Peer crowd affiliation as a segmentation tool for young adult tobacco use.

BackgroundIn California, young adult tobacco prevention is of prime importance; 63% of smokers start by the age of 18 years, and 97% start by the age of 26 years. We examined social affiliation with 'peer crowd' (eg, Hipsters) as an innovative way to identify high-risk tobacco users.MethodsCross-sectional surveys were conducted in 2014 (N=3368) among young adult bar patrons in 3 California cities. We examined use rates of five products (cigarettes, e-cigarettes, hookah, cigars and smokeless tobacco) by five race/ethnicity categories. Peer crowd affiliation was scored based on respondents' selecting pictures of young adults representing those most and least likely to be in their friend group. Respondents were classified into categories based on the highest score; the peer crowd score was also examined as a continuous predictor. Logistic regression models with each tobacco product as the outcome tested the unique contribution of peer crowd affiliation, controlling for race/ethnicity, age, sex, sexual orientation and city.ResultsRespondents affiliating with Hip Hop and Hipster peer crowds reported significantly higher rates of tobacco use. As a categorical predictor, peer crowd was related to tobacco use, independent of associations with race/ethnicity. As a continuous predictor, Hip Hop peer crowd affiliation was also associated with tobacco use, and Young Professional affiliation was negatively associated, independent of demographic factors.ConclusionsTobacco product use is not the same across racial/ethnic groups or peer crowds, and peer crowd predicts tobacco use independent of race/ethnicity. Antitobacco interventions targeting peer crowds may be an effective way to reach young adult tobacco users.Trial registration numberNCT01686178, Pre-results

Peer crowd-based targeting in E-cigarette advertisements: a qualitative study to inform counter-marketing.

BACKGROUND:Cigarette lifestyle marketing with psychographic targeting has been well documented, but few studies address non-cigarette tobacco products. This study examined how young adults respond to e-cigarette advertisements featuring diverse peer crowds - peer groups with shared identities and lifestyles - to inform tobacco counter-marketing design. METHODS:Fifty-nine young adult tobacco users in California participated in interviews and viewed four to five e-cigarette advertisements that featured characters from various peer crowd groups. For each participant, half of the advertisements they viewed showed characters from the same peer crowd as their own, and the other half of the advertisements featured characters from a different peer crowd. Advertisements were presented in random order. Questions probed what types of cues are noticed in the advertisements, and whether and how much participants liked or disliked the advertisements. RESULTS:Results suggest that participants liked and provided richer descriptions of characters and social situations in the advertisements featuring their own peer crowd more than the advertisements featuring a different peer crowd. Mismatching age or device type was also noted: participants reported advertisements showing older adults were not intended for them. Participants who used larger vaporizers tended to dislike cigalike advertisements even if they featured a matching peer crowd. CONCLUSION:Peer crowd and lifestyle cues, age and device type are all salient features of e-cigarette advertising for young adults. Similarly, educational campaigns about e-cigarettes should employ peer crowd-based targeting to engage young adults, though messages should be carefully tested to ensure authentic and realistic portrayals

Reconstructed Intentions in Collaborative Problem Solving Dialogues

We provide evidence that speech act recognition, is 1) difficult for humans to do and 2) likely to misidentify proposals involving reconstructed intentions. We examine the reliability of coding for speech acts in collaborative dialogues and we present an approach for recognizing reconstructed proposals using domain context and other more easily recognized features. 1 Introduction Speech act recognition plays a prominent role in dialogue understanding, in traditional approaches that infer a plan using plan construction operators [PA80], [LA90], [LC91, LC92], and in more recent techniques relying on statistical correlations or finite state machines [RM95, QDL + 97]. Both approaches recognize surface speech acts, using surface form and information provided by the discourse context and the discourse operators, or by a finite state approximation of the planning information. These approaches assume that it is (relatively) simple to recognize speech acts, and that speech acts are a requi..

The world-sheet description of A and B branes revisited

We give a manifest supersymmetric description of A and B branes on Kahler manifolds using a completely local N=2 superspace formulation of the world-sheet nonlinear sigma-model in the presence of a boundary. In particular, we show that an N=2 superspace description of type A boundaries is possible, at least when the background is Kahler. This leads to an elegant and concrete setting for studying coisotropic A branes. Here, apgesan important role is played by the boundary potential, whose precise physical meaning remains to be fully understood. Duality transformations relating A and B branes in the presence of isometries are studied as well.Comment: LaTeX, 32 page

Bars, Nightclubs, and Cancer Prevention: New Approaches to Reduce Young Adult Cigarette Smoking.

