Measurement of Change in Dynamic Factors Using the START:AV.

Historical approaches to violence risk assessment emphasized prediction of future violence and focused on static or historical risk factors. Consideration of dynamic factors as part of a comprehensive violence risk assessment approach may allow practitioners to better tailor treatment and risk management strategies. Limited research exists on whether risk assessment instruments can detect change in dynamic factors over time. The Short-Term Assessment of Risk and Treatability: Adolescent Version (START:AV) is a relatively new risk assessment instrument that considers both Vulnerabilities and Strengths on factors that are purportedly dynamic in nature. This study examined changes in START:AV factors between initial and follow-up assessments conducted approximately three months later as part of a pilot implementation at three juvenile justice residential facilities in a Southern state. Overall, findings revealed significant item-level changes on several factors, as well as reliable changes in total scores for 28% (reliable change index; 95% confidence interval) of adolescents.

Effects of sample size and distributional assumptions on competing models of the factor structure of the PANSS and BPRS.

Factor analytic work on the Positive and Negative Syndrome Scale (PANSS) and Brief Psychiatric Rating Scale (BPRS) has yielded varied and conflicting results. The current study explored potential causes of these discrepancies. Prior research has been limited by small sample sizes and an incorrect assumption that the items are normally distributed when in practice responses are highly skewed ordinal variables. Using simulation methodology, we examined the effects of sample size, (in)correctly specifying item distributions, collapsing rarely endorsed response categories, and four factor analytic models. The first is the model of Van Dorn et al., developed using a large integrated data set, specified the item distributions as multinomial, and used cross-validation. The remaining models were developed specifying item distributions as normal: the commonly used pentagonal model of White et al.; the model of Van der Gaag et al. developed using extensive cross-validation methods; and the model of Shafer developed through meta-analysis. Our simulation results indicated that incorrectly assuming normality led to biases in model fit and factor structure, especially for small sample size. Collapsing rarely used response options had negligible effects.

The latent structure of psychiatric symptoms across mental disorders as measured with the PANSS and BPRS-18.

Raw data were used from five studies of adults with mental illnesses (N=4,480) in an attempt to identify a psychiatric symptoms factor structure, as measured by the Positive and Negative Syndrome Scale or the Brief Psychiatric Rating Scale, that was generalizable across participant characteristics. First, the fit of four extant models was tested via confirmatory factor analysis (CFA), then exploratory factor analyses (EFA) were conducted with a 50% random sample, followed by a CFA with the remaining 50% to confirm the EFA factor structure. Measurement invariance of the factor structure was also examined across diagnosis, sex, race, age, and hospitalization status. The extant models were not generalizable to these data. However, a 4-factor (Affective, Positive, Negative, Disorganized Cognitive Processing) model was identified that retained all items and showed invariance across participant characteristics. It is possible to obtain a psychiatric symptoms factor structure that is generalizable across patient characteristics, which has clinical and research implications. Specifically, future research examining the impact of various interventions on psychiatric symptoms among adults with mental illnesses should confirm, and assuming good model-data fit, use the 4-factor model identified in this study.

From Risk Assessment to Risk Management: Matching Interventions to Adolescent Offenders' Strengths and Vulnerabilities.

Though considerable research has examined the validity of risk assessment tools in predicting adverse outcomes in justice-involved adolescents, the extent to which risk assessments are translated into risk management strategies and, importantly, the association between this link and adverse outcomes has gone largely unexamined. To address these shortcomings, the Risk-Need-Responsivity (RNR) model was used to examine associations between identified strengths and vulnerabilities, interventions, and institutional outcomes for justice-involved youth. Data were collected from risk assessments completed using the Short-Term Assessment of Risk and Treatability: Adolescent Version (START:AV) for 120 adolescent offenders (96 boys and 24 girls). Interventions and outcomes were extracted from institutional records. Mixed evidence of adherence to RNR principles was found. Accordant to the risk principle, adolescent offenders judged to have more strengths had more strength-based interventions in their service plans, though adolescent offenders with more vulnerabilities did not have more interventions targeting their vulnerabilities. With respect to the need and responsivity principles, vulnerabilities and strengths identified as particularly relevant to the individual youth's risk of adverse outcomes were addressed in the service plans about half and a quarter of the time, respectively. Greater adherence to the risk and need principles was found to predict significantly the likelihood of externalizing outcomes. Findings suggest some gaps between risk assessment and risk management and highlight the potential usefulness of strength-based approaches to intervention.

Girls arrested for murder: an empirical analysis of 32 years of U.S. data by offender age groups.

Most studies on juvenile homicide offenders (JHOs) have used small samples and have concentrated on adolescent male offenders. As a result, little is known about the population of female juveniles arrested for murder. This study utilized the Supplementary Homicide Report (SHR) database to investigate age differences between younger (aged 6-12 years) and older (aged 13-17 years) females arrested for murder in the United States from 1976 to 2007. As predicted, six variables used to test seven hypotheses with respect to younger and older female JHOs in single victim incidents were significant (victim age, victim gender, victim offender relationship, murder weapon, offender count, and homicide circumstance). Regression analysis revealed that younger girls were seven times more likely than older girls to kill children aged 0-12 years. Girls aged 6-12 years were five times more likely than their teen counterparts to be involved in conflict-related homicides as opposed to crime-related homicides. Although approximately the same percentages of younger and older girls killed infants under the age of 1, the victims were significantly different for the two offender age groups. This article concludes with a discussion of our findings and directions for future research.

Accuracy of self-report, biological tests, collateral reports and clinician ratings in identifying substance use disorders among adults with schizophrenia.

Identifying substance use disorders among adults with schizophrenia presents unique challenges but is critical to research and practice. This study examined: (a) the accuracy of assessments completed using various approaches in identifying substance use disorders, (b) their ability to discriminate between disorders of abuse and dependence, and (c) the benefits of using multiple indicators to identify substance use disorders. Data are from the Clinical Antipsychotic Trials of Intervention Effectiveness study. The sample comprised 1,460 community-based adults with schizophrenia, 15.8% (n = 230) of whom were positive for a current (past month) drug or alcohol use disorder using the Structured Clinical Interview for DSM-IV Disorders (SCID). Clinician ratings, self-report, collateral reports, and results of hair and urine tests were compared to SCID diagnoses. Congruence with SCID diagnoses was good across approaches and evidence for superiority of one approach over another was limited. No approach discriminated between abuse and dependence. There was limited benefit of using multiple indicators. Findings suggest that the decision regarding the "best" approach for identifying substance use disorders among adults with schizophrenia may be made through consideration of practical issues and assessment purpose, rather than selection of the approach that yields the most accurate diagnostic assessment.

Assessing illicit drug use among adults with schizophrenia.

Accurate drug use assessment is vital to understanding the prevalence, course, treatment needs, and outcomes among individuals with schizophrenia because they are thought to remain at long-term risk for negative drug use outcomes, even in the absence of drug use disorder. This study evaluated self-report and biological measures for assessing illicit drug use in the Clinical Antipsychotic Trials of Intervention Effectiveness study (N=1460). Performance was good across assessment methods, but differed as a function of drug type, measure, and race. With the Structured Clinical Interview for DSM-III-R as the criterion, self-report evidenced greater concordance, accuracy and agreement overall, and for marijuana, cocaine, and stimulants specifically, than did urinalysis and hair assays, whereas biological measures outperformed self-report for detection of opiates. Performance of the biological measures was better when self-report was the criterion, but poorer for black compared white participants. Overall, findings suggest that self-report is able to garner accurate information regarding illicit drug use among adults with schizophrenia. Further work is needed to understand the differential performance of assessment approaches by drug type, overall and as a function of race, in this population.

Pilot Implementation and Preliminary Evaluation of START:AV Assessments in Secure Juvenile Correctional Facilities.

The Short-Term Assessment of Risk and Treatability: Adolescent Version (START:AV) is a new structured professional judgment guide for assessing short-term risks in adolescents. The scheme may be distinguished from other youth risk assessment and treatment planning instruments by its inclusion of 23 dynamic factors that are each rated for both vulnerability and strength. In addition, START:AV is also unique in that it focuses on multiple adverse outcomes-namely, violence, self-harm, suicide, unauthorized leave, substance abuse, self-neglect, victimization, and general offending-over the short-term (i.e., weeks to months) rather than long-term (i.e., years). This paper describes a pilot implementation and preliminary evaluation of START:AV in three secure juvenile correctional facilities in the southern United States. Specifically, we examined the descriptive characteristics and psychometric properties of START:AV assessments completed by 21 case managers on 291 adolescent offenders (250 boys and 41 girls) at the time of admission. Results provide preliminary support for the feasibility of completing START:AV assessments as part of routine practice. Findings also highlight differences in the characteristics of START:AV assessments for boys and girls and differential associations between the eight START:AV risk domains. Though results are promising, further research is needed to establish the reliability and validity of START:AV assessments completed in the field.

Male and female child murderers: an empirical analysis of U.S. arrest data.

Recent U.S. cases of murders by children below age 11 have captured national headlines. A review of the literature reveals that little is known about this population of juvenile homicide offenders (JHOs). Most studies on juvenile murderers have used small clinical samples, focused on adolescents, and concentrated on male offenders. Studies that have used Supplementary Homicide Report (SHR) data have found significant gender differences among juveniles below 18 years arrested for murder. This study investigated gender differences among 226 juvenile murderers ages 6 through 10 involved in single-victim incidents using bivariate and multivariate statistical techniques. Consistent with previous research, bivariate analyses revealed gender differences with respect to the type of weapon used, age of the victim, relationship to the victim, and circumstances of the crime. Logistic regression analysis identified female JHOs as more likely to use a knife, kill a family member, and kill a victim below age 5, when compared with male JHOs. From these findings, profiles of young male and female JHOs can be drawn. The article concludes with a discussion of the study's implications for prevention and treatment. The authors recommend that future research in gender differences among young children focus on examining psychological, neurological, and sociological variables not included in the SHR data set.