Do Demographic Factors Moderate How Well Criminal Thinking Predicts Recidivism?

Is the relationship between criminal thinking and recidivism the same for criminal justice-involved individuals from varying demographic backgrounds? Relying on two independent samples of offenders and two measures of criminal thinking, the current studies examined whether four demographic factors-gender, race, age, and education-moderated the relationship between criminal thinking and recidivism. Study 1 consisted of 226 drug-involved probationers enrolled in a randomized clinical trial. Study 2 consisted of 346 jail inmates from a longitudinal study. Logistic regression models suggested that the strength of the relationship between criminal thinking and subsequent recidivism did not vary based on participant demographics, regardless of justice system setting or measure of criminal thinking. Criminal thinking predicts recidivism similarly for people who are male, female, Black, White, older, younger, and more or less educated.

Is Treatment Readiness Associated With Substance Use Treatment Engagement? An Exploratory Study.

With nearly 8.2% of Americans experiencing substance use disorders (SUDs), a need exists for effective SUD treatment and for strategies to assist treatment participants to complete treatment programs (Chandler, Fletcher, & Volkow, 2009). The purpose of the current research is to contribute to an emerging knowledge base about treatment readiness and its utility for predicting substance use treatment process performance measures. The study examines the relative salience of treatment readiness as a predictor of treatment engagement. Data are derived from adult cases included in the 2012 Global Appraisal of Individual Needs-Intake data set ( n = 5,443). Binary logistic regression was used to identify if treatment readiness predicts substance use treatment engagement. The findings of this study do not provide support for treatment readiness significantly predicting substance use treatment engagement. Further research is needed to better understand treatment engagement.

Differences by Gender in Predictors of Motivation Among Substance Abuse Treatment Participants.

BACKGROUND: Substance-involved females tend to have different clinical profiles than men (Adams, Leukefeld, & Peden, 2008 ); yet they do not appear to have worse treatment outcomes (Green, 2006 ; Hser, Huang, Teruya, & Anglin, 2003 ). As motivation for treatment is considered essential in the substance abuse treatment context (Cahill, Adinoff, Hosig, Muller, & Pulliam, 2003 ; Longshore & Teruya, 2006 ), it is possible that higher motivation among females could potentially counteract the negative effect of more risk factors. OBJECTIVE: The purpose of the current study was to examine if females differ from males in their motivation for treatment using the Texas Christian University Motivation Form scales: desire for help, problem recognition, treatment readiness, pressure for treatment, and treatment needs; and whether factors predicting motivation for treatment differed between male and female participants of substance abuse treatment. METHODS: The sample included 2,989 substance-involved males and 982 substance-involved females who were referred to substance abuse treatment through a case management program. Linear regression models predicting each motivation scale were analyzed, followed by gender-specific models. RESULTS: Overall, the results did not demonstrate a significant gender difference in the motivation scales. However, among male participants, the findings did show that Hispanic significantly predicted desire for help and alcohol as a primary drug of choice predicted treatment readiness. CONCLUSION: Findings suggest that motivation for treatment may be a gender-neutral construct, and that there is a need to better understand sociodemographic predictors of motivation.

Does substance misuse moderate the relationship between criminal thinking and recidivism?

PURPOSE: Some differential intervention frameworks contend that substance use is less robustly related to recidivism outcomes than other criminogenic needs such as criminal thinking. The current study tested the hypothesis that substance use disorder severity moderates the relationship between criminal thinking and recidivism. METHODS: The study utilized two independent criminal justice samples. Study 1 included 226 drug-involved probationers. Study 2 included 337 jail inmates with varying levels of substance use disorder severity. Logistic regression was employed to test the main and interactive effects of criminal thinking and substance use on multiple dichotomous indicators of recidivism. RESULTS: Bivariate analyses revealed a significant correlation between criminal thinking and recidivism in the jail sample (r = .18, p < .05) but no significant relationship in the probation sample. Logistic regressions revealed that SUD symptoms moderated the relationship between criminal thinking and recidivism in the jail-based sample (B = -.58, p < .05). A significant moderation effect was not observed in the probation sample. CONCLUSIONS: Study findings indicate that substance use disorder symptoms moderate the strength of the association between criminal thinking and recidivism. These findings demonstrate the need for further research into the interaction between various dynamic risk factors.

The Psychometric Properties of the Simple Screening Instrument for Substance Abuse.

