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Examined job tenure among 85 individuals with psychiatric disabilities. Surveyed clients' demographic, clinical, and vocational histories, their initial reactions to specific jobs, and aspects of the work environment. The average job lasted 70 days. Longer tenure was predicted by previous work history, early satisfaction with the job, lower autonomy, and higher innovation. (RJM)

Objective: Co-occurring posttraumatic stress (PTSD) and substance use disorders provide clinical challenges to addiction treatment providers. Interventions are needed that are effective, well-tolerated by patients, and capable of being delivered by typical clinicians in community settings. This is a randomized controlled trial of integrated cognitive behavioral therapy for co-occurring PTSD and substance use disorders. Methods: Fifty-three participants sampled from seven community addiction treatment programs were randomized to integrated cognitive behavioral therapy plus standard care or individual addiction counseling plus standard care. Fourteen community therapists employed by these programs delivered both manual-guided therapies. Primary outcomes were PTSD symptoms, substance use symptoms, and therapy retention. Participants were assessed at baseline, 3- and 6-month follow-up. Results: Integrated cognitive behavioral therapy was more effective than individual addiction counseling in reducing PTSD re-experiencing symptoms and PTSD diagnosis. Individual addiction counseling was comparably effective to integrated cognitive behavioral therapy in substance use outcomes and on other measures of psychiatric symptom severity. Participants assigned to individual addiction counseling with severe PTSD were less likely to initiate and engage in the therapy than those assigned to integrated cognitive behavioral therapy. In general, participants with severe PTSD were more likely to benefit from integrated cognitive behavioral therapy. Conclusions: The findings support the promise of efficacy of integrated cognitive behavioral therapy in improving outcomes for persons in addiction treatment with PTSD. Community counselors delivered both interventions with satisfactory adherence and competence. Despite several limitations to this research, a larger randomized controlled trial of integrated cognitive behavioral therapy appears to be warranted. [ABSTRACT FROM PUBLISHER]

Medicaid recipients with serious mental illness die 25–30 years earlier than people in the general population due to health conditions that are modifiable through lifestyle changes. Cardiovascular diseases from excess weight, smoking, and sedentary lifestyle contribute substantially to this life expectancy disparity. The current study evaluated the impact of incentives on participation in weight management programming (for overweight and obese adults) and smoking cessation treatment (for regular smokers). Participants were Medicaid recipients with disabling mental illness receiving services at any one of 10 community mental health centers across New Hampshire. Using an equipoise stratified randomized design, n = 1348 were enrolled and assigned to one of four weight management programs (Healthy Choices Healthy Changes: HCHC) and n = 661 were enrolled and assigned to one of three smoking cessation interventions (Breathe Well Live Well: BWLW). Following assignment to an intervention, participants were randomized to receive financial incentives (to attend weight management programs, or to achieve abstinence from smoking) or not. Data were collected at baseline and every 3 months for 12 months. New Hampshire's HCHC and BWLW programs were designed to address serious and preventable health disparities by providing incentivized health promotion programs to overweight/obese and/or tobacco-smoking Medicaid beneficiaries with mental illness. This study was an unprecedented opportunity to evaluate an innovative statewide implementation of incentivized health promotion targeting the most at-risk and costly beneficiaries. If proven effective, this program has the potential to serve as a national model for widespread implementation. [ABSTRACT FROM AUTHOR]

Objective: Second-generation antipsychotics vary in their propensity to cause serious cardiometabolic side effects. In addition, use of two or more antipsychotics (polypharmacy) may lead to additive side effects and has not been shown to be consistently more effective than monotherapy. This study examined the use of academic detailing with audit and feedback to improve antipsychotic prescribing practices, including antipsychotic polypharmacy and utilization of medication with high or low risk of cardiometabolic side effects ("high risk" or "low risk," respectively)., Methods: Four intervention sessions were provided over two years to psychiatric care providers at community mental health centers. Segmented regression within the general estimating equation model framework used Medicaid pharmacy claims to examine prescribing patterns before and after the intervention among all beneficiaries (67,721 person-months) over a five-year period., Results: After the intervention, 10.9% of beneficiaries with antipsychotic claims were on polypharmacy, compared with 13.1% before the invention. Use of high-risk and low-risk antipsychotics did not change. The final adjusted polypharmacy model showed that antipsychotic polypharmacy decreased among young adults and adults ages 40 or older compared with beneficiaries ages 30-39 (β=-.02, p=.04, and β=-.02, p=.007, respectively). The raw proportion of beneficiaries on high- and low-risk agents did not change, although final adjusted models demonstrated changes in use of high- and low-risk agents by diagnosis and risk group., Conclusions: Polypharmacy decreased among young and older adults after academic detailing with audit and feedback. Although further research is needed, this low-intensity intervention may help mental health systems reduce antipsychotic polypharmacy.

