title: A Method for Classifying User-Reported Electronic Cigarette Liquid Flavors.
abstract: BACKGROUND
  Along with the growth in popularity of electronic cigarette devices (e-cigs), the variety of e-cig liquids (e-liquid) available to users has also grown. Although some studies have published data about the use of flavored e-liquid, there is no standardized way to group flavors, making it difficult to interpret the data and replicate results across studies. The current study describes a method to classify user-reported e-liquid flavors and presents the resulting proportion of users in each flavor group in a large online survey of e-cig users.
  
  
  METHODS
  Three thousand seven hundred sixteen participants completed an online survey about their e-cig use and responded to the following open-ended question regarding their use of e-liquid, "What is your favorite flavor and what brand of flavored liquid do you prefer?" Researchers used a 3 step method to determine the flavor attributes present in the e-liquids reported using an online search engine. Once all flavor attributes were identified, researchers used the constant comparative method to group the flavor attributes and delineate how to classify flavors with mixed components (eg, cinnamon Red Hots as a candy not a spice).
  
  
  RESULTS
  The resulting classification scheme and proportions of e-liquids in each category were as follows: Tobacco (23.7%), Menthol/mint (14.8%), Fruit (20.3%), Dessert/sweets (20.7%), Alcohol (2.8%), Nuts/spices (2.0%), Candy (2.1%), Coffee/tea (4.3%), Beverage (3.1%), Unflavored (0.4%), and Don't Know/Other (5.8%).
  
  
  CONCLUSIONS
  To better understand the use of flavored e-liquids, standardized methods to classify the flavors could facilitate data interpretation and comparison across studies. This study proposes a method for classifying the characterizing flavors in e-liquids used most commonly by experienced e-cig users.
  
  
  CONCLUSIONS
  Current studies on the use of flavored e-liquid have used unclear methods to collect and report information on the use of flavors. This study adds a proposed method for classifying the flavors in the e-liquids used most commonly by experienced e-cig users. With a clear and explicit method for classifying self-reported flavors, future study results may be more easily compared.
authors.affiliation: Department of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.
authors.forename: Jessica M
authors.initials: JM
authors.lastname: Yingst
authors.affiliation: Department of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.
authors.forename: Susan
authors.initials: S
authors.lastname: Veldheer
authors.affiliation: Department of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.
authors.forename: Erin
authors.initials: E
authors.lastname: Hammett
authors.affiliation: Department of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.
authors.forename: Shari
authors.initials: S
authors.lastname: Hrabovsky
authors.affiliation: Department of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Foulds
mesh_terms: D000328:Adult; D066300:Electronic Nicotine Delivery Systems; D005260:Female; D005421:Flavoring Agents / Q000032:analysis* / Q000145:classification; D006801:Humans; D020407:Internet; D008297:Male; D011795:Surveys and Questionnaires
chemical_list: D005421:Flavoring Agents