The Simple Screening Instrument for Substance Abuse (SSI-SA) is gaining widespread use as a self-report measure of substance abuse; yet, little information exists regarding the instrument's psychometric properties. This study examined the SSI's psychometric properties within a population of 6,664 adult Medicaid enrollees in Florida, who responded to a survey conducted as part of a statewide evaluation of Medicaid services. The SSI-SA had excellent internal consistency (.85). Evidence of the SSI's validity was strong; SSI-SA scores distinguished among individuals with and without substance abuse needs and were significantly correlated with a measure of functioning in daily living. Using the recommended SSI-SA cutoff score of 4 or higher to indicate the presence of a substance abuse problem, the SSI-SA had respectable sensitivity (.82) and specificity (.90).

Case studies from three states: breaking down silos between health care and criminal justice.

The jail-involved population-people with a history of arrest in the previous year-has high rates of illness, which leads to high costs for society. A significant percentage of jail-involved people are estimated to become newly eligible for coverage through the Affordable Care Act's expansion of Medicaid, including coverage of substance abuse treatment and mental health care. In this article we explore the need to break down the current policy silos between health care and criminal justice, to benefit both sectors and reduce unnecessary costs resulting from lack of coordination. To draw attention to the hidden costs of the current system, we review three case studies, from Washington State, Los Angeles County in California, and New York City. Each case study addresses different aspects of care needed by or provided to the jail-involved population, including mental health and substance abuse, emergency care, and coordination of care transitions. Ultimately, bending the cost curve for health care and criminal justice will require greater integration of the two systems.

The Reactome pathway knowledgebase.

Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 human proteins (34% of the predicted human proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. The Reactome Web site and analysis tool set have been completely redesigned to increase speed, flexibility and user friendliness. The data model has been extended to support annotation of disease processes due to infectious agents and to mutation.

Short-term trajectories of substance use in a sample of drug-involved probationers.

The current study estimates trajectories of illegal substance use in a sample of 251 drug-involved probationers to identify risk profiles that predict group membership and explores the impact of treatment participation across these trajectories. Trajectory analyses reveal five patterns of drug use during probation supervision. Age and the use of hard drugs are identified as the strongest predictors of involvement in illicit drug use while on probation. The effect of participation in substance use treatment varies across treatment settings and trajectory groups. Prior research has tended to treat drug abusers as a homogeneous population, but the current study findings suggest considerable heterogeneity amongst drug users involved in the criminal justice system. Identifying trajectories of drug use during supervision can help identify individuals who may be more likely to persist in drug use, can inform practice by identifying individuals in need of more intensive treatment services, and can assist in developing new drug treatment strategies.

A statistical method for synthesizing meta-analyses.

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.

A reanalysis of the self-appraisal questionnaire: psychometric properties and predictive validity.

This research reassessed the psychometric properties and predictive validity of the Self-Appraisal Questionnaire (SAQ) in response to published criticism of the authors' earlier work. The current research used a much longer recidivism tracking-period, a different measure of recidivism, a larger sample, and more advanced analytic techniques than the original. Examination of the SAQ's psychometric properties continued to indicate that three of the six recidivism prediction subscales exhibited substandard levels of reliability and four of these subscales were not unidimensional. Yet, in contrast to the author's earlier results, the current analyses found that SAQ total score modestly predicted reconviction.

Co-occurring disorders in treatment-based courts: results of a national survey.

Drug courts and mental health courts have expanded rapidly in the past several decades to provide more efficient coordination of treatment and supervision of offenders with behavioral health problems. A significant number of offenders in these court-based programs have co-occurring mental and substance use disorders, which predict early termination, relapse, rearrest, and other negative outcomes. A web-based national survey examined programmatic adaptations for co-occurring disorders (CODs) among 54 drug courts, mental health courts, and freestanding COD dockets. COD dockets were smaller and of longer duration, and provided more intensive services than programs situated in drug courts or in mental health courts. However, more similarities than differences were noted across the different types of court-based program. Key adaptations for CODs included extended program duration, highly intensive and integrated treatment, smaller, less formal, and more frequent hearings, and use of specialized supervision teams and dually credentialed staff.

The Protein Ontology: a structured representation of protein forms and complexes.

The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as to enhance accessibility to results of protein research. PRO (http://pir.georgetown.edu/pro) is part of the Open Biomedical Ontology Foundry.

Reactome: a database of reactions, pathways and biological processes.

