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A Method for Classifying User-Reported Electronic Cigarette Liquid Flavors.

Jessica M Yingst1, Susan Veldheer1, Erin Hammett1

  • 1Department of Public Health Sciences, Penn State University College of Medicine, Hershey, PA.

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PubMed
Summary
This summary is machine-generated.

A new classification method for electronic cigarette (e-cig) liquid flavors was developed. This system categorizes popular e-liquid flavors, aiding future research on e-cig use.

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Area of Science:

  • Public Health
  • Tobacco Control
  • Consumer Product Research

Background:

  • The popularity of electronic cigarettes (e-cigs) has led to a wide variety of e-cigarette liquids (e-liquids).
  • Existing research on flavored e-liquids lacks standardized flavor categorization, hindering data interpretation and replication.
  • This study addresses the need for a consistent method to classify user-reported e-liquid flavors.

Purpose of the Study:

  • To develop and present a novel classification system for user-reported e-liquid flavors.
  • To determine the proportional distribution of users across different e-liquid flavor categories.

Main Methods:

  • A large online survey of 3,716 electronic cigarette users was conducted.
  • Participants reported their preferred e-liquid flavors and brands in an open-ended question.
  • A three-step method involving online searches and constant comparative analysis was used to identify and group flavor attributes.

Main Results:

  • The developed classification scheme identified the following flavor proportions: 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%).
  • This categorization provides a quantitative overview of popular e-liquid flavor preferences among surveyed users.

Conclusions:

  • Standardized classification of e-liquid flavors is crucial for improving data interpretation and comparability in future research.
  • The proposed classification method offers a clear and explicit approach for categorizing characterizing flavors in e-liquids.
  • This study provides a foundation for more consistent and reliable research into flavored e-cigarette use.