Dataset Information

"Technophilia": A new risk factor for electronic cigarette use among early adolescents?

ABSTRACT: PURPOSE:Develop and validate a scale that measures Technophilia (positive orientation toward new technology) and use it to address orientation toward new technologies to explain e-cigarette trial and adoption, especially in relatively low risk adolescents. METHODS:Survey data were obtained from students of the three largest cities in Mexico (n?=?8123). We developed eight questions involving access, use and pleasure from different electronic media to measure technophilia. Exploratory factor analysis (EFA) was conducted. Linear GEE models were used when regressing technophilia on covariates. When regressing e-cigarette and conventional cigarette trial and use, logistic GEE models were used. Finally, we used multinomial logistic regression to evaluate the associations between technophilia and e-cigarettes as the first tobacco product. RESULTS:Technophilia were correlated with theoretically-related variables. Unadjusted and adjusted models regressing e-cigarette trial and use indicated that students in the highest quartile for technophilia were more likely to have tried e-cigarettes compared with the lowest quartile (AORQ4 vs Q1?=?1.36, 95% CI 1.14-1.62). Technophilia was not independently associated with current e-cigarette use in adjusted models. Students with higher technophilia were more likely to have first tried e-cigarettes in both crude and adjusted models (AORQ4vQ1?=?1.66, 95% CI 1.20-2.31; AORQ3vQ1?=?1.43, 95% CI 1.02-2.01). Technophilia did not have a statistically significant, independent association with first use of other tobacco products. CONCLUSION:This study suggests that technophilia is associated with trial of e-cigarettes among youth. The measure we developed appears useful for understanding why some youth are open to trying novel, technologically oriented ways to consume nicotine.

SUBMITTER: Barrientos-Gutierrez I

PROVIDER: S-EPMC6358480 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

"Technophilia": A new risk factor for electronic cigarette use among early adolescents?

Barrientos-Gutierrez Inti I Lozano Paula P Arillo-Santillan Edna E Morello Paola P Mejia Raul R Thrasher James F JF

Addictive behaviors 20180906

<h4>Purpose</h4>Develop and validate a scale that measures Technophilia (positive orientation toward new technology) and use it to address orientation toward new technologies to explain e-cigarette trial and adoption, especially in relatively low risk adolescents.<h4>Methods</h4>Survey data were obtained from students of the three largest cities in Mexico (n = 8123). We developed eight questions involving access, use and pleasure from different electronic media to measure technophilia. Explorato ...[more]

PMID: 30224154

Similar Datasets

Project description:Importance:Use of electronic cigarettes (e-cigarettes) is high among adolescents, but the extent to which the JUUL e-cigarette brand accounts for the high prevalence has not been explored using population-based surveys. Objective:To examine e-cigarette and JUUL use among adolescents in New Jersey. Design, Setting, and Participants:Survey study using data from the 2018 New Jersey Youth Tobacco Survey, a cross-sectional statewide representative survey of tobacco use. The survey was school based and sampled New Jersey students in grades 9 to 12. Exposures:Use of tobacco products; JUUL as first tobacco product tried; exposure to JUUL at school; number of friends perceived as JUUL users; liking or following a tobacco brand on social media; and buying or receiving tobacco-branded merchandise. Main Outcomes and Measures:Prevalence ratio (PR) for current and frequent e-cigarette use, inclusive of JUUL. Results:In this sample of 4183 adolescents, respondents were 49.6% female and 49.6% non-Hispanic white. Students were evenly distributed across grades 9 through 12. Overall, the estimate for current use of e-cigarettes inclusive of JUUL was higher (24.2%; 95% CI, 22.5%-25.9%) compared with current use assessed by use of e-cigarettes only (17.8%; 95% CI, 16.4%-19.4%) or JUUL use only (21.3%; 95% CI, 19.7%-23.0%). Divergence in e-cigarette use estimates was higher for certain subgroups, including female respondents and non-Hispanic black respondents. Also, 88.8% (95% CI, 86.6%-91.1%) of current e-cigarette users reported JUUL as a brand they used. Hispanic students (PR, 0.78; 95% CI, 0.69-0.89) and non-Hispanic students of other races (PR, 0.64; 95% CI, 0.51-0.81) were significantly less likely than non-Hispanic white students to be current e-cigarette users, and students in 12th grade were more likely than those in 9th grade to be current users (PR, 1.29; 95% CI, 1.11-1.48). Current e-cigarette use was positively associated with current use of other tobacco products (PR, 2.57; 95% CI, 2.24-2.95), endorsing a tobacco brand on social media (PR, 1.43; 95% CI, 1.19-1.72), having tobacco-branded merchandise (PR, 1.70; 95% CI, 1.46-1.97), having close friends who used JUUL (PR, 3.81; 95% CI, 3.17-4.58), and seeing JUUL used on school grounds (PR, 1.43; 95% CI, 1.24-1.65). Estimates of prevalence were greater when modeling frequent use. Conclusions and Relevance:This study found that prevalence of current and frequent e-cigarette use among adolescents was higher when inclusive of JUUL use, and JUUL was by far the most common e-cigarette brand used, providing support for inclusion of brand-specific questions when assessing e-cigarette use. The results also identify characteristics of adolescents who may be more likely to use e-cigarettes.

