Tobacco Cessation Services in Addiction Treatment: What Do Clients Say?

ObjectiveSpecialty addiction programs treat people who are addicted to alcohol, opioids, stimulants, and other drugs. This study identified the proportion of addiction program clients who received tobacco-related services and factors associated with receipt of such services.MethodsIn 2015 and 2016, clients (N=2,119) in 24 programs were surveyed for receipt of services aligning with three of the five As of tobacco cessation: ask, advise, assist. Multivariate analyses examined factors associated with receipt of each service.ResultsMost clients (76%) were asked about smoking. Among smokers (N=1,630), 53% were advised to quit, 41% received counseling, 26% received cessation medication, and 17% received counseling and medication. Clients were more likely to receive tobacco-related services if they wanted help quitting smoking or were enrolled in programs with tobacco-free grounds.ConclusionsThese correlational findings suggest that increasing client motivation to quit and implementing tobacco-free policies on the grounds of treatment centers may increase tobacco-related services in addiction treatment

Prospective Study of Violence Risk Reduction by a Mental Health Court

Although many mental health courts (MHCs) have been established to reduce criminal justice involvement of persons with mental disorders, research has not kept pace with the widespread implementation of these courts. Whereas early MHCs were restricted to persons charged with nonviolent misdemeanors, many MHCs now accept persons with more serious charges for whom ameliorating risk of violence is a greater concern. This study evaluated the relationship between MHC participation and risk of violence by using a prospective design. It was hypothesized that MHC participation would decrease the risk of violence during a one year follow-up compared with a matched comparison group.The sample included 169 jail detainees with a mental disorder who either entered an MHC (N=88) or received treatment as usual (N=81). Seventy-two percent had been charged with felonies. Participants were interviewed at baseline and during a one-year follow up, and their arrest records were reviewed. Propensity-adjusted logistic regression evaluated the relationship between MHC participation and risk of violence, controlling for potential confounders such as history of violence, demographic characteristics, baseline treatment motivation, and time at risk in the community.MHC participation was associated with reduction in risk of violence (odds ratio=.39). During follow-up, 25% of the MHC group perpetrated violence, compared with 42% of the treatment-as-usual group.MHC participation can reduce the risk of violence among justice-involved persons with mental disorders. The findings support the conclusion that the MHC model can be extended beyond persons charged with nonviolent misdemeanors in a way that enhances public safety

Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials

BACKGROUND: Heterogeneity in Acute Respiratory Distress Syndrome (ARDS), as a consequence of its non-specific definition, has led to a multitude of negative randomised controlled trials (RCTs). Investigators have sought to identify heterogeneity of treatment effect (HTE) in RCTs using clustering algorithms. We evaluated the proficiency of several commonly-used machine-learning algorithms to identify clusters where HTE may be detected. METHODS: Five unsupervised: Latent class analysis (LCA), K-means, partition around medoids, hierarchical, and spectral clustering; and four supervised algorithms: model-based recursive partitioning, Causal Forest (CF), and X-learner with Random Forest (XL-RF) and Bayesian Additive Regression Trees were individually applied to three prior ARDS RCTs. Clinical data and research protein biomarkers were used as partitioning variables, with the latter excluded for secondary analyses. For a clustering schema, HTE was evaluated based on the interaction term of treatment group and cluster with day-90 mortality as the dependent variable. FINDINGS: No single algorithm identified clusters with significant HTE in all three trials. LCA, XL-RF, and CF identified HTE most frequently (2/3 RCTs). Important partitioning variables in the unsupervised approaches were consistent across algorithms and RCTs. In supervised models, important partitioning variables varied between algorithms and across RCTs. In algorithms where clusters demonstrated HTE in the same trial, patients frequently interchanged clusters from treatment-benefit to treatment-harm clusters across algorithms. LCA aside, results from all other algorithms were subject to significant alteration in cluster composition and HTE with random seed change. Removing research biomarkers as partitioning variables greatly reduced the chances of detecting HTE across all algorithms. INTERPRETATION: Machine-learning algorithms were inconsistent in their abilities to identify clusters with significant HTE. Protein biomarkers were essential in identifying clusters with HTE. Investigations using machine-learning approaches to identify clusters to seek HTE require cautious interpretation. FUNDING: NIGMS R35 GM142992 (PS), NHLBI R35 HL140026 (CSC); NIGMS R01 GM123193, Department of Defense W81XWH-21-1-0009, NIA R21 AG068720, NIDA R01 DA051464 (MMC)

Expectancies regarding the interaction between smoking and substance use in alcohol-dependent smokers in early recovery.