Reactome (http://www.reactome.org) is a collaboration among groups at the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University School of Medicine and The European Bioinformatics Institute, to develop an open source curated bioinformatics database of human pathways and reactions. Recently, we developed a new web site with improved tools for pathway browsing and data analysis. The Pathway Browser is an Systems Biology Graphical Notation (SBGN)-based visualization system that supports zooming, scrolling and event highlighting. It exploits PSIQUIC web services to overlay our curated pathways with molecular interaction data from the Reactome Functional Interaction Network and external interaction databases such as IntAct, BioGRID, ChEMBL, iRefIndex, MINT and STRING. Our Pathway and Expression Analysis tools enable ID mapping, pathway assignment and overrepresentation analysis of user-supplied data sets. To support pathway annotation and analysis in other species, we continue to make orthology-based inferences of pathways in non-human species, applying Ensembl Compara to identify orthologs of curated human proteins in each of 20 other species. The resulting inferred pathway sets can be browsed and analyzed with our Species Comparison tool. Collaborations are also underway to create manually curated data sets on the Reactome framework for chicken, Drosophila and rice.

Differential regulation of transcription through distinct Suppressor of Hairless DNA binding site architectures during Notch signaling in proneural clusters.

In Drosophila melanogaster, achaete (ac) and m8 are model basic helix-loop-helix activator (bHLH A) and repressor genes, respectively, that have the opposite cell expression pattern in proneural clusters during Notch signaling. Previous studies have shown that activation of m8 transcription in specific cells within proneural clusters by Notch signaling is programmed by a "combinatorial" and "architectural" DNA transcription code containing binding sites for the Su(H) and proneural bHLH A proteins. Here we show the novel result that the ac promoter contains a similar combinatorial code of Su(H) and bHLH A binding sites but contains a different Su(H) site architectural code that does not mediate activation during Notch signaling, thus programming a cell expression pattern opposite that of m8 in proneural clusters.

The systematic annotation of the three main GPCR families in Reactome.

Reactome is an open-source, freely available database of human biological pathways and processes. A major goal of our work is to provide an integrated view of cellular signalling processes that spans from ligand-receptor interactions to molecular readouts at the level of metabolic and transcriptional events. To this end, we have built the first catalogue of all human G protein-coupled receptors (GPCRs) known to bind endogenous or natural ligands. The UniProt database has records for 797 proteins classified as GPCRs and sorted into families A/1, B/2 and C/3 on the basis of amino acid sequence. To these records we have added details from the IUPHAR database and our own manual curation of relevant literature to create reactions in which 563 GPCRs bind ligands and also interact with specific G-proteins to initiate signalling cascades. We believe the remaining 234 GPCRs are true orphans. The Reactome GPCR pathway can be viewed as a detailed interactive diagram and can be exported in many forms. It provides a template for the orthology-based inference of GPCR reactions for diverse model organism species, and can be overlaid with protein-protein interaction and gene expression datasets to facilitate overrepresentation studies and other forms of pathway analysis. Database URL: http://www.reactome.org.

Exploring the utility of an estimation procedure to reveal drug use among arrestees: implications for service delivery.

One of the most persistent questions plaguing researchers and service providers is how to best estimate the extent of targeted behaviors in relevant populations. One problem of particular importance is the prevalence of drug use in justice-involved populations. Data have been collected through such methods as self-report and analysis of biological specimens, although both have notable limitations when used alone. As a means of drawing on the strengths of both methods, such data can be used in a confirmatory manner or, alternatively, may be summed to estimate prevalence. However, this latter approach is not without difficulty as different sources lack substantial agreement. The focus of this study is to employ a methodology that utilizes multiple data sources and adjusts for nonreporting from either source. Compared to more commonly employed techniques, the results indicate that the alternative method yields higher estimates of marijuana and cocaine use among a sample of arrestees. These findings, in turn, suggest that current behavioral health interventions and policies may be based on underestimates of drug use.

The Daughterless N-terminus directly mediates synergistic interactions with Notch transcription complexes via the SPS+A DNA transcription code.

