Krysten W. Bold

Reasons for trying e-cigarettes and risk of continued use

BACKGROUND: Longitudinal research is needed to identify predictors of continued electronic cigarette (e-cigarette) use among youth. We expected that certain reasons for first trying e-cigarettes would predict continued use over time (eg, good flavors, friends use), whereas other reasons would not predict continued use (eg, curiosity). METHODS: Longitudinal surveys from middle and high school students from fall 2013 (wave 1) and spring 2014 (wave 2) were used to examine reasons for trying e-cigarettes as predictors of continued e-cigarette use over time. Ever e-cigarette users (n = 340) at wave 1 were categorized into those using or not using e-cigarettes at wave 2. Among those who continued using e-cigarettes, reasons for trying e-cigarettes were examined as predictors of use frequency, measured as the number of days using e-cigarettes in the past 30 days at wave 2. Covariates included age, sex, race, and smoking of traditional cigarettes. RESULTS: Several reasons for first trying e-cigarettes predicted continued use, including low cost, the ability to use e-cigarettes anywhere, and to quit smoking regular cigarettes. Trying e-cigarettes because of low cost also predicted more days of e-cigarette use at wave 2. Being younger or a current smoker of traditional cigarettes also predicted continued use and more frequent use over time. CONCLUSIONS: Regulatory strategies such as increasing cost or prohibiting e-cigarette use in certain places may be important for preventing continued use in youth. In addition, interventions targeting current cigarette smokers and younger students may also be needed.

Assessment of Riboflavin as a Tracer Substance: Comparison of a Qualitative to a Quantitative Method of Riboflavin Measurement

BACKGROUND Noncompliance with medications may have major impacts on outcomes measured in research, potentially distorting the validity of controlled clinical trials. Riboflavin is frequently used in trials as a marker of adherence. It can be combined with study medication and is excreted in urine where it fluoresces under UV light. This study compares qualitative visual inspection of fluorescence to quantitative fluorometric analysis of riboflavin concentration in its ability to detect the presence of riboflavin in urine. METHODS Twenty-four volunteers received 0mg, 25mg, and 50mg doses of riboflavin under single-blind conditions, with 20 also receiving a 100mg dose. Five serial urine samples were collected over the following 36h. Quantitative measurement of riboflavin by fluorometric analysis and qualitative assessment of each sample using visual inspection were performed. RESULTS The overall false positive rate for qualitative assessment was 53%. For quantitative assessment, a riboflavin concentration of 900ng/mL was established to classify positive samples. More than 80% of samples were positive 2-24h following ingestion of 25mg and 50mg, and less than 80% were positive at 36h. At least 95% of observations for the 100mg dose were above 900ng/mL at all timepoints. CONCLUSIONS Quantitative fluorometric assessment is superior to qualitative visual inspection alone in determining medication adherence. The combination of 25-50mg of daily riboflavin and a cut-off level of 900ng/mL allows for the acceptable sensitivity of missing detection of non-compliant participants while preserving a high level of power to detect all cases of medication compliance.

E-Cigarette Susceptibility as a Predictor of Youth Initiation of E-Cigarettes

Introduction Identifying youth at risk for future e-cigarette use is critical for informing prevention efforts. Prior research established measures of susceptibility to conventional cigarettes, and this study aimed to examine whether items adapted for e-cigarette susceptibility predicted subsequent e-cigarette use among never e-cigarette users. Methods Longitudinal school-wide survey data were collected from middle and high school students in Fall 2013 (wave 1) and Spring 2014 (wave 2). Among never e-cigarette users at wave 1 (n = 1720), e-cigarette susceptibility was measured by two items assessing anticipation of experimenting with e-cigarettes in the future and willingness to use an e-cigarette if offered by a best friend. Logistic regression models examined susceptibility as a predictor of e-cigarette initiation and past 30-day use 6 months later at wave 2. Models were clustered by school and controlled for sex, age, race, SES, and other substance use (alcohol, marijuana, and other tobacco). Results In total, 8.9% (n = 153) of youth initiated e-cigarettes and 3.7% (n = 63) reported past 30-day use at wave 2. E-cigarette susceptibility was a significant independent predictor of subsequent initiation (OR = 4.27, 95% CI = 3.12-5.85) and past 30-day e-cigarette use (OR = 5.10, 95%CI = 3.38-7.68) 6 months later. Susceptible youth were more likely to be male, older, and have used alcohol, marijuana, or other tobacco products. Conclusions These findings provide initial support for adapting two susceptibility items to identify adolescents at risk for future e-cigarette use. Identifying strategies that are effective for targeting susceptible youth and preventing future e-cigarette use will be critical areas for future research. Implications More than a quarter of the sample who reported both a willingness to try e-cigarettes if offered by a best friend and anticipation of experimenting with e-cigarettes in the future went on to try e-cigarettes within the academic year, suggesting that targeting this group will be critical for preventing youth e-cigarette initiation. There were notable demographic differences between susceptible and non-susceptible youth, suggesting targeting e-cigarette prevention efforts to male students who have used other substances may be especially important for preventing future e-cigarette use. Research is needed to determine the most effective prevention strategies to reach susceptible youth.

