scholarly journals An E-Liquid Flavor Wheel: A Shared Vocabulary Based on Systematically Reviewing E-Liquid Flavor Classifications in Literature

2018 ◽  
Vol 21 (10) ◽  
pp. 1310-1319 ◽  
Author(s):  
Erna J Z Krüsemann ◽  
Sanne Boesveldt ◽  
Kees de Graaf ◽  
Reinskje Talhout
Keyword(s):  
Data Interpretation ◽  
Qualitative Studies ◽  
Electronic Cigarette ◽  
Cigarette Use ◽  
Policy Makers ◽  
Systematic Classification ◽  
Support Policy ◽  
Similarities And Differences ◽  
Comparability Of Results

Abstract Introduction E-liquids are available in a high variety of flavors. A systematic classification of e-liquid flavors is necessary to increase comparability of research results. In the food, alcohol, and fragrance industry, flavors are classified using flavor wheels. We systematically reviewed literature on flavors related to electronic cigarette use, to investigate how e-liquid flavors have been classified in research, and propose an e-liquid flavor wheel to classify e-liquids based on marketing descriptions. Methods The search was conducted in May 2017 using PubMed and Embase databases. Keywords included terms associated with electronic cigarette, flavors, liking, learning, and wanting in articles. Results were independently screened and reviewed. Flavor categories used in the articles reviewed were extracted. Results Searches yielded 386 unique articles of which 28 were included. Forty-three main flavor categories were reported in these articles (eg, tobacco, menthol, mint, fruit, bakery/dessert, alcohol, nuts, spice, candy, coffee/tea, beverages, chocolate, sweet flavors, vanilla, and unflavored). Flavor classifications of e-liquids in literature showed similarities and differences across studies. Our proposed e-liquid flavor wheel contains 13 main categories and 90 subcategories, which summarize flavor categories from literature to find a shared vocabulary. For classification of e-liquids using our flavor wheel, marketing descriptions should be used. Conclusions We have proposed a flavor wheel for classification of e-liquids. Further research is needed to test the flavor wheels’ empirical value. Consistently classifying e-liquid flavors using our flavor wheel in research (eg, experimental, marketing, or qualitative studies) minimizes interpretation differences and increases comparability of results. Implications We reviewed e-liquid flavors and flavor categories used in research. A large variation in the naming of flavor categories was found and e-liquid flavors were not consistently classified. We developed an e-liquid flavor wheel and provided a guideline for systematic classification of e-liquids based on marketing descriptions. Our flavor wheel summarizes e-liquid flavors and categories used in literature in order to create a shared vocabulary. Applying our flavor wheel in research on e-liquids will improve data interpretation, increase comparability across studies, and support policy makers in developing rules for regulation of e-liquid flavors.

Electronic cigarette use in restaurants and workplaces where combustible tobacco smoking is not allowed: an Internet survey in Japan

2017 ◽  
Vol 27 (3) ◽  
pp. 254-257 ◽  
Author(s):  
Kosuke Kiyohara ◽  
Takahiro Tabuchi
Keyword(s):  
Tobacco Smoking ◽  
Educational Level ◽  
Electronic Cigarette ◽  
Internet Survey ◽  
Cigarette Use ◽  
Regression Analyses ◽  
Policy Makers ◽  
Factors Associated ◽  
Japanese Adults ◽  
Potential Factors

BackgroundThe present study aimed to examine the experience of actual electronic cigarette (e-cigarette) use in smoke-free areas of restaurants and workplaces and to explore the determinants associated with such use among Japanese adults who reported any experience using e-cigarettes (e-cigarette ever-users).MethodsAn Internet-based self-reported questionnaire survey was conducted in 2015 on Japanese e-cigarette ever-users. The proportion of the respondents who had ever used or frequently used e-cigarettes in smoke-free restaurants and/or workplaces was calculated. Potential factors associated with e-cigarette use in those smoke-free areas were also examined by using multivariable logistic regression analyses.ResultsIn total, 1243 e-cigarette ever-users (662 current and 581 former e-cigarette users) were analysed. The majority of them (1020/1243, 82.1%) were male and their mean age ± SD was 47.0±10.4 years. The proportion of those who had ever used e-cigarettes in smoke-free restaurants was 28.8% (358/1243) and that in smoke-free workplaces was 25.5% (317/1243), respectively. The proportion of those who had frequently used e-cigarettes in smoke-free restaurants was 18.5% (230/1243) and that in smoke-free workplaces was 16.3% (202/1243), respectively. In general, the proportion of e-cigarette use in those smoke-free areas was higher among those having a higher educational level than those having a lower educational level.ConclusionAmong adult Japanese e-cigarette ever-users, approximately 26%–29% had ever used and 16%–19% had frequently used e-cigarettes in restaurants and/or workplaces where combustible tobacco smoking is not allowed. Policy-makers may need to establish explicit rules as to e-cigarette use in smoke-free environments.

