BackgroundSocial media platforms such as Twitter are rapidly becoming key resources for public health surveillance applications, yet little is known about Twitter users’ levels of informedness and sentiment toward tobacco, especially with regard to the emerging tobacco control challenges posed by hookah and electronic cigarettes.ObjectiveTo develop a content and sentiment analysis of tobacco-related Twitter posts and build machine learning classifiers to detect tobacco-relevant posts and sentiment towards tobacco, with a particular focus on new and emerging products like hookah and electronic cigarettes.MethodsWe collected 7362 tobacco-related Twitter posts at 15-day intervals from December 2011 to July 2012. Each tweet was manually classified using a triaxial scheme, capturing genre, theme, and sentiment. Using the collected data, machine-learning classifiers were trained to detect tobacco-related vs irrelevant tweets as well as positive vs negative sentiment, using Naïve Bayes, k-nearest neighbors, and Support Vector Machine (SVM) algorithms. Finally, phi contingency coefficients were computed between each of the categories to discover emergent patterns.ResultsThe most prevalent genres were first- and second-hand experience and opinion, and the most frequent themes were hookah, cessation, and pleasure. Sentiment toward tobacco was overall more positive (1939/4215, 46% of tweets) than negative (1349/4215, 32%) or neutral among tweets mentioning it, even excluding the 9% of tweets categorized as marketing. Three separate metrics converged to support an emergent distinction between, on one hand, hookah and electronic cigarettes corresponding to positive sentiment, and on the other hand, traditional tobacco products and more general references corresponding to negative sentiment. These metrics included correlations between categories in the annotation scheme (phihookah-positive=0.39; phie-cigs-positive=0.19); correlations between search keywords and sentiment (χ2 4=414.50, P<.001, Cramer’s V=0.36), and the most discriminating unigram features for positive and negative sentiment ranked by log odds ratio in the machine learning component of the study. In the automated classification tasks, SVMs using a relatively small number of unigram features (500) achieved best performance in discriminating tobacco-related from unrelated tweets (F score=0.85).ConclusionsNovel insights available through Twitter for tobacco surveillance are attested through the high prevalence of positive sentiment. This positive sentiment is correlated in complex ways with social image, personal experience, and recently popular products such as hookah and electronic cigarettes. Several apparent perceptual disconnects between these products and their health effects suggest opportunities for tobacco control education. Finally, machine classification of tobacco-related posts shows a promising edge over strictly keyword-based approaches, yielding an improved signal-to-noise ratio in Twitter data and paving the way for automated tobacco surveillance ap...

Objective To review literature on the impact of FDA drug risk communications on medication utilization, health care services use, and health outcomes. Data Sources The authors searched MEDLINE and the Web of Science for manuscripts published between January 1990 and November 2010 that included terms related to drug utilization, the FDA, and advisories or warnings. We manually searched bibliographies and works citing selected articles and consulted with experts to guide study selection. Study Selection Studies were included if they involved an empirical analysis evaluating the impact of an FDA risk communication. Data Extraction We extracted the drug(s) analyzed, relevant FDA communication(s), data source, analytical method, and main outcome(s) assessed. Results Of the 1432 records screened, 49 studies were included. These studies covered sixteen medicines or therapeutic classes; one-third examined communications regarding antidepressants. Most used medical or pharmacy claims and few rigorously examined patient-provider communication, decision-making or risk perceptions. Advisories recommending increased clinical or laboratory monitoring generally led to decreased drug use, but only transient and modestly increased monitoring. Communications targeting specific subpopulations often spilled over to other groups. Repeated or sequential advisories tended to have larger but delayed effects and decreased incident more than prevalent use. Drug-specific warnings were associated with particularly large decreases in utilization, though the magnitude of substitution within therapeutic classes varied across clinical contexts. Conclusions While some FDA drug risk communications had immediate, strong impacts, many had either delayed or no impact on health care utilization or health behaviors. These data demonstrate the complexity of using risk communication to improve the quality and safety of prescription drug use, and suggest the importance of continued assessments of the effect of future advisories and label changes. Identifying factors that are associated with rapid and sustained responses to risk communications will be important for informing future risk communication efforts.

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Objectives Because of several recent clinical and regulatory changes regarding Attention Deficit Hyperactivity Disorder (ADHD) in the United States, we quantified changes in ADHD diagnosis and medication management from 2000 through 2010. Methods We used the IMS Health National Disease and Therapeutic Index™, a nationally representative audit of office-based providers, to examine aggregate trends among children and adolescents under 18. We also quantified how diagnosis and treatment patterns have evolved based on patient and physician characteristics and the therapeutic classes used. Results From 2000 to 2010, the number of physician outpatient visits where ADHD was diagnosed increased 66% from 6.2 million [M] (95% confidence intervals [CI] 5.5- 6.9M) to 10.4M visits (CI 9.3-11.6M). Of these visits, psychostimulants have remained the dominant treatment, used in 96% of treatment visits in 2000 and 87% of treatment visits in 2010. Atomoxetine use declined from 15% of treatment visits upon product launch in 2003 to 6% of treatment visits by 2010. The use of potential substitute therapies – clonidine, guanfacine, and bupropion – remained relatively constant (between 5-9% of treatment visits) during most of the period examined. Over this period, the ADHD management shifted towards psychiatrists (from 24% to 36% of all visits) without large changes in illness severity or the proportion of ADHD treatment visits accounted for by males (73%-77%). Conclusions In ten years, the ambulatory diagnosis of ADHD increased by two-thirds and is increasingly managed by psychiatrists. The effects of these changing treatment patterns on children's health outcomes and their families are unknown.