Relations among affect, abstinence motivation and confidence, and daily smoking lapse risk.

This study tested the hypothesis that changes in momentary affect, abstinence motivation, and confidence would predict lapse risk over the next 12-24 hr using Ecological Momentary Assessment (EMA) data from smokers attempting to quit smoking. One hundred and three adult, daily, treatment-seeking smokers recorded their momentary affect, motivation to quit, abstinence confidence, and smoking behaviors in near real time with multiple EMA reports per day using electronic diaries postquit. Multilevel models indicated that initial levels of negative affect were associated with smoking, even after controlling for earlier smoking status, and that short-term increases in negative affect predicted lapses up to 12, but not 24, hr later. Positive affect had significant effects on subsequent abstinence confidence, but not motivation to quit. High levels of motivation appeared to reduce increases in lapse risk that occur over hours although momentary changes in confidence did not predict lapse risk over 12 hr. Negative affect had short-lived effects on lapse risk, whereas higher levels of motivation protected against the risk of lapsing that accumulates over hours. An increase in positive affect was associated with greater confidence to quit, but such changes in confidence did not reduce short-term lapse risk, contrary to expectations. Relations observed among affect, cognitions, and lapse seem to depend critically on the timing of assessments.

E-Cigarettes and “Dripping” Among High-School Youth

Using surveys, this study captures rates and reasons for ever use of e-cigarettes for “dripping” among high school youth. BACKGROUND: Electronic cigarettes (e-cigarettes) electrically heat and vaporize e-liquids to produce inhalable vapors. These devices are being used to inhale vapors produced by dripping e-liquids directly onto heated atomizers. The current study conducts the first evaluation of the prevalence rates and reasons for using e-cigarettes for dripping among high school students. METHODS: In the spring of 2015, students from 8 Connecticut high schools (n = 7045) completed anonymous surveys that examined tobacco use behaviors and perceptions. We assessed prevalence rates of ever using e-cigarettes for dripping, reasons for dripping, and predictors of dripping behaviors among those who reported ever use of e-cigarettes. RESULTS: Among 1080 ever e-cigarette users, 26.1% of students reported ever using e-cigarettes for dripping. Reasons for dripping included produced thicker clouds of vapor (63.5%), made flavors taste better (38.7%), produced a stronger throat hit (27.7%), curiosity (21.6%), and other (7.5%). Logistic regression analyses indicated that male adolescents (odds ratio [OR] = 1.64), whites (OR = 1.46), and those who had tried multiple tobacco products (OR = 1.34) and had greater past-month e-cigarette use frequency (OR = 1.07) were more likely to use dripping (Ps < .05). CONCLUSIONS: These findings indicate that a substantial portion (∼1 in 4) of high school adolescents who had ever used e-cigarettes also report using the device for dripping. Future efforts must examine the progression and toxicity of the use of e-cigarettes for dripping among youth and educate them about the potential dangers of these behaviors.

Factors Predicting Smoking in a Laboratory-Based Smoking- Choice Task

This study aimed to expand the current understanding of smoking maintenance mechanisms by examining how putative relapse risk factors relate to a single behavioral smoking choice using a novel laboratory smoking-choice task. After 12 hr of nicotine deprivation, participants were exposed to smoking cues and given the choice between smoking up to two cigarettes in a 15-min window or waiting and receiving four cigarettes after a delay of 45 min. Greater nicotine dependence, higher impulsivity, and lower distress tolerance were hypothesized to predict earlier and more intensive smoking. Out of 35 participants (n = 9 women), 26 chose to smoke with a median time to a first puff of 1.22 min (SD = 2.62 min, range = 0.03-10.62 min). Survival analyses examined latency to first puff, and results indicated that greater pretask craving and smoking more cigarettes per day were significantly related to smoking sooner in the task. Greater behavioral disinhibition predicted shorter smoking latency in the first 2 min of the task, but not at a delay of more than 2 min. Lower distress tolerance (reporting greater regulation efforts to alleviate distress) was related to more puffs smoked and greater nicotine dependence was related to more time spent smoking in the task. This novel laboratory smoking-choice paradigm may be a useful laboratory analog for the choices smokers make during cessation attempts and may help identify factors that influence smoking lapses.

Trajectories of E-Cigarette and Conventional Cigarette Use Among Youth

In this study, we examine predictive longitudinal relationships between past-month cigarette and e-cigarette use across 3 waves by using high school survey data. BACKGROUND: Electronic cigarette (e-cigarette) use is common among youth, and there are concerns that e-cigarette use leads to future conventional cigarette use. We examined longitudinal associations between past-month cigarette and e-cigarette use to characterize the stability and directionality of these tobacco use trajectