aggression to be higher in veterans with PTSD without alcohol misuse.

CONCLUSIONS

Co-occurring PTSD and alcohol misuse was associated with a marked increase in violence and aggression in veterans. Compared with veterans with neither PTSD nor alcohol misuse, veterans with PTSD and no alcohol misuse were not significantly more likely to be severely violent and were only marginally more likely to engage in other physical aggression. Attention to cumulative effects of multiple risk factors beyond diagnosis--including demographics, violence history, combat exposure, and veterans' having money to cover basic needs like food, shelter, transportation, and medical care--is crucial for optimising violence risk management.

Identifying young adults at risk of Medicaid enrollment lapses after inpatient mental health treatment

OBJECTIVE

This study sought to describe Medicaid disenrollment rates and risk factors among young adults after discharge from inpatient psychiatric treatment.

METHODS

The sample included 1,176 Medicaid-enrolled young adults ages 18 to 26 discharged from inpatient psychiatric care in a mid-Atlantic state. Medicaid disenrollment in the 365 days postdischarge and disenrollment predictors from the 180-day predischarge period (antecedent period) were identified from administrative records. Classification and regression tree and probit regression analysis were used.

RESULTS

Thirty-two percent were disenrolled from Medicaid within a year of discharge. Both analytical approaches converged on four main risk factors: being in the Medicaid enrollment category for persons with a nondisabled low-income parent or for a child in a low-income household, being age 18 or 20 at discharge, having a Medicaid enrollment gap in the antecedent period, and having no primary care utilization in the antecedent period. For the 48% of the sample continuously enrolled in the antecedent period who were in the enrollment categories for disabled adults or foster care children, the disenrollment rate was 13%.

CONCLUSIONS

A substantial minority of Medicaid-enrolled young adults discharged from inpatient care were disenrolled from Medicaid within a year. About half the sample had a low disenrollment risk, but the other half was at substantial risk. Risk factors largely reflected legal status changes that occur among these transition-age youths. Identifying inpatients at high risk of disenrollment and ensuring continuous coverage should improve access to needed postdischarge supports. Regular primary care visits may also help reduce unintended Medicaid disenrollment in this population.

Psychopathic traits modulate brain responses to drug cues in incarcerated offenders

Recent neuroscientific evidence indicates that psychopathy is associated with abnormal function and structure in limbic and paralimbic areas. Psychopathy and substance use disorders are highly comorbid, but clinical experience suggests that psychopaths abuse drugs for different reasons than non-psychopaths, and that psychopaths do not typically experience withdrawal and craving upon becoming incarcerated. These neurobiological abnormalities may be related to psychopaths' different motivations for—and symptoms of—drug use. This study examined the modulatory effect of psychopathic traits on the neurobiological craving response to pictorial drug stimuli. Drug-related pictures and neutral pictures were presented and rated by participants while hemodynamic activity was monitored using functional magnetic resonance imaging. These data were collected at two correctional facilities in New Mexico using the Mind Research Network mobile magnetic resonance imaging system. The sample comprised 137 incarcerated adult males and females (93 females) with histories of substance dependence. The outcome of interest was the relation between psychopathy scores (using the Hare Psychopathy Checklist-Revised) and hemodynamic activity associated with viewing drug-related pictures vs. neutral pictures. There was a negative association between psychopathy scores and hemodynamic activity for viewing drug-related cues in the anterior cingulate, posterior cingulate, hippocampus, amygdala, caudate, globus pallidus, and parts of the prefrontal cortex. Psychopathic traits modulate the neurobiological craving response and suggest that individual differences are important for understanding and treating substance abuse.