Kale, D;
Pickering, A;
Cooper, A;
(2020)
Examining the Psychometric Properties of the CEAC (Comparing e-Cigarette and Cigarette) Questionnaire and Its Usefulness as a Predictor of e-Cigarette Use.
Substance Use & Misuse
, 55
(1)
pp. 147-155.
10.1080/10826084.2019.1657897.
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Abstract
Background: Electronic cigarette (e-cigarette) use continues to rise, while there is conflicting evidence about the health effects of its use. As such, research is needed to better determine risks factors for e-cigarette use. Accumulating evidence suggests that attitudes toward e-cigarette use could be a potential risk factor for e-cigarette use. Objectives: This study sought to examine the psychometric properties of the Comparing E-cigarette And Cigarette questionnaire (CEAC), and to replicate a structural model of the relationship between impulsive-related personality traits and e-cigarette use mediated by positive attitudes toward e-cigarettes. Methods: Participants were 525 adults (mean age = 33.42, SD = 11.27) who completed the CEAC and UPPS-P (trait impulsivity) questionnaires online. Results: Confirmatory factor analysis of the CEAC replicated the a priori factor structure of the questionnaire reasonably well (χ2(df = 32) =172.85, CFI = 0.94, TLI = 0.91, RMSEA = 0.09 (0.08–0.11, 90% Confidence Interval, SRMR = 0.06). Structural path analysis showed that deficits in conscientiousness was significantly negatively related to e-cigarette attitudes (β = –0.20, p = .01), while urgency (β = 0.19, p = .018) showed a significant positive relationship to e-cigarette attitudes. E-cigarette users showed significantly more positive attitudes toward e-cigarettes than nonusers (β = 0.59, p < .001). No significant direct effects were found between impulsivity-related traits and e-cigarette use. Conclusions: The present study suggests that impulsivity-related traits and attitudes toward e-cigarettes are likely to be important risk factors for e-cigarette use. Future prospective and experimental studies should test if the causal model described in this study predicts risk for e-cigarette use, and whether this model could therefore be used to guide strategies for reducing risk for e-cigarette use.
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