Lung Cancer Mortality Is Elevated in Coal Mining Areas of Appalachia

Previous research has documented increased lung cancer incidence and mortality in Appalachia. The current study tests whether residence in coal mining areas of Appalachia is a contributing factor. We conducted a national county-level analysis to identify contributions of smoking rates, socioeconomic variables, coal mining intensity and other variables to age-adjusted lung cancer mortality. Results demonstrate that lung cancer mortality for the years 2000-2004 is higher in areas of heavy Appalachian coal mining after adjustments for smoking, poverty, education, age, sex, race and other covariates. Higher mortality may be the result of exposure to environmental contaminates associated with the coal mining industry, although smoking and poverty are also contributing factors. The knowledge of the geographic areas within Appalachia where lung cancer mortality is higher can be used to target programmatic and policy interventions. The set of socioeconomic and health inequalities characteristic of coal mining areas of Appalachia highlights the need to develop more diverse, alternative local economies

What May Be Associated with Young Adult E-Cigarette Use? Examination of Key Correlates

Given increasing rates of e-cigarette use among young adults, research is needed on the attitudes and beliefs that drive use among this age group. Tobacco control approaches used to prevent cigarette smoking may not work as effectively for preventing e-cigarette use. To address this research gap, the present study applied the Integrated Behavior Model (IBM) encompassing the affect heuristic theory to examine the individual-level determinants (i.e., attitude, perceived norm, personal agency, intention, and e-cigarette risk perception) of young adults\u27 e-cigarette use. The 2013-2014 Population Assessment of Tobacco and Health (PATH) Study Wave 1 baseline adult dataset consisted of 9,112 young adults (ages 18-24). A total of 3,887 (42.7%) reported ever having used an e-cigarette even one or two times, and reported now using e-cigarettes every day (n=160), some days (n=947), or not at all/non-users (2,780). Structural equation modeling (SEM) indicated that both the affect heuristic theory and constructs adapted from the IBM were significant drivers of e-cigarette use among young adults. The final structural model demonstrated acceptable fit (CFI = 0.935; TLI = 0.925; RMSEA = 0.024, 90% CI: 0.022-0.026). As expected for the IBM, as young adults’ positive feelings, perceived benefits, and normative beliefs of e-cigarettes increased, their intention to quit e-cigarettes decreased; which increased the likelihood of currently using e-cigarettes. As perceived benefit and positive feelings increased, young adults\u27 risk perceptions decreased resulting in a higher likelihood of using the device. These findings suggest that future communication, educational, and policy strategies to prevent e-cigarette use among young adults should highlight the health risk of e-cigarettes to address the high perceived benefits and low risk perceptions reported by young adults in this study

Developing a dissemination model to improve intervention reach among West Virginia youth smokers

The Not-On-Tobacco program is an evidence-based teen smoking cessation program adopted by the American Lung Association (ALA). Although widely disseminated nationally via ALA Master Trainers, in recent years, adoption and implementation of the N-O-T program in West Virginia has slowed. West Virginia, unfortunately, has one of the highest smoking rates in the US. Although it is a goal of public health science, dissemination of evidence-based interventions is woefully understudied. The present manuscript reviews a theoretical model of dissemination of the Not-On-Tobacco program in West Virginia. Based on social marketing, diffusion of innovations, and social cognitive theories, the nine-phase model incorporates elements of infrastructure development, accountability, training, delivery, incentives, and communication. The model components as well as preliminary lessons learned from initial implementation are discussed

Benchmarking Representation Learning for Natural World Image Collections

Recent progress in self-supervised learning has resulted in models that are capable of extracting rich representations from image collections without requiring any explicit label supervision. However, to date the vast majority of these approaches have restricted themselves to training on standard benchmark datasets such as ImageNet. We argue that fine-grained visual categorization problems, such as plant and animal species classification, provide an informative testbed for self-supervised learning. In order to facilitate progress in this area we present two new natural world visual classification datasets, iNat2021 and NeWT. The former consists of 2.7M images from 10k different species uploaded by users of the citizen science application iNaturalist. We designed the latter, NeWT, in collaboration with domain experts with the aim of benchmarking the performance of representation learning algorithms on a suite of challenging natural world binary classification tasks that go beyond standard species classification. These two new datasets allow us to explore questions related to large-scale representation and transfer learning in the context of fine-grained categories. We provide a comprehensive analysis of feature extractors trained with and without supervision on ImageNet and iNat2021, shedding light on the strengths and weaknesses of different learned features across a diverse set of tasks. We find that features produced by standard supervised methods still outperform those produced by self-supervised approaches such as SimCLR. However, improved self-supervised learning methods are constantly being released and the iNat2021 and NeWT datasets are a valuable resource for tracking their progress.Comment: CVPR 202

Almost Everything We Need to Better Serve Children of the Opioid Crisis We Learned in the 80s and 90s

Opioid use disorder impedes dependent parents' abilities to care for their children. In turn, children may languish in unpredictability and persistent chaos. Societal responses to these children are often guided by a belief that unless the drug dependent parent receives treatment, there is little help for the child. While a preponderance of the drug dependence research is adult-centric, a significant body of research demonstrates the importance of not only addressing the immediate well being of the children of drug dependent caregivers but preventing the continuing cycle of drug dependence. The present commentary demonstrates through a brief review of the US history of drug dependence crises and research from the 1980s and 1990s, a range of “tried and true” family, school, and community interventions centered on children. We already know that these children are at high risk of maladjustment and early onset of drug dependence; early intervention is critical; multiple risk factors are likely to occur simultaneously; comprehensive strategies are optimal; and multiple risk-focused strategies are most protective. Where we need now to turn our efforts is on how to effectively implement and disseminate best practices, many of which we learned in the 1980s and 1990s. The greatest opportunity in both changing the nature of the opioid epidemic at scale and influencing rapid translation of existing research findings into policy and practice is not in asking what to do, but in asking how to do the right things well, and quickly

A profile of teen smokers who volunteered to participate in school-based smoking intervention

<p>Abstract</p> <p>Objectives</p> <p>Although a number of population-based studies have examined the characteristics of teens who attempt to quit smoking, few have identified the characteristics of youth who participate in structured cessation interventions, particularly those with demonstrated effectiveness. The purpose of the present study is to describe the sociodemographic and smoking-related characteristics of teen smokers who participated in the American Lung Association's Not On Tobacco (N-O-T) program, spanning eight years. N-O-T is the most widely used teen smoking cessation program in the nation.</p> <p>Methods</p> <p>Drawn from multiple statewide N-O-T studies, this investigation examined data from 5,892 teen smokers ages 14–19 who enrolled in N-O-T between 1998–2006. We demonstrate similarities and differences between N-O-T findings and existing data from representative samples of US teen smokers where available and relevant.</p> <p>Results</p> <p>N-O-T teens started smoking earlier, were more likely to be poly-tobacco users, were more dependent on nicotine, had made more previous attempts to quit, and were more deeply embedded in smoking contexts than comparative samples of teen smokers. Additionally, N-O-T teens were moderately ready to quit smoking, believed important people in their lives would support their quit efforts, yet had deficits in their confidence with quitting.</p> <p>Conclusion</p> <p>This profile of N-O-T teens can guide efforts for targeted recruitment strategies to enhance intervention reach for teen smoking cessation. Findings provide guidance for marketing and recruitment efforts of intensive, school-based cessation interventions among established teen smokers, particularly those who want to quit. Study results may shed light upon who is and is not enrolling in N-O-T.</p

Sonneries Woodwind Quintet

Kemp Recital Hall Monday Evening April 5, 1999 8:00p.m