Aims Smoking prevalence is higher among persons enrolled in addiction treatment as compared to the general population, and very high rates of smoking are associated with opiate drug use and receipt of opiate replacement therapy (ORT). We assessed whether these findings are observed internationally. Methods PubMed, PsycINFO and the Alcohol and Alcohol Problems Science Database were searched for papers reporting smoking prevalence among addiction treatment samples, published in English, from 1987 to 2013. Search terms included tobacco use, cessation, and substance use disorders using AND/OR Boolean connectors. For 4,549 papers identified, abstracts were reviewed by multiple raters. 239 abstracts met inclusion criteria and these full papers were reviewed for exclusion. 54 studies, collectively including 37,364 participants, were included. For each paper we extracted country, author, year, sample size and gender, treatment modality, primary drug treated, and smoking prevalence. Results The random-effect pooled estimate of smoking across persons in addiction treatment was 84% (CI 79%, 88%), while the pooled estimate of smoking prevalence across matched population samples was 31% (CI 29%, 33%). The difference in the pooled estimates was 52% (CI 48%, 57%, p < .0001). Smoking rates were higher in programs treating opiate use as compared to alcohol use (OR = 2.52, CI 2.00, 3.17), and higher in ORT compared to outpatient programs (OR = 1.42, CI 1.19, 1.68). Conclusions Smoking rates among people in addiction treatment are more than double those of people with similar demographic characteristics. Smoking rates are also higher in people being treated for opiate dependence compared with people being treated for alcohol use disorder.

BackgroundSeveral health organizations have adopted the 5A’s brief intervention model (Ask, Advise, Assess, Assist, Arrange), based on evidence-based guidelines for smoking cessation. We examine individual, cognitive, behavioral, and organizational factors associated with the 5A’s performance among clinical healthcare workers in Catalonia. We also investigate how these factors interact and potentially predict the implementation of each component of the 5A’s.MethodsA cross-sectional survey was conducted among clinical health workers enrolled in an online smoking cessation training course (n = 580). The survey included questions about individual characteristics as well as cognitive, behavioral, and organizational factors previously identified in research. We assessed self-reported performance of the 5A’s, assessed on a scale from 0 to 10, and used Multivariate regression to examine factors associated with its performance.ResultsThe performance means (standard deviation) were moderate for the first 3A’s [Ask: 6.4 (3.1); Advise: 7.1 (2.7); Assess: 6.3 (2.8)] and low for the last 2A’s [Assist: 4.4 (2.9); Arrange: 3.2 (3.3)]. We observed a high correlation between Assist and Arrange (r = 0.704, p < 0.001). Having positive experiences and feeling competent were positively associated with performing the 5A’s model and having organizational support with Assist and Arrange. Personal tobacco use among healthcare workers was negatively associated with Advice and Arrange.ConclusionsOur study found that clinical healthcare workers do not perform the 5A’s completely. The main barriers identified suggest the need of training and making available practical guidelines in healthcare services. Organizational support is essential for moving towards the implementation of Assist and Arrange.Electronic supplementary materialThe online version of this article (10.1186/s12971-017-0146-7) contains supplementary material, which is available to authorized users.

This study shows that simulation is an alternative that can be used to model inventory components in blood centers. A responsible selection of inventory variables can improve the capability of the system to respond to the final patient requirements.