Electronic nicotine delivery systems ("e-cigarettes"): review of safety and smoking cessation efficacy.

BACKGROUND AND OBJECTIVES: Cigarette smoking is common among cancer patients and is associated with negative outcomes. Electronic nicotine delivery systems ("e-cigarettes") are rapidly growing in popularity and use, but there is limited information on their safety or effectiveness in helping individuals quit smoking. DATA SOURCES: The authors searched PubMed, Web of Science, and additional sources for published empirical data on safety and use of electronic cigarettes as an aid to quit smoking. REVIEW METHODS: We conducted a structured search of the current literature up to and including November 2013. RESULTS: E-cigarettes currently vary widely in their contents and are sometimes inconsistent with labeling. Compared to tobacco cigarettes, available evidence suggests that e-cigarettes are often substantially lower in toxic content, cytotoxicity, associated adverse effects, and secondhand toxicity exposure. Data on the use of e-cigarettes for quitting smoking are suggestive but ultimately inconclusive. CONCLUSIONS: Clinicians are advised to be aware that the use of e-cigarettes, especially among cigarette smokers, is growing rapidly. These devices are unregulated, of unknown safety, and of uncertain benefit in quitting smoking. IMPLICATIONS FOR PRACTICE: In the absence of further data or regulation, oncologists are advised to discuss the known and unknown safety and efficacy information on e-cigarettes with interested patients and to encourage patients to first try FDA-approved pharmacotherapies for smoking cessation.

A latent class approach to treatment readiness corresponds to a transtheoretical ("Stages of Change") model.

Motivation for treatment among people with substance use problems is an important aspect of treatment success. Models for treatment motivation are widely debated. Latent Class Analysis can help to demonstrate the appropriateness of available models. The current study utilizes Latent Class Analysis to analyze treatment readiness statements as they relate to the reduction or cessation of marijuana, cocaine, and opioid use among 539 cocaine and opioid users recruited from the community of Baltimore, MD, USA. Participants completed an in-person structured interview including demographic questions, a treatment readiness questionnaire with items on Intention to Stop Use (ISU) and Problem Recognition (PR), current substance abuse treatment utilization, and urinalysis testing for marijuana, cocaine, and heroin. Latent class models were fit to the treatment readiness questionnaire. A four-class model provided the best fit with one class low on both ISU and PR ("Pre-contemplative"), a second class low on ISU but high on PR ("Contemplative"), a third class high on both ("Preparation/Action"), and a final class high on ISU but low on PR ("Post-Action"). Compared to the "Contemplative" class, the "Pre-contemplative" class was significantly more likely to be positive for marijuana, and the "Post-Action" class was significantly less likely to be positive for opioids. The "Preparation/Action" class was significantly more likely to be in treatment. With the exception of the "Post-Action" class, the analysis appears similar to the "Stages of Change" model and suggests that problem recognition and intention to stop use are important domains in the model. However, further longitudinal research is needed to assess predictive validity of model.