Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Signs and customer behaviors at vape shops: Multivariate multilevel model analysis.

IntroductionThis study examined vape shop customers' behaviors in relation to shop display practices. We hypothesized that display of signs conveying supportive attitude toward vaping at vape shops would be positively associated with customer purchasing and in-shop vaping behaviors.MethodsWe recruited vape shops throughout Southern California (N = 122). Trained teams of data collectors visited each of the consented vape shops, observed customers' characteristics and behaviors (N = 254) and coded items in the shops that were visible and on display. We conducted a multivariate multilevel analysis to account for the data structure where customers were nested within vape shops.ResultsMale customers were more likely to purchase e-liquid at the shop than female customers (p < .001). There were no sex differences vaping at the shop (p = .353). We observed more customers vaping at shops with e-cigarette safety displays (p = .024) and more customers purchasing e-liquid at shops with quit smoking signage (p = .004). Point-of-sale displays were not associated with either customer vaping or purchasing behaviors observed at the shop. Displays of state-regulated and nonregulated (i.e., tobacco industry) age-of-sale compliance signs, Ask4ID and WeCard, were not significantly associated with customer vaping or purchase behaviors.ConclusionCertain display signs present at vape shops might communicate to customers that engaging in certain behaviors (e.g., vaping inside the shops) may be safe or acceptable

Signs and customer behaviors at vape shops: Multivariate multilevel model analysis.

IntroductionThis study examined vape shop customers' behaviors in relation to shop display practices. We hypothesized that display of signs conveying supportive attitude toward vaping at vape shops would be positively associated with customer purchasing and in-shop vaping behaviors.MethodsWe recruited vape shops throughout Southern California (N = 122). Trained teams of data collectors visited each of the consented vape shops, observed customers' characteristics and behaviors (N = 254) and coded items in the shops that were visible and on display. We conducted a multivariate multilevel analysis to account for the data structure where customers were nested within vape shops.ResultsMale customers were more likely to purchase e-liquid at the shop than female customers (p < .001). There were no sex differences vaping at the shop (p = .353). We observed more customers vaping at shops with e-cigarette safety displays (p = .024) and more customers purchasing e-liquid at shops with quit smoking signage (p = .004). Point-of-sale displays were not associated with either customer vaping or purchasing behaviors observed at the shop. Displays of state-regulated and nonregulated (i.e., tobacco industry) age-of-sale compliance signs, Ask4ID and WeCard, were not significantly associated with customer vaping or purchase behaviors.ConclusionCertain display signs present at vape shops might communicate to customers that engaging in certain behaviors (e.g., vaping inside the shops) may be safe or acceptable

Predictors of Vape Shops Going out of Business in Southern California.

ObjectivesVape shops have proliferated in the United States (US) in recent years. As of May 2016, the US Food and Drug Administration (FDA) asserted its authority to regulate electronic nicotine delivery systems. It is critical to understand how these polices have affected the vape shop industry, as the rise and fall of vape shop proliferation has the potential for influencing public health.MethodsIn this longitudinal study, we examined factors associated with vape shop (N = 77) closure over a 2-1/2-year period in southern California. We assessed predictors of vape shops going out of business using a multivariate logistic regression model.ResultsAmong 77 vape shops assessed at baseline, 44.2% closed over a 2-1/2-year period. The absence of a "bar type" physical environment (OR = 2.64, 95% CI = 1.12-6.20), poorer shop accessibility (OR = 7.11, 95% CI = 1.17-43.24), fewer reports of qualified personnel (OR = 2.28, 95% CI = 1.12-4.64), less average time spent in shop by customers (OR = 4.8, 95% CI = 1.18-19.60), a narrower e-liquid flavor selection (OR = 6.55, 95% CI = 1.56-27.49), and less vape device diversity (OR = 2.36, 95% C = 1.13-4.91) predicted vape shop closure.ConclusionsThe rise and subsequent decline in vape shops could potentially affect public health. However, there needs to be more research on their association with public health.

Predictors of Vape Shops Going out of Business in Southern California.

ObjectivesVape shops have proliferated in the United States (US) in recent years. As of May 2016, the US Food and Drug Administration (FDA) asserted its authority to regulate electronic nicotine delivery systems. It is critical to understand how these polices have affected the vape shop industry, as the rise and fall of vape shop proliferation has the potential for influencing public health.MethodsIn this longitudinal study, we examined factors associated with vape shop (N = 77) closure over a 2-1/2-year period in southern California. We assessed predictors of vape shops going out of business using a multivariate logistic regression model.ResultsAmong 77 vape shops assessed at baseline, 44.2% closed over a 2-1/2-year period. The absence of a "bar type" physical environment (OR = 2.64, 95% CI = 1.12-6.20), poorer shop accessibility (OR = 7.11, 95% CI = 1.17-43.24), fewer reports of qualified personnel (OR = 2.28, 95% CI = 1.12-4.64), less average time spent in shop by customers (OR = 4.8, 95% CI = 1.18-19.60), a narrower e-liquid flavor selection (OR = 6.55, 95% CI = 1.56-27.49), and less vape device diversity (OR = 2.36, 95% C = 1.13-4.91) predicted vape shop closure.ConclusionsThe rise and subsequent decline in vape shops could potentially affect public health. However, there needs to be more research on their association with public health.

Hypothetical flavour ban and intention to vape among vape shop customers: the role of flavour preference and e-cigarette dependence.

E-cigarette users typically initiate vaping with flavoured e-liquids. People who vape flavours tend to underestimate the harm of vaping. We examined the inter-relationship between flavour preference, vaping for cessation purposes, e-cigarette dependence, e-cigarette harm perception and purchase/use intention, given a hypothetical flavour ban. We hypothesised that non-tobacco flavour preference and vaping for cessation would be negatively associated with harm perception of e-cigarettes and intention to continue vaping if a flavour ban occurred and that these effects would be mediated by e-cigarette dependence. From July 2019 to March 2020, we conducted intercept interviews with 276 customers at 44 vape shops in California. The predictor variables were flavour preference and vaping for cessation. The outcome variables were harm perception of e-cigarettes and intention to purchase/use, given a hypothetical flavour ban. Multilevel structural equation modelling tested whether e-cigarette dependence mediates the effects of flavour preference on hypothetical continued vaping and purchase. Those who preferred flavours showed significantly lower intention to purchase e-liquids (β=-0.28, p<0.001) and to continue vaping (β=-0.17, p=0.001), given a hypothetical flavour ban. Those who vaped for smoking cessation indicated greater intention to purchase e-liquid (β=0.10, p=0.016) and to continue vaping (β=0.17, p=0.001), given a hypothetical flavour ban. E-cigarette dependence significantly mediated these effects (ps<0.04). Flavour preference was negatively related to intention to continue to vape within a hypothetical flavour ban. Our results also highlight the importance of e-cigarette dependence and use of e-cigarettes as smoking cessation methods. Implications for future flavour bans are discussed