Browsing by Subject "electronic cigarettes"

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    Assessing the Depiction of Electronic Cigarettes in YouTube Videos
    (Office of the Vice Chancellor for Research, 2014-04-11) Hurwich, R.; Romito, Laura M.
    Objective: Use of electronic cigarettes is an emerging phenomenon with unknown health implications. YouTube videos of e-cigarettes are abundant, easily accessible, and possess the potential to promote e-cigarette use through the increased visibility of user-generated content and novel marketing strategies. As there are no published studies examining the content of e-cigarette videos, this study aimed to assess the depiction of e-cigarettes in terms of content and viewing qualities. Methods: Two calibrated reviewers conducted 4 searches for e-cigarette English language YouTube videos between August 2, 2013 and November 26, 2013. Based on a Google Insights analysis, the sample was selected from the top 20 search results for the terms “electronic cigarette,” and “e-cig”. Two searches were performed for each term using the filters “Relevance” and “View Count”. The initial sample included a total of 80 short-length videos from which duplicates were removed, leaving a final sample of 63 unique videos. Data collected included: title; uploader alias; length; number of views, “likes”, “dislikes”, comments and actor demographics. Videos were rated independently by the two reviewers for content theme and connotation. Inter-rater reliability was good (k=.70). Reviewer ratings were compared; consensus was reached on any discrepancies. Data was coded and recorded into an electronic database for statistical analysis. Results: The sample of assessed videos (N=63), generated the following means: video length, 135 seconds; views, 199,311; “likes”, 21.5; “dislikes”, 98.2; and posted comments, 244. Of the actors shown, 49.2% were male, 61.9% were Caucasian, and 33.3%, the largest segment, were coded as young (i.e. < 40 years). The most commonly mentioned brand was Blu. Video content connotation was coded as follows: positive (76.1%); neutral (17.4%); and negative (6.3%). Videos were categorized into one of the following seven content themes: Advertisement (33%); Instructional/how-to (17.4%); news clip/story (19.0%); product review (12.7%); entertainment (11.1%); public health/educational (3.1%); and personal testimonial (3.1%). Conclusions: YouTube videos of electronic cigarettes primarily feature young, male, Caucasian actors and depict e-cigarettes in a positive manner. Most videos were non-traditional advertisements.
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    Beliefs About the Direct Comparison of E-Cigarettes and Cigarettes
    (Taylor & Francis, 2017) Hershberger, Alexandra R.; Karyadi, Kenny A.; VanderVeen, J. Davis; Cyders, Melissa A.; Psychology, School of Science
    Background: Recent data suggests that positive beliefs about electronic cigarettes (e-cigs) use can lead to later e-cig use. Considering that many advertisements claim that e-cigs are superior to cigarettes, individuals' likelihood to view e-cigs more favorably than cigarettes can also influence subsequent e-cig use; however, no studies have directly assessed such a comparison. Objectives: The present study created and validated the Comparing E-Cigarettes and Cigarettes questionnaire (CEAC), which asks individuals to directly compare e-cigs and cigarettes on a number of dimensions, in two independent samples. Methods: In sample 1 (451 undergraduates; mean age = 20.35, SD = 5.44, 72.4% female, 73.4% Caucasian) we explored the factor structure of the CEAC and in sample 2 (699 community adults collected via Amazon's Mechanical Turk; mean age = 34.04, SD = 10.9, 47.7% female, 83.3% Caucasian) we replicated the factor structure. Results: Exploratory factor analysis suggested a three-factor structure: General Benefits (α = 0.80), General Effects (α = 0.86), and Health Benefits (α = 0.88), which was replicated via confirmatory factor analysis, χ2 = 4.36; RMSEA = 0.07, 90% CI = 0.06–0.08; TLI = 0.99; CFI = 0.99, and was relatively invariant across product use and gender. Individuals reported viewing e-cigs as safer and more beneficial than cigarettes and these beliefs were higher in e-cig users. Conclusions: Future work should establish how these comparative beliefs are influenced by e-cig use and/or influence subsequent transition to and increases in e-cig use. Although e-cigs are likely less harmful than cigarettes, and thus these comparative beliefs represent that state of nature, e-cigs are not completely without risk.