Project description:ImportanceMany studies have reported a positive association of youth electronic cigarette (e-cigarette) use with subsequent cigarette smoking initiation, but it remains unclear whether e-cigarette use is associated with continued cigarette smoking after initiation.ObjectiveTo assess the association of youth baseline e-cigarette use with their continued cigarette smoking 2 years after initiation.Design, setting, and participantsThe Population Assessment of Tobacco and Health (PATH) Study is a national longitudinal cohort study. This sample consisted of youth who participated in waves 3, 4, and 5 of the study (wave 3 was from October 2015 to October 2016, wave 4 was from December 2016 to January 2018, and wave 5 was from December 2018 to November 2019) and had never used cigarettes (cigarette-naive) by wave 3. The current analysis used multivariable logistic regressions in August 2022 to assess the association between e-cigarette use among cigarette-naive adolescents aged 12 to 17 years in 2015 and 2016 and subsequent continued cigarette smoking. PATH uses audio computer-assisted self-interviewing and computer-assisted personal interviewing to collect data.ExposuresEver and current (past 30-day) use of e-cigarettes in wave 3.Main outcomes and measuresContinued cigarette smoking in wave 5 after initiating smoking in wave 4.ResultsThe current sample included 8671 adolescents who were cigarette naive in wave 3 and also participated in waves 4 and 5; 4823 of the participants (55.4%) were aged 12 to 14 years, 4454 (51.1%) were male, and 3763 (51.0%) were non-Hispanic White. Overall, regardless of e-cigarette use, few adolescents (362 adolescents [4.1%]) initiated cigarette smoking at wave 4, and even fewer (218 participants [2.5%]) continued smoking at wave 5. Controlling for multiple covariates, the adjusted odds ratio of baseline ever e-cigarette use, compared with never e-cigarette use, was 1.81 (95% CI, 1.03 to 3.18) for continued smoking measured as past 30-day smoking at wave 5. However, the adjusted risk difference (aRD) was small and not significant. The aRD was 0.88 percentage point (95% CI, -0.13 to 1.89 percentage points) for continued smoking, with the absolute risk being 1.19% (95% CI, 0.79% to 1.59%) for never e-cigarette users and 2.07% (95% CI, 1.01% to 3.13%) for ever e-cigarette users. Similar results were found using an alternative measure of continued smoking (lifetime ≥100 cigarettes and current smoking at wave 5) and using baseline current e-cigarette use as the exposure measure.Conclusions and relevanceIn this cohort study, absolute and relative measures of risks yielded findings suggesting very different interpretations of the association. Although there were statistically significant odds ratios of continued smoking comparing baseline e-cigarette users with nonusers, the minor risk differences between them, along with the small absolute risks, suggest that few adolescents are likely to continue smoking after initiation regardless of baseline e-cigarette use.