BACKGROUND: Cell-specific expression of a subset of Enhancer of split (E(spl)-C) genes in proneural clusters is mediated by synergistic interactions between bHLH A (basic Helix-Loop-Helix Activator) and Notch-signalling transcription complex (NTC) proteins. For a some of these E(spl)-C genes, such as m8, these synergistic interactions are programmed by an "SPS+A" transcription code in the cis-regulatory regions. However, the molecular mechanisms underlying this synergistic interaction between NTCs and proneural bHLH A proteins are not fully understood. FINDINGS: Using cell transcription assays, we show that the N-terminal region of the Daughterless (Da) bHLH A protein is critical for synergistic interactions with NTCs that activate the E(spl)-C m8 promoter. These assays also show that this interaction is dependent on the specific inverted repeat architecture of Suppressor of Hairless (Su(H)) binding sites in the SPS+A transcription code. Using protein-protein interaction assays, we show that two distinct regions within the Da N-terminus make a direct physical interaction with the NTC protein Su(H). Deletion of these interaction domains in Da creates a dominant negative protein that eliminates NTC-bHLH A transcriptional synergy on the m8 promoter. In addition, over-expression of this dominant negative Da protein disrupts Notch-mediated lateral inhibition during mechanosensory bristle neurogenesis in vivo. CONCLUSION: These findings indicate that direct physical interactions between Da-N and Su(H) are critical for the transcriptional synergy between NTC and bHLH A proteins on the m8 promoter. Our results also indicate that the orientation of the Su(H) binding sites in the SPS+A transcription code are critical for programming the interaction between Da-N and Su(H) proteins. Together, these findings provide insight into the molecular mechanisms by which the NTC synergistically interacts with bHLH A proteins to mediate Notch target gene expression in proneural clusters.

Reactome knowledgebase of human biological pathways and processes.

Reactome (http://www.reactome.org) is an expert-authored, peer-reviewed knowledgebase of human reactions and pathways that functions as a data mining resource and electronic textbook. Its current release includes 2975 human proteins, 2907 reactions and 4455 literature citations. A new entity-level pathway viewer and improved search and data mining tools facilitate searching and visualizing pathway data and the analysis of user-supplied high-throughput data sets. Reactome has increased its utility to the model organism communities with improved orthology prediction methods allowing pathway inference for 22 species and through collaborations to create manually curated Reactome pathway datasets for species including Arabidopsis, Oryza sativa (rice), Drosophila and Gallus gallus (chicken). Reactome's data content and software can all be freely used and redistributed under open source terms.

Promoter-specific co-activation by Drosophila mastermind.

Mastermind (Mam) is a co-activator protein of binary complexes consisting of Suppressor of Hairless (Su(H)) and Notch Intracellular Domain (NICD) proteins assembled on cis-regulatory regions of target genes activated by Notch signaling. Current evidence indicates that Mastermind is necessary and sufficient for the formation of a functional Su(H)/NICD/Mam ternary complex on at least one specific architecture of Su(H) binding sites, called the SPS element (Su(H) Paired Sites). However, using transcription assays with a combination of native and synthetic Notch target gene promoters in Drosophila cultured cells, we show here that co-activation of Su(H)/NICD complexes on SPS elements by Mam is promoter-specific. Our novel results suggest this promoter specificity is mediated by additional unknown cis-regulatory elements present in the native promoters that are required for the recruitment of Mam and formation of functional Su(H)/NICD/Mam complexes on SPS elements. Together, the findings in this study suggest Mam is not always necessary and sufficient for co-activation of binary Su(H)/NICD complexes on SPS elements.

A DNA transcription code for cell-specific gene activation by notch signaling.

BACKGROUND: Cell-specific gene regulation is often controlled by specific combinations of DNA binding sites in target enhancers or promoters. A key question is whether these sites are randomly arranged or if there is an organizational pattern or "architecture" within such regulatory modules. During Notch signaling in Drosophila proneural clusters, cell-specific activation of certain Notch target genes is known to require transcriptional synergy between the Notch intracellular domain (NICD) complexed with CSL proteins bound to "S" DNA sites and proneural bHLH activator proteins bound to nearby "A" DNA sites. Previous studies have implied that arbitrary combinations of S and A DNA binding sites (an "S+A" transcription code) can mediate the Notch-proneural transcriptional synergy. RESULTS: By contrast, we show that the Notch-proneural transcriptional synergy critically requires a particular DNA site architecture ("SPS"), which consists of a pair of specifically-oriented S binding sites. Native and synthetic promoter analysis shows that the SPS architecture in combination with proneural A sites creates a minimal DNA regulatory code, "SPS+A", that is both sufficient and critical for mediating the Notch-proneural synergy. Transgenic Drosophila analysis confirms the SPS orientation requirement during Notch signaling in proneural clusters. We also present evidence that CSL interacts directly with the proneural Daughterless protein, thus providing a molecular mechanism for this synergy. CONCLUSIONS: The SPS architecture functions to mediate or enable the Notch-proneural transcriptional synergy which drives Notch target gene activation in specific cells. Thus, SPS+A is an architectural DNA transcription code that programs a cell-specific pattern of gene expression.