Count data with skewness and many zeros are common in substance abuse and addiction research. Zero-adjusting models, especially zero-inflated models, have become increasingly popular in analyzing this type of data. This paper reviews and compares five mixed-effects Poisson family models commonly used to analyze count data with a high proportion of zeros by analyzing a longitudinal outcome: number of smoking quit attempts from the New Hampshire Dual Disorders Study. The findings of our study indicated that count data with many zeros do not necessarily require zero-inflated or other zero-adjusting models. For rare event counts or count data with small means, a simpler model such as the negative binomial model may provide a better fit., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Objective: Approximately three-quarters of people with severe mental illnesses smoke cigarettes, and the rate is even higher among those with co-occurring substance use disorders. This longitudinal study explored patterns of cigarette use and cessation attempts among mental health clients with co-occurring disorders., Methods: Clients participating in a longitudinal study of co-occurring disorders (N=174) were assessed yearly over 11 years for smoking and smoking cessation behaviors, psychiatric symptoms, and other substance use, as well as social, occupational, and other characteristics. Generalized linear mixed-effects models were used to examine smoking cessation outcomes., Results: Eighty-nine percent of participants were current smokers at baseline. Seventy-five percent of participants tried to quit at least once over the 11 years of the study, although none received nicotine replacement therapy or bupropion. Only 17% were not smoking at the 11-year follow-up. The presence of a chronic general medical condition predicted a longer duration of not smoking in the past year. Being male and having a high school education or higher were associated with more attempts to quit smoking, as were higher scores on the activation subscale of the Brief Psychiatric Rating Scale, more social contact with non-substance-using friends, and more daily activities., Conclusions: Although many clients with co-occurring serious mental illness and substance use disorders tried to quit each year, few achieved sustained abstinence and none used evidence-based interventions (nicotine replacement therapy or bupropion). Treatment providers need to administer evidence-based interventions to help people quit successfully.

This pilot study examined whether participation in the individualized, community-integrated In SHAPE health promotion program would result in improved physical activity and dietary behaviors, health indicators, and psychological functioning or symptoms in 76 adults with schizophrenia, bipolar disorder, major depression, or other mental disorders. Over a 9-month period, participation was associated with increased exercise, vigorous activity, and leisurely walking (P < .01), and a trend toward improved readiness to reduce caloric intake (P = .053). Participants demonstrated a reduction in waist circumference (P < .05), but no change in BMI. Satisfaction with fitness (P < .001) and mental health functioning (P < .05) improved, and severity of negative symptoms decreased (P < .01). This study demonstrated the feasibility and potential effectiveness of the In SHAPE program, which consisted of exercise and dietary modification. Based on these promising results, randomized controlled trials of the In SHAPE program are necessary to establish its effectiveness compared with usual care and alternative approaches to enhancing fitness.

Background: Previous correlational research with schizophrenic patients has suggested that the second-generation antipsychotic medication clozapine helps to induce remissions of substance use disorder in patients with co-occurring psychosis and substance abuse. This research, however, could be biased by selection factors. Studying patients who are currently in substance abuse remission could control for level of motivation to stop using substances and other methodological confounds., Methods: To test whether clozapine was associated with prevention of substance abuse relapses, we examined patients with schizophrenia or schizoaffective disorder who were in their first 6-month remission of substance use disorder during a prospective 10-year follow-up study. All patients received yearly multimodal assessments of substance use. Antipsychotic medications were prescribed by community doctors as part of usual clinical care., Results: Patients using clozapine at the first 6-month period of substance abuse remission (n = 25) were much less likely to relapse over the next year compared with those on other antipsychotic medications (n = 70): 8.0% vs 40.0%, chi(2) = 8.73 (df = 1), P = .003. Although medication assignment was not randomized, several potential confounders were similar between the groups., Conclusion: Clozapine should be considered for the treatment of patients with schizophrenia and co-occurring substance use disorder to prevent relapses to substance abuse.

This paper introduces to mental health services and evaluation researchers a method for analyzing longitudinal data: a group-based modeling approach for applied research. We present the basic formulations of the model and illustrate its application by analyzing the 10-year longitudinal data on substance abuse remission from the New Hampshire Dual Disorders Study. The basic features of the approach are: identifying latent groups with distinctive trajectories, estimating the proportion of the population in each group, linking individual-level covariates to group membership, assigning individuals to different groups, and creating group profiles based on posterior probabilities. We also discuss cautions and the controversies surrounding this approach. The major findings include four groups with distinct trajectories of remission from substance abuse.

Health care utilization and cost data have challenged analysts because they are often correlated over time, highly skewed, and clumped at 0. Traditional approaches do not address all these problems, and evaluators of mental health and substance abuse interventions often grapple with the problem of how to analyze these data in a way that accurately represents program impact. Recently, the traditional 2-part model has been extended to mixed-effects mixed-distribution model with correlated random effects to deal simultaneously with excess zeros, skewness, and correlated observations. We introduce and demonstrate this new method to mental health services researchers and evaluators by analyzing the data from a study of assertive community treatment (ACT). The response variable is the number of days of hospitalization, collected every 6 months over 3 years. The explanatory variable is group: ACT vs. standard case management. Diagnosis (schizophrenia vs. bipolar disorder), time, and the baseline values of hospital days are covariates. Results indicate that clients in the ACT group have a higher probability of hospital admission, but tend to have shorter lengths of stay. The mixed-distribution model provides greater specification of a model to fit these data and leads to more refined interpretation of the results.