Project description:ImportanceDespite increasing use of cigarettes and electronic cigarettes (e-cigarettes) and related health effects among youth, few studies have reported their effects on eyes.ObjectiveTo examine the frequency and severity of ocular symptoms (ocular discomfort, pain, burning, itching, redness, dryness, glare, blurriness, strain, and headaches) in young e-cigarette and cigarette users.Design, setting, and participantsIn an observational cross-sectional study, a survey conducted in May 6 to 14, 2020, asked participants about use (ever, past 30 days, and past 7 days) of e-cigarettes and cigarettes. The participants included US individuals aged 13 to 24 years.Main outcomes and measuresAssociations between vision-related outcomes (general vision, severity/frequency of ocular symptoms) and tobacco use were analyzed using weighted multivariable logistic regressions, adjusting for sociodemographic factors, contact lens use, and other combustible use.ResultsThere were 2168 never users, 2183 ever users, 1092 past 30-day users, and 919 past 7-day users of e-cigarettes; 55.9% of e-cigarette ever users also used cigarettes (dual users). Of the 4351 respondents, 63.8% identified as female, and mean (SD) age was 19.1 (2.9) years. Between 1.1% and 3.9% of ever dual users reported severe to very severe ocular symptoms; between 0.9% and 4.3% reported daily symptoms, which was higher than the proportion of symptoms in e-cigarette- or cigarette-only users. Past 7-day dual users had more severe itching (adjusted odds ratio [AOR], 2.37; 95% CI, 1.36-4.13; P = .002), redness (AOR, 2.58; 95% CI, 1.50-4.46; P = .001), dryness (AOR, 2.89; 95% CI, 1.64-5.08; P < .001), glare (AOR, 2.56; 95% CI, 1.50-4.35; P = .001), blurriness (AOR, 2.47; 95% CI, 1.36-4.50; P = .003), headaches (AOR, 2.31; 95% CI, 1.34-4.00; P = .003); and more frequent pain (AOR, 3.45; 95% CI, 2.09-5.68; P < .001), burning (AOR, 3.08; 95% CI, 1.86-5.09; P < .001), and redness (AOR, 2.72; 95% CI, 1.69-4.36; P < .001) than all other participants. Past 30-day dual users had more severe dryness (AOR, 2.65; 95% CI, 1.61-4.36; P < .001) and more frequent pain (AOR, 3.33; 95% CI, 2.12-5.21; P < .001) than all other participants. Ever dual users experienced more severe dryness (AOR, 1.60; 95% CI, 1.05-2.43; P = .03) and blurriness (AOR, 1.79; 95% CI, 1.21-2.64; P = .003) and more frequent pain (AOR, 1.69; 95% CI, 1.13-2.53; P = .01) and blurriness (AOR, 1.63; 95% CI, 1.13-2.36; P = .009) than never users.Conclusions and relevanceIn this cross-sectional US study, adolescents and young adult users of both e-cigarettes and cigarettes had a higher likelihood of experiencing severe and frequent ocular symptoms, with past 7-day users reporting more symptoms than past 30-day users or ever users. These findings provide additional reasons for users of e-cigarettes and cigarettes to reduce their tobacco use to possibly prevent or minimize ocular symptoms.