The purpose of this study was to investigate expectancies regarding the interaction between cigarette smoking and use of alcohol among alcohol-dependent smokers in early recovery, using the Nicotine and Other Substances Interaction Expectancies Questionnaire (NOSIE). Participants were 162 veterans, 97% male, with a mean age of 50 years, enrolled in a clinical trial aimed at determining the efficacy of an intensive smoking cessation intervention versus usual care. At baseline, participants were assessed on measures of smoking behavior, abstinence thoughts about alcohol and tobacco use, symptoms of depression, and smoking-substance use interaction expectancies. In addition, biologically verified abstinence from tobacco and alcohol was assessed at 26 weeks. Participants reported that they expected smoking to have less of an impact on substance use than substance use has on smoking (p < .001). Severity of depressive symptoms was significantly associated with the expectancy that smoking provides a way of coping with the urge to use other substances (p < .01). The expectation that smoking increases substance urges/use was predictive of prospectively measured and biologically verified abstinence from smoking at 26 weeks (p < .03). The results add to our knowledge of smoking-substance use interaction expectancies among alcohol-dependent smokers in early recovery and will inform the development of more effective counseling interventions for concurrent alcohol and tobacco use disorders

Design and implementation of the START (STem cells for ARDS Treatment) trial, a phase 1/2 trial of human mesenchymal stem/stromal cells for the treatment of moderate-severe acute respiratory distress syndrome

Background: Despite advances in supportive care, moderate-severe acute respiratory distress syndrome (ARDS) is associated with high mortality rates, and novel therapies to treat this condition are needed. Compelling pre-clinical data from mouse, rat, sheep and ex vivo perfused human lung models support the use of human mesenchymal stem (stromal) cells (MSCs) as a novel intravenous therapy for the early treatment of ARDS. Methods: This article describes the study design and challenges encountered during the implementation and phase 1 component of the START (STem cells for ARDS Treatment) trial, a phase 1/2 trial of bone marrow-derived human MSCs for moderate-severe ARDS. A trial enrolling 69 subjects is planned (9 subjects in phase 1, 60 subjects in phase 2 treated with MSCs or placebo in a 2:1 ratio). Results: This report describes study design features that are unique to a phase 1 trial in critically ill subjects and the specific challenges of implementation of a cell-based therapy trial in the ICU. Conclusions: Experience gained during the design and implementation of the START study will be useful to investigators planning future phase 1 clinical trials based in the ICU, as well as trials of cell-based therapy for other acute illnesses. Trial registration Clinical Trials Registration: NCT01775774 and NCT02097641

Symptom Dimensions in OCD: Item-Level Factor Analysis and Heritability Estimates

To reduce the phenotypic heterogeneity of obsessive-compulsive disorder (OCD) for genetic, clinical and translational studies, numerous factor analyses of the Yale-Brown Obsessive Compulsive Scale checklist (YBOCS-CL) have been conducted. Results of these analyses have been inconsistent, likely as a consequence of small sample sizes and variable methodologies. Furthermore, data concerning the heritability of the factors are limited. Item and category-level factor analyses of YBOCS-CL items from 1224 OCD subjects were followed by heritability analyses in 52 OCD-affected multigenerational families. Item-level analyses indicated that a five factor model: (1) taboo, (2) contamination/cleaning, (3) doubts, (4) superstitions/rituals, and (5) symmetry/hoarding provided the best fit, followed by a one-factor solution. All 5 factors as well as the one-factor solution were found to be heritable. Bivariate analyses indicated that the taboo and doubts factor, and the contamination and symmetry/hoarding factor share genetic influences. Contamination and symmetry/hoarding show shared genetic variance with symptom severity. Nearly all factors showed shared environmental variance with each other and with symptom severity. These results support the utility of both OCD diagnosis and symptom dimensions in genetic research and clinical contexts. Both shared and unique genetic influences underlie susceptibility to OCD and its symptom dimensions.Obsessive Compulsive FoundationTourette Syndrome AssociationAnxiety Disorders Association of AmericaAmerican Academy of Child and Adolescent Psychiatr

APOE e4 genotype and cigarette smoking in adults with normal cognition and mild cognitive impairment: a retrospective baseline analysis of a national dataset

BackgroundAPOE e4 genotype is known to be a risk factor for Alzheimer's disease and atherosclerosis. Recently, published evidence has shown that APOE e4 genotype may also be associated with the cessation of cigarette smoking.ObjectivesThe aim of this retrospective analysis was to explore whether any past smoking outcomes differed based on APOE e4 genotype in a large national dataset.MethodsData were extracted from the National Alzheimer's Coordinating Center's longitudinal Uniform Data Set study. We limited this retrospective baseline analysis to the normal cognition (n = 2995) and mild cognitive impairment (n = 1627) groups that had APOE genotype and smoking data. Because this was an exploratory retrospective analysis, we conducted descriptive analyses on all variables based on APOE e4 genotype. We controlled for demographic, clinical, medication and neurocognitive data in the analyses.ResultsIn both the normal cognition group and the mild cognitive impairment group, e4 carriers and e4 non-carriers did not significantly differ on total years smoked, age when last smoked and the average # of packs/day smoked during the years they smoked. In both groups, e4 carriers and e4 non-carriers differed on various neurocognitive measures.ConclusionThese data do not support the recently published evidence of the association between APOE e4 genotype and smoking outcomes.Scientific significanceLarger prospective clinical trials are needed to further explore the relationship between APOE genotype and smoking outcomes