Combined expectancies of alcohol and e-cigarette use relate to higher alcohol use

Electronic cigarettes (e-cigs) were created to approximate the look, feel, and experience of using a cigarette. Since cigarette and alcohol use co-occur, we hypothesized that e-cig and alcohol use also co-occur, likely due to shared positive drug expectations. Using self-report data from two independent samples of community-dwelling alcohol using adults, the present study: (1) modified the Nicotine and Other Substance Interaction Expectancy Questionnaire (NOSIE) to assess expectancies of combined e-cig and alcohol use (i.e. the individuals perceived likelihood of using e-cigs and alcohol together; NOSIE-ER); and (2) examined the relationships among e-cig use, expectancies, and alcohol use across e-cig use status. In the first sample (N=692, mean age=32.6, SD=9.74, 50.7% female, 82.2% Caucasian), exploratory factor analysis suggested the presence of two factors: (1) alcohol use leads to e-cig use (Scale 1; α=0.85); and (2) e-cig use leads to alcohol use (Scale 2; α=0.91). In the second sample (N=714, mean age=34.1, SD=10.89, 47.8% female, 75.6% Caucasian), confirmatory factor analysis supported this factor structure (χ(2)=47.00, p<0.01, df=19; RMSEA=0.08, 90% CI=0.05-0.11; TLI=0.99; CFI=0.99). Compared to non e-cig users, e-cig users had significantly higher problematic alcohol use in both samples (b's=0.09 to 0.14, p's<.05). Expectancies of combined e-cig and alcohol use were significantly related to problematic alcohol use (b's=-0.92 to 0.26, p's<.05). In sum, e-cig use is related to alcohol use and expectancies of combined e-cig and alcohol use; consequently, reshaping of beliefs about needs or desires to co-use could be a prime point of intervention

UPPS-P Model Impulsivity and Marijuana Use Behaviors in Adolescents: A Meta-Analysis

Background Impulsivity is often included as a risk factor in models of adolescent marijuana use behaviors; however, the magnitude of the association between impulsivity and marijuana use behaviors is variable across studies. The present study reviewed existent literature to 1) quantify the relationship between separable impulsivity-related traits and both marijuana use and negative marijuana consequences and 2) quantify the size of the effect of gender on these relationships. Method Thirty-eight studies (41 independent samples) were meta-analyzed using a random effects model to examine the relationship between impulsivity traits and marijuana use behaviors. Results Marijuana use was significantly related to all impulsivity-related traits except lack of perseverance (r’s ranging from 0.13–0.23, p’s < 0.01). Negative marijuana consequences were only significantly related to sensation seeking, lack of planning, and positive urgency (r’s ranging from 0.37–0.39, p’s < 0.01). Effects were small for marijuana use, but medium for negative marijuana consequences. Gender was not a significant moderator of any relationships. Conclusions Impulsivity-related traits had more robust relationships with negative marijuana consequences than marijuana use, suggesting impulsivity-related traits are important in differentiating adolescents most likely to experience negative consequences from marijuana use. Few relationships examined gender and many of the impulsivity-related traits, other than sensation seeking. Data and trends suggest a more multi-dimensional approach to marijuana use and consequences is warranted

Sparse Fault-Tolerant BFS Trees

This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph $T$ of the given network $G$ such that subsequent to the failure of a single edge or vertex, the surviving part $T'$ of $T$ still contains a BFS spanning tree for (the surviving part of) $G$. Our main results are as follows. We present an algorithm that for every $n$-vertex graph $G$ and source node $s$ constructs a (single edge failure) FT-BFS tree rooted at $s$ with O(n \cdot \min\{\Depth(s), \sqrt{n}\}) edges, where \Depth(s) is the depth of the BFS tree rooted at $s$. This result is complemented by a matching lower bound, showing that there exist $n$-vertex graphs with a source node $s$ for which any edge (or vertex) FT-BFS tree rooted at $s$ has $\Omega(n^{3/2})$ edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source $s\in S$ for some subset of sources $S\subseteq V$. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every $n$-vertex graph and source set $S \subseteq V$ of size $\sigma$ constructs a (single failure) FT-MBFS tree $T^*(S)$ from each source $s_i \in S$, with $O(\sqrt{\sigma} \cdot n^{3/2})$ edges, and on the other hand there exist $n$-vertex graphs with source sets $S \subseteq V$ of cardinality $\sigma$, on which any FT-MBFS tree from $S$ has $\Omega(\sqrt{\sigma}\cdot n^{3/2})$ edges. Finally, we propose an $O(\log n)$ approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no $\Omega(\log n)$ approximation algorithm for these problems under standard complexity assumptions

Beliefs About the Direct Comparison of E-Cigarettes and Cigarettes

Background: Recent data suggests that positive beliefs about electronic cigarettes (e-cigs) use can lead to later e-cig use. Considering that many advertisements claim that e-cigs are superior to cigarettes, individuals' likelihood to view e-cigs more favorably than cigarettes can also influence subsequent e-cig use; however, no studies have directly assessed such a comparison. Objectives: The present study created and validated the Comparing E-Cigarettes and Cigarettes questionnaire (CEAC), which asks individuals to directly compare e-cigs and cigarettes on a number of dimensions, in two independent samples. Methods: In sample 1 (451 undergraduates; mean age = 20.35, SD = 5.44, 72.4% female, 73.4% Caucasian) we explored the factor structure of the CEAC and in sample 2 (699 community adults collected via Amazon's Mechanical Turk; mean age = 34.04, SD = 10.9, 47.7% female, 83.3% Caucasian) we replicated the factor structure. Results: Exploratory factor analysis suggested a three-factor structure: General Benefits (α = 0.80), General Effects (α = 0.86), and Health Benefits (α = 0.88), which was replicated via confirmatory factor analysis, χ2 = 4.36; RMSEA = 0.07, 90% CI = 0.06–0.08; TLI = 0.99; CFI = 0.99, and was relatively invariant across product use and gender. Individuals reported viewing e-cigs as safer and more beneficial than cigarettes and these beliefs were higher in e-cig users. Conclusions: Future work should establish how these comparative beliefs are influenced by e-cig use and/or influence subsequent transition to and increases in e-cig use. Although e-cigs are likely less harmful than cigarettes, and thus these comparative beliefs represent that state of nature, e-cigs are not completely without risk

Transitioning from cigarettes to electronic cigarettes increases alcohol consumption

Objective Electronic cigarettes (e-cigs) are a nicotine delivery device that have recently been linked to alcohol use. Many individuals that smoke cigarettes transition to e-cigs as an alternative to cigarette use, despite potential negative health effects of e-cigs. No research to date has examined how former smokers that have transitioned to e-cigs differ from former smokers that do not use e-cigs, particularly in relation to alcohol use. Further, no research has examined how former smokers that use e-cigs regularly or socially may differ in alcohol consumption. Method Using an online community dwelling sample (Former smokers N=198, mean age=34.70, SD=11.45, 56.1% female, 78.3% Caucasian, 37.9% e-cig users), the present study assessed smoking status and alcohol use, with the latter assessed using a Timeline Followback calendar and the Alcohol Use Disorder Identification Test (AUDIT). Results In all former smokers, total drinks (b=4.01, p=0.02) and average drinks per drinking day (b=0.61, p=.01) were both related to e-cig use status, with e-cig users reporting higher alcohol consumption. Among e-cig using former smokers, social users, but not regular users, showed positive relationships with AUDIT scores, b=1.90, p=.02, total drinks, b=9.12, p<.001, average drinks, b=0.98, p=.006, and hazardous drinking status, OR=3.21, p=.01. Conclusions Findings suggest that: (1) former smokers who use e-cigs may have a potential for higher alcohol use; and (2) those who use e-cigs socially may be at heightened risk for hazardous patterns of alcohol consumption. This should be taken into consideration by healthcare providers

Guarding art galleries by guarding witnesses

Let P be a simple polygon. We de ne a witness set W to be a set of points su h that if any (prospective) guard set G guards W, then it is guaranteed that G guards P . We show that not all polygons admit a nite witness set. If a fi nite minimal witness set exists, then it cannot contain any witness in the interior of P ; all witnesses must lie on the boundary of P , and there an be at most one witness in the interior of any edge. We give an algorithm to compute a minimal witness set for P in O(n2 log n) time, if such a set exists, or to report the non-existence within the same time bounds. We also outline an algorithm that uses a witness set for P to test whether a (prospective) guard set sees all points in P

Computing a rectilinear shortest path amid splinegons in plane

We reduce the problem of computing a rectilinear shortest path between two given points s and t in the splinegonal domain \calS to the problem of computing a rectilinear shortest path between two points in the polygonal domain. As part of this, we define a polygonal domain \calP from \calS and transform a rectilinear shortest path computed in \calP to a path between s and t amid splinegon obstacles in \calS. When \calS comprises of h pairwise disjoint splinegons with a total of n vertices, excluding the time to compute a rectilinear shortest path amid polygons in \calP, our reduction algorithm takes O(n + h \lg{n}) time. For the special case of \calS comprising of concave-in splinegons, we have devised another algorithm in which the reduction procedure does not rely on the structures used in the algorithm to compute a rectilinear shortest path in polygonal domain. As part of these, we have characterized few of the properties of rectilinear shortest paths amid splinegons which could be of independent interest