PT  - JOURNAL ARTICLE
AU  - Nicole McKenzie
AU  - Tavis Glassman
AU  - Joseph Dake
AU  - Ling Na
AU  - S. Maggie Maloney
TI  - Using the Integrated Behavioral Model to Explain and Predict Cannabis Vaping Among College Students
DP  - 2021 Oct 01
TA  - Respiratory Care
PG  - 3611331
VI  - 66
IP  - Suppl 10
4099  - http://rc.rcjournal.com/content/66/Suppl_10/3611331.short
4100  - http://rc.rcjournal.com/content/66/Suppl_10/3611331.full
AB  - Background: As cannabis laws have become more permissive, use of electronic nicotine delivery systems (ENDS) to vaporize cannabis has also become more prevalent, particularly among college students. With this increase in cannabis vaporizer use, detrimental health effects are emerging, including a new medical diagnosis for vaping-induced respiratory disease, referred to as Electronic cigarette or Vaping-Associated Lung Injury (EVALI). The Integrated Behavior Model is based on the premise that fundamental theoretical constructs explain individual health behavior. Fishbein and Ajzen (2010) posit that the function of attitudes, norms, and personal agency (control beliefs and self-efficacy) are the primary determinants of intention to perform a behavior. Specific research regarding cannabis vaping among college students examining personal agency, or the Integrated Behavioral Model in its entirety, is lacking; the aim of this scientific inquiry is to address this gap in the literature. Methods: Researchers used a cross-sectional research design to collect 423 online survey responses. The survey instrument consisted of 35 items assessing the IBM constructs: Experiential Attitude, Instrumental Attitude, Injunctive Norms, Descriptive Norms, Perceived Control, Self-Efficacy, and Behavioral Intention. Additionally, participants reported past use of cannabis and nicotine, as well as any cannabis vaping behavior changes related to COVID-19. The confirmatory factor analysis indicated good fit of the data to the measurement model. The structural equation model was used to assess the effects of IBM predictors on Behavioral Intention. Results: The IBM predictors accounted for 54.2% of the variance in Behavioral Intention. The strongest path coefficients on Behavioral Intention were Perceived Norm and Experiential Attitude. Additionally, there was a weak positive correlation between vaping cannabis and smoking cannabis within the sample. Conclusions: The results from this study can be used to design interventions to decrease cannabis vaping use among college students. More specifically, social norm interventions and addressing other misconceptions about vaping cannabis, appears to be a promising theoretical approach to help ameliorate this unique public health challenge. Additionally, the low correlation between combustible cannabis use and vaping it indicates the motives for using the different delivery devices vary, suggesting the need to tailor education efforts.