Addiction research is challenged to disseminate evidence-based practices into routine clinical settings. The successful adoption of innovation must consider issues of fit, such as the characteristics, readiness, and attitudes of clinicians in the community. We constructed a survey to assess clinical practices and readiness to adopt certain evidence-based practices in addiction treatment programs. The instrument was administered to directors (n = 21) and clinicians (n = 89) from 24 public addiction treatment programs in New Hampshire (USA). Clinicians are more motivated to adopt some evidence-based practices (twelve-step facilitation, cognitive behavioral therapy, motivational interviewing, relapse prevention therapy) than others (contingency management, behavioral couples therapy, pharmacotherapies). Translational strategies for treatment development and research dissemination are discussed.

Background: Benzodiazepines have many benefits for persons with severe mental disorders, but they may also lead to or exacerbate substance abuse. An American Psychiatric Association taskforce established practice guidelines in 1990 to assist physicians in managing these and other potential side effects of benzodiazepine use. The objectives of this study were to determine the prevalence of benzodiazepine use among persons with psychiatric disorders and to evaluate compliance with published prescribing guidelines., Method: We studied benzodiazepine use among New Hampshire Medicaid beneficiaries aged 18 to 64 years with ICD-9 diagnoses that were grouped under the headings "schizophrenia," "bipolar disorder," "major depression," and "other psychiatric disorders" from Jan. 1995 through Dec. 1999. Rates and length of use, frequency of high-potency/fast-acting prescriptions, and diazepam-equivalent dosages were compared for those with and without retrospectively determined evidence of substance abuse, substance dependence, or a procedure code indicating treatment for a substance use disorder (SUD)., Results: Five-year prevalence of benzodiazepine use for persons with and without SUD was 63% versus 54% for schizophrenia, 75% versus 58% for bipolar disorder, 66% versus 49% for major depression, and 48% versus 40% for other psychiatric disorders. Differences were statistically significant over 5 years and in 1999 (p <.0001). Among persons with major depression or other psychiatric disorders, those with comorbid SUD were more likely to use fast-acting/high-potency benzodiazepines; there were no such differences for those with schizophrenia or bipolar disorder. Persons with bipolar disorder or other psychiatric disorders and SUD received significantly higher diazepam-equivalent dosages than did those without SUD., Conclusion: Contrary to published guidelines, rates of benzodiazepine use are higher among Medicaid beneficiaries with severe mental illness and co-occurring SUD than among persons with severe mental illness alone. Additional research and possibly a reassessment of prescribing guidelines are recommended.

Objectives: Because use of benzodiazepines may exacerbate existing substance use disorders or become abused substances, prescription of benzodiazepines for patients with severe mental illness (schizophrenia or bipolar disorder) and co-occurring substance use disorders (abuse or dependence) is controversial. The authors examined benzodiazepine use and associated psychiatric, substance abuse, and institutional outcomes in a six-year longitudinal study of patients with co-occurring disorders., Methods: At baseline and yearly follow-up for six years, 203 patients with co-occurring severe mental illness and substance use disorder were prospectively assessed for medication use, substance use, psychiatric symptoms, use of hospitalization, and quality of life., Results: Almost one-half of the patients (43 percent) reported taking prescribed benzodiazepines at the time of at least one assessment. Patients taking prescribed benzodiazepines were more likely to have high scores on measures of overall symptoms and affective symptoms (anxiety and depression) and low ratings for general quality of life throughout the study. Benzodiazepine use was unrelated to remission of substance use disorder or hospitalization, but a greater proportion of patients who were prescribed benzodiazepines developed benzodiazepine abuse, compared with those who were not prescribed benzodiazepines (15 percent compared with 6 percent)., Conclusions: Prescription benzodiazepine use was common among patients with co-occurring severe mental illness and a substance use disorder and was not associated with any of the measured outcomes other than increasing the likelihood of benzodiazepine abuse. Physicians should consider other treatments for anxiety in this population.

Investigators in mental health research are often interested in examining critical events such as onset, relapse, and recovery from illness, including substance use disorders. As data on these critical events are often collected at discrete-time intervals (e.g., weekly, monthly, or yearly), discrete-time survival models are more appropriate than well-known continuous-time methods. In this paper, we present discrete-time survival analysis methods at an introductory level. Using data collected every 6 months from a 3-year study of assertive community treatment in New Hampshire, we show that discrete-time survival models can be used to analyze patterns of remission from substance use disorder among clients with severe mental illness. The main questions investigated are (1) when are remissions more likely to occur? and (2) what variables predict remission? The results indicate that remission is more likely to occur in the first 6 months and in the 3rd year of the study. Gender, age, baseline use of substances, and diagnosis are strong predictors of remission.