Using the Theory of Planned Behavior to Anticipate DIY E-juice Mixing among Young Adult International E-cigarette Users

Document Type : Original Article

Authors

1 School of Communication, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA

2 Department of Communication, University of Kentucky, 308 Lucille Little Library, Lexington, KY 40506, USA

3 Department of Biology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA

10.34172/ahj.2023.1385

Abstract

Background: Trends in young adult use of electronic nicotine delivery systems (ENDS) and experimentation with do-it-yourself (DIY) 
e-juice mixing are growing around the world. Theoretical frameworks for examining secondary behaviors (i.e., mixing) embedded 
within a primary behavior (i.e., vaping) are limited, leading to challenges in scholarly understanding of behavioral performance. This 
study explored the theoretically driven factors surrounding ENDS users’ decision to mix DIY e-juice through a multiple behavior test 
of the theory of planned behavior (TPB).
Methods: An international sample of young adult participants aged 18-19 (n=203) was recruited from Prolific for an online crosssectional survey. Path modeling tested four theoretically driven models to explore behavioral performance of mixing.

Findings: The data supported TPB expectations and revealed new paths for secondary behavior. Primary perceptions of attitudes, 
norms, and intention were predictive of the same secondary perceptions. In addition, for both primary and secondary behaviors, 
perceived norms were a function of perceived attitudes. For the secondary behavior, normative influence was experienced indirectly 
through perceived attitudes.

Conclusion: DIY e-juice mixing is a product of perceived attitudes and behavioral control surrounding mixing as well as perceived 
attitudes, norms, and intention surrounding general ENDS use. While unregulated DIY experimentation increases among youth, 
these findings provide a lens for public health efforts seeking to reach and reduce use. Understanding DIY e-juice behaviors is
essential to anticipate stockpiling behaviors and negative outcomes from amateur experimentation.

Highlights

Rachael A.Record: (Google Scholar) (PubMed)

Maxwell Groznik: (Google Scholar) (PubMed)

Mark A. Sussman: (Google Scholar) (PubMed)

Keywords