As e-cigarette brand JUUL continues to climb in popularity among users of all ages, University of Pittsburgh School of Medicine researchers took a unique approach to analyzing its impact by using Twitter to investigate any mention of nicotine effects, symptoms of dependence and withdrawal in regards to JUUL use.
The study revealed that 1 out of every 5 tweets mentioning JUUL identified for the analysis also referenced addiction-related themes.
The full results are published in the journal Drug and Alcohol Dependence.
“Many news stories have reported that people are using JUUL and experiencing what sound like acute effects of nicotine exposure and symptoms of dependence,” said lead author Jaime Sidani, Ph.D., assistant director of Pitt’s Center for Research on Media, Technology, and Health. “We turned to Twitter to gather real-time data on what people are sharing about their JUUL use.”
To complete the study, Sidani and her team of researchers created search filters within Twitter’s Filtered Streams interface to collect data on all available tweets matching the terms “juul,” “juuls” and “juuling,” as well as their hashtag equivalents between April 11, 2018, and June 16, 2018.
After additional narrowing of search results by implementing specific keywords, excluding commercial content and ensuring the tweets were in first-person context, a final data set of 1,986 tweets remained for final analysis by two independent coders.
Of these tweets, 21.1% were coded as being related to dependence (335 tweets), nicotine effects (189 tweets), quitting JUUL or withdrawal, or both (42 tweets).
Sidani said these findings aren’t surprising when considering the powerful dose of nicotine that JUUL provides.
In addition, JUUL uses a nicotine salt formula, which is designed to increase the rate of absorption and create a more palatable vapor, making JUUL a more appealing option compared to other modes of nicotine delivery.
“We found many self-reported symptoms of nicotine dependence,” said co-author A. Everette James, J.D., director of the Pitt Health Policy Institute and interim dean of Pitt’s Graduate School of Public Health. “Because of the lack of public knowledge about the dependence risks, it makes sense that many people seemed surprised about experiencing symptoms of withdrawal when they could not use their device.”
Sidani and her team hope to continue studying the social conversation surrounding JUUL and its addictive properties, as well as promote the use of Twitter and other social media platforms as analysis tools for related research topics.
“By leveraging real-time data from the Twitter platform, we can research timely health trends on an unprecedented scale,” said co-author Jason Colditz, M.Ed., program coordinator at Pitt’s Center for Research on Media, Technology, and Health. “In this study, we detected candid narratives related to JUUL dependence, a relatively recent public health trend that deserves further investigation.”
JUUL e-cigarettes are popular among youth. However, it is unknown whether adolescents understand that 5% JUUL pods contain a high nicotine concentration or consider JUULs to be e-cigarettes.
3170 students from 4 Connecticut high schools completed a school-based survey (May–October 2018).
Students reported on lifetime and past-month JUUL use and perceived JUUL nicotine strength (low/medium/high/don’t know) when no information about nicotine concentration was provided and, subsequently, when informed JUULs contain 5% nicotine. Students reported whether they believe JUULs are e-cigarettes (no/yes/don’t know).
Students were never JUUL users (56.6%), ever users (13.2%), and past-month users (30.2%). When no information was provided, students reported that JUULs contain low (10.5%), medium (26.9%), or high nicotine levels (31.1%); 31.4% did not know. When informed JUULs contain 5% nicotine, students were more likely to believe JUUL’s nicotine strength was low (29.5%) or medium (29.3%) than high (21.3%) and less likely to report not knowing (19.9%). 39% of students believed JUULs are not e-cigarettes or did not know.
Most students were unaware of JUUL’s high nicotine concentration, with more believing that JUULs contain low or medium nicotine concentrations when informed JUULs contain 5% nicotine. Thus, youth may misinterpret the nicotine concentration printed on JUUL pod packaging, raising concerns about inadvertent exposure to high nicotine levels and dependence risk. Further, 39% of adolescents believed JUULs are not e-cigarettes or were unsure. Regulatory efforts are needed to establish understandable nicotine concentration labels, require products to be labeled accordingly, and clarify what products constitute e-cigarettes.
Electronic cigarettes (e-cigarettes) have soared in popularity to such an extent that the Surgeon General has declared their use an “epidemic”. Per the Centers for Disease Control and Prevention (CDC) report of 2018 National Youth Tobacco Survey data, one in five high school students is a current e-cigarette user . One may associate this precipitous rise in popularity with the emergence of the fourth-generation e-cigarette products, pods. We previously reported that Juul and similar pod devices contain high concentrations of nicotine salts, and that urinary cotinine (primary nicotine metabolite) in adolescent pod users was higher than cotinine levels previously reported among adolescent smokers of conventional cigarettes . We also reported that adolescent e-cigarette daily users were more likely to report using pods . These findings raised important questions about the potential for early onset of nicotine dependence among adolescents who use pods. In this secondary analysis of a previously described cohort of adolescents , we compare use patterns of past-week pod vs. non-pod e-cigarette users in order to assess potential symptoms of nicotine dependence, and to correlate these outcomes with subjects’ measured urinary cotinine.Go to:
Materials and Methods
Between April 2017 and April 2018, 517 adolescents, ages 12–21, were recruited from three Stony Brook Children’s outpatient offices. All participants completed an anonymous survey regarding e-cigarette use and provided a urine sample. Urine from all e-cigarette users and a random sample of non-e-cigarette using controls was sent to Roswell Park Comprehensive Cancer Center for analysis of cotinine, the main metabolite of nicotine, and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), found only in users of combusted tobacco cigarettes. Urine samples with overly dilute (<10 mg/dL) or concentrated (>390 mg/dL) creatinine were excluded from analysis. The full analysis protocol has been described previously .
In this secondary analysis, past-week pod users (n = 21) were compared with past-week e-cigarette users who did not use pods (“non-pod users”) (n = 27). Subjects who used combusted tobacco were excluded. Urinary cotinine levels were evaluated and compared between the two groups (pod vs. non-pod e-cigarette users) in 42 participants who answered questions regarding nicotine dependence. Statistical analysis was conducted using Statistical Package for the Social Sciences (Version 25, IBM Corporation, Armonk, NY 10504, USA). Descriptive statistics were used to describe self-reported use patterns. The chi-square test of independence/analysis of variance were used to analyze relationships between self-reported use and urinary biomarkers. All tests of significance were two-tailed and significant at p < 0.05. This study was approved by the Stony Brook University Institutional Review Board (CORIHS#:2016-3912-F).
Of the 517 participants in the full cohort, 14.3% (n = 74) had used e-cigarettes in the past week and 2.9% (n = 18) were past-week tobacco smokers. Pod users were younger than non-pod users: 60.0% (pod users) vs. 40.0% (non-pod users) were 12–14 years; 56.0% vs. 44.0%, 15–17 years; 22.2% vs. 77.8% were ages 18–21 (p = 0.06). Overall, the most common reasons for trying e-cigarettes were curiosity (67.3%), friends using them (57.1%), and flavoring (24.5%). There was no significant difference between the percent in each group that had ever tried a cigarette (45% of pod users vs. 33% of non-pod e-cigarette users; p = 0.324). There were no significant differences between the pod and non-pod groups with respect to gender, race, or ethnicity.
Analysis of all survey results revealed that two-thirds (66.7%) of frequent (“use a lot”) past-week e-cigarette users used pods. Of “sometimes” users, 45.5% were pod users and 54.5% non-pod users. Of respondents who stated they had tried but no longer used e-cigarettes (so-called “experimenters”), 23.5% were pod and 68.5% non-pod users. More pod users categorized themselves as daily users compared to non-pod users (63.0% vs. 11.0%; p = 0.001); more pod than non-pod users reported having used an e-cigarette within the past day (76.2% vs. 29.6%, p = 0.001).
We included five questions regarding nicotine dependence, for which any positive answer received a score of one, resulting in a total maximum score of 5 (Table 1). Of 48 past-week e-cigarette users with urine samples analyzed, 43.8% (n = 21) were pod users and 56.2% (n = 27) were non-pod e-cigarette users. Of these, 42 respondents answered questions about dependence, and 28.6% (n = 12) had at least one positive response. A higher percentage of these were pod (vs. non-pod) users (21.4%, n = 9 vs. 7.1%, n = 3; p = 0.04). Each of the three non-pod users who responded positively answered only one question affirmatively, giving each a total score of one. Of the pod users, five answered one question affirmatively, two answered two questions affirmatively, and one each answered four and five questions affirmatively. The cotinine concentration (mean ± SD) in urine samples from 12 positive respondents (nine pod users and three non-pod users) was higher than that of the 30 negative respondents’ cotinine: 675.40 ± 828.12 vs. 96.12 ± 298.31 ng/mL; p = 0.002. Six pod users vs. no non-pod users stated that they needed to vape upon awakening (p = 0.006); their cotinine levels were significantly higher than those of other respondents: 921.2 ± 960.4 vs. 148.2 ± 385.1 ng/mL (p = 0.001).
Dependence questions ** among 48 patients aged 12–21 who reported use of e-cigarettes in past week.
|Statement||Total (%) Rated Agreement with Statement|
(n = 42)
|Pod Users (%) Rated Agreement with Statement|
(n = 20)
|Non-Pod Users (%) Rated Agreement with Statement|
(n = 22)
|If I go too long without vaping, the desire to vape interrupts my thinking||3 (7)||3(15)||0 (0)||0.060|
|If I go too long without vaping, the desire to vape is so great that I need to vape again||2 (5)||2 (10)||0 (0)||0.130|
|If I go too long without vaping, I get angry or irritable||5 (12)||4 (20)||1 (5)||0.122|
|If I go too long without vaping, I get stressed||6 (14)||4 (20)||2 (9)||0.320|
|I need to vape when I awaken in the morning||6 (14)||6 (29)||0 (0)||0.006|
** Not all respondents answered all questions.
More information: Jaime E. Sidani et al, I wake up and hit the JUUL: Analyzing Twitter for JUUL Nicotine Effects and Dependence, Drug and Alcohol Dependence (2019). DOI: 10.1016/j.drugalcdep.2019.06.005
Journal information: Drug and Alcohol Dependence
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