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An Examination of Objective and Self-Report Measures of Ad libitum Electronic Cigarette Use: Identifying Patterns of Puffing Behavior and Evaluating Self-Report Items.

Ashley N DowdLovina JohnJennifer M BettsPrajakta BelsareEdward SazonovStephen T Tiffany
Published in: Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco (2023)
This is the first study to identify and distinguish three empirically based e-cigarette use-groups. These use-groups, as well as the specific topography data discussed, can provide a foundation for future research assessing the impact of use across different use-types. Furthermore, as participants tended to over-report use and assessments did not capture use accurately, this study can serve as a foundation for future work developing more appropriate assessments for use in research studies as well as clinical practice.
Keyphrases
  • clinical practice
  • machine learning
  • big data
  • electronic health record
  • artificial intelligence
  • deep learning