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Published on: August 25, 2018
Does a 10-puff bout reflect natural puffing patterns for electronic nicotine delivery systems?
Melissa D Blank1, Nicholas Felicione2, Alison Breland3
1Department of Psychology, West Virginia University, Morgantown, WV, 26506, USA.
Electronic nicotine delivery system (ENDS) users predominantly take single puffs or small clusters, not the 10-puff sessions common in lab studies. This reveals naturalistic ENDS use patterns differ significantly from standardized research methods.
Area of Science:
- Public Health
- Tobacco Control
- Behavioral Science
Background:
- Electronic nicotine delivery systems (ENDS) are widely used, but user puffing behavior is not well understood.
- Standardized 10-puff procedures in laboratory settings may not accurately reflect real-world ENDS use patterns.
Purpose of the Study:
- To investigate how users group puffs into clusters during electronic nicotine delivery system (ENDS) use.
- To compare naturalistic puffing patterns with standardized laboratory procedures.
Main Methods:
- Analyzed puffing data from 8 studies using a consistent definition of puff clusters (puffs separated by <60 seconds).
- Categorized clusters into single, short (2-5 puffs), medium (6-10 puffs), and long (>10 puffs).
- Examined cluster frequency, puff count per cluster, and percentage of total puffs, exploring variations based on pre-session abstinence and puffing duration.
Main Results:
- Single and small puff clusters were the most frequent types across most studies.
- Small clusters accounted for the largest percentage of total puffs (37.12%), followed by single puffs (28.55%).
- Puff cluster patterns remained consistent regardless of pre-session abstinence or puffing bout length.
Conclusions:
- The majority of ENDS puffs occur as single or small clusters, totaling 67.0% of all puffs.
- The standard 10-puff method used in laboratory research does not accurately represent naturalistic ENDS puffing behavior.
- Findings highlight a discrepancy between laboratory research conditions and actual user behavior.
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