scholarly journals ‘Malenkey Robot’ in the Carpathian Basin, in Hungary – Data, Facts, Interpretations, Connections

2015 ◽  
Vol 7 (1) ◽  
pp. 5-16
Author(s):  
Zalán Bognár
Keyword(s):  
Data Interpretation ◽  
Carpathian Basin ◽  
Effective Number ◽  
The Real ◽  
Real Value ◽  
Similarities And Differences ◽  
Archive Data

Abstract Interpretation problems related to the notion of ‘malenkaya rabota,’ POW, internee, GULAG and GUPVI. Ways of classification of the victims of ‘malenkaya rabota' in the Carpathian Basin, various groups and types. Determination of the effective number of the groups, and of the total number of those deported as civilians from the 14.7 million inhabitants of the Hungary of the time, based on different data, and the difficulties of definitions. The interpretation and implementation of the central Soviet commands. The connections between the deportations. Similarities and differences between the deportations as internee and as POW. Manageability of the data, interpretation of Soviet and Hungarian archive data and the reasons why they are different. The real value of Soviet archival sources. The determination of the losses attributed to ‘malenkaya rabota’.

Classification of the Foraminiferida

1982 ◽  
Vol 6 ◽  
pp. 22-36 ◽  
Author(s):  
Alfred R. Loeblich ◽  
Helen Tappan
Keyword(s):  
The State ◽  
Systematic Classification ◽  
Detailed Classification ◽  
Similarities And Differences

A systematic classification generally reflects accurately the state of knowledge of a group. As information concerning the group increases, both similarities and differences become more apparent. New characters then may be utilized to develop a more complex classification, that better serves to indicate presumed relationships. Assuming that organisms have evolved through time, the more detailed classification may also prove more valuable to the biostratigrapher.

Factors Associated With Concurrent Cigarette and Electronic Cigarette Use in U.S. Adults

2015 ◽  
Author(s):  
K. Pulvers ◽  
R.B. Hayes ◽  
T.S. Scheuermann ◽  
D.R. Romero ◽  
A.S. Emami ◽  
...  
Keyword(s):  
Electronic Cigarette ◽  
Cigarette Use ◽  
Factors Associated

scholarly journals Flavor and product messaging are the two most important drivers of electronic cigarette selection in a choice-based task

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Allison N. Baker ◽  
Stephen J. Wilson ◽  
John E. Hayes
Keyword(s):  
Young Adults ◽  
Conjoint Analysis ◽  
Policy Making ◽  
Evidence Base ◽  
Electronic Cigarette ◽  
Food Craving ◽  
Cigarette Use ◽  
Men And Women ◽  
Nicotine Level ◽  
Utility Scores

AbstractElectronic cigarette use—vaping—is increasingly popular. Various product factors may influence an individual’s choice of e-cigarette. To provide an evidence base for e-cigarette regulation, a better understanding of the role different product attributes play in product preferences is needed. Here, we used conjoint analysis to quantify different factors that influence e-cigarettes choices, including flavors, nicotine level, customizability, or use of e-cigarettes to manage appetite/food craving. Young adults completed a set of choice-based conjoint tasks online. Choice Based Conjoint analysis (CBC) was used to determine utility scores for each attribute. Young adults (n = 587) who vaped at least once per week were included in analyses; gender differences were explored. Flavor was the most important attribute (48.1%), followed by product messaging (21.0%) and nicotine level (15.3%). Within flavor, confectionery and fruit flavors had the highest utility scores, while classic menthol and tobacco flavors had the lowest. Men and women differed in flavors, nicotine levels, and product messaging that appealed most. Among young adults who vape weekly, flavor is the most important factor in e-cigarette preferences. Gender also factors into e-cigarette preferences, especially for preferred nicotine level. Understanding why individuals choose particular e-cigarette products will help inform public health efforts and policy making.

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