IntroductionTobacco contributes to multiple cancers, and it is largely preventable. As overall smoking prevalence in California declines, smoking has become concentrated among high-risk groups. Targeting social/cultural groups (i.e., "peer crowds") that share common values, aspirations, and activities in social venues like bars and nightclubs may reach high-risk young adult smokers. Lack of population data on young adult peer crowds limits the ability to assess the potential reach of such interventions.MethodsThis multimodal population-based household survey included young adults residing in San Francisco and Alameda counties. Data were collected in 2014 and analyzed in 2016. Multivariable logistic regressions assessed smoking by sociodemographic factors, attitudes, self-rated health, peer crowd affiliation, and bar/nightclub attendance.ResultsSmoking prevalence was 15.1% overall; 35.3% of respondents sometimes or frequently attended bars. In controlled analyses, bar attendance (AOR=2.13, 95% CI=1.00, 4.53) and binge drinking (AOR=3.17, 95% CI=1.59, 6.32) were associated with greater odds of smoking, as was affiliation with "Hip Hop" (AOR=4.32, 95% CI=1.48, 12.67) and "Country" (AOR=3.13, 95% CI=1.21, 8.09) peer crowds. Multivariable models controlling for demographics estimated a high probability of smoking among bar patrons affiliating with Hip Hop (47%) and Country (52%) peer crowds.ConclusionsBar attendance and affiliation with certain peer crowds confers significantly higher smoking risk. Interventions targeting Hip Hop and Country peer crowds could efficiently reach smokers, and peer crowd-tailored interventions have been associated with decreased smoking and binge drinking. Targeted interventions in bars and nightclubs may be an efficient way to address these cancer risks

Advancing the use of gridded, online climate information for risk management in the Horn of Africa

This report summarizes the discussions, deliberations and recommendations made during the side event, Advancing the use of gridded, online climate information for risk management in the Horn of Africa, to the Forty Eighth Greater Horn of Africa Climate Outlook Forum (GHACOF 48). This event was co-organized by the Climate Services for Africa project—led by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS)—and the Weather and Climate Information Services for Africa (WISER) - qEnhancing National Climate Services initiative (ENACTS), that was held on 13 February 2018 in Mombasa, Kenya. The main aim of the event was to advance shared understanding, between climate information users and providers on how the GHACOF process and member country National Meteorological and Hydrological Services (NMHSs) can support more effective use of climate information. The meeting was geared towards raising awareness on recent developments in climate information products developed for the agriculture and food security sector through the ENACTS approach and demonstrate ICPAC capabilities to support member countries in the development of gridded historical and seasonal forecast climate information Maproom products tailored to user needs. Agro-climatic variables showcased included rainfall onset dates (both in historical and forecast mode), cessation dates, historical wet and dry spells, and rainfall intensity. The meeting was also intended to bring an informed agriculture user perspective into a discussion with ICPAC and NMHSs about how the GHACOF process can be made more useful for the agriculture and food security sector. The workshop brought together representatives from member country NMHSs, experienced agricultural and food security users and champions of climate information, ICPAC, WMO, and WISER and Climate Services for Africa project partners. Workshop participants appreciated the importance of these agro-climatic variables in making timely and informed decisions

Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records

Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363–372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h2g) and genetic correlation (rg) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency—“coded-strict”, “coded-broad”, and “coded-broad based on a single clinical encounter” (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h2g were 0.24 (p = 0.015), 0.09 (p = 0.064), 0.13 (p = 0.003), 0.00 (p = 0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h2g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h2g) was 0.12 (p = 0.004). These h2g were lower or similar to the h2g observed by the ICCBD + PGCBD (0.23, p = 3.17E−80, total N = 33,181). However, the rg between ICCBD + PGCBD and the EHR-based cases were high for 95-NLP (0.66, p = 3.69 × 10–5), coded-strict (1.00, p = 2.40 × 10−4), and coded-broad (0.74, p = 8.11 × 10–7). The rg between EHR-based BD definitions ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research

Cross-Disorder Genomewide Analysis of Schizophrenia, Bipolar Disorder, and Depression

Family and twin studies indicate substantial overlap of genetic influences on psychotic and mood disorders. Linkage and candidate gene studies have also suggested overlap across schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD). The objective of this study was to apply genomewide association study (GWAS) analysis to address the specificity of genetic effects on these disorders