Project description:Background: The microbiome is increasingly being linked to cancer risk. Little is known about the lung and oral cavity microbiomes in healthy smokers (SM), and even less for electronic cigarette (EC) users, compared healthy never-smokers (NS). Methods: In a cross-sectional pilot study of SM (N=8), EC users (N=10) and NS (N=10) saliva and bronchoscopy-collected bronchoalveolar lavage samples were collected. Bacteria species were identified through metatranscriptome profiling by RNA-sequencing to study associations with the lung and oral microbiome. Pairwise comparisons and linear modeling was assessed with false discovery rates <0.1. Results: Total bacterial load was similar for the SM, EC users and NS, and there was no differences in the bacterial diversity across groups. In the lung, there were 44 bacterial species that were statistically significantly different for SM/NS, 80% of which were decreased in the SM. There were 12 bacterial species that were different for SM/EC users, all of which were decreased, 10 of which were also identified in the SM/NS comparison. The 2 bacterial species unique to SM/EC comparison were Neisseria sp. KEM232 and Curvibacter sp. AEP1-3. From the top 5 decreased species in SM/EC, 3 were also identified in the SM/NS comparison (Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae) and 2 of these were unique to the SM/EC comparison (Neisseria zoodegmatis and Ottowia sp. oral taxon 894). There were 8 species increased in SM compared to NS, none of which are known to be clinically significant. In the oral microbiome, 152 bacteria species were differentially abundant for the SM/NS analysis, and only 17 for the EC/NS comparison, all which were also present in SM/NS comparisons. There were 21 bacteria that were differentially abundant in both the lung and oral cavity for SM and NS, 95% also were decreased in the SM. Conclusion: Smoking and EC use do not appear to materially affect the lung microbiome, although differences are noted of unclear clinical significance. Most differentially abundant bacteria decreased, which may be due to a toxic effect of cigarette smoke, including a change in humidity or heating. Given the low number of overlapping oral and lung microbes, the oral microbiome does not appear to be a good surrogate for smoking-related effects in the lung.

Project description:To examine e-cigarette use and conventional cigarette smoking.Cross-sectional analyses of survey data from a representative sample of US middle and high school students in 2011 (n = 17 353) and 2012 (n = 22 529) who completed the 2011 and 2012 National Youth Tobacco Survey.Ever and current e-cigarette use.Experimentation with, ever, and current smoking, and smoking abstinence.Among cigarette experimenters (1 puff), ever e-cigarette use was associated with higher odds of ever smoking cigarettes (100 cigarettes; odds ratio [OR] = 6.31; 95% CI, 5.39-7.39) and current cigarette smoking (OR = 5.96; 95% CI, 5.67-6.27). Current e-cigarette use was positively associated with ever smoking cigarettes (OR = 7.42; 95% CI, 5.63-9.79) and current cigarette smoking (OR = 7.88; 95% CI, 6.01-10.32). In 2011, current cigarette smokers who had ever used e-cigarettes were more likely to intend to quit smoking within the next year (OR = 1.53; 95% CI, 1.03-2.28). Among experimenters with conventional cigarettes, ever use of e-cigarettes was associated with lower 30-day (OR = 0.24; 95% CI, 0.21-0.28), 6-month (OR = 0.24; 95% CI, 0.21-0.28), and 1-year (OR = 0.25; 95% CI, 0.21-0.30) abstinence from cigarettes. Current e-cigarette use was also associated with lower 30-day (OR = 0.11; 95% CI, 0.08-0.15), 6-month (OR = 0.11; 95% CI, 0.08-0.15), and 1-year (OR = 0.12; 95% CI, 0.07-0.18) abstinence. Among ever smokers of cigarettes (100 cigarettes), ever e-cigarette use was negatively associated with 30-day (OR = 0.61; 95% CI, 0.42-0.89), 6-month (OR = 0.53; 95% CI, 0.33-0.83), and 1-year (OR = 0.32; 95% CI, 0.18-0.56) abstinence from conventional cigarettes. Current e-cigarette use was also negatively associated with 30-day (OR = 0.35; 95% CI, 0.18-0.69), 6-month (OR = 0.30; 95% CI, 0.13-0.68), and 1-year (OR = 0.34; 95% CI, 0.13-0.87) abstinence.Use of e-cigarettes was associated with higher odds of ever or current cigarette smoking, higher odds of established smoking, higher odds of planning to quit smoking among current smokers, and, among experimenters, lower odds of abstinence from conventional cigarettes. Use of e-cigarettes does not discourage, and may encourage, conventional cigarette use among U.S. adolescents.

Dataset Information

"Technophilia": A new risk factor for electronic cigarette use among early adolescents?

Publications

"Technophilia": A new risk factor for electronic cigarette use among early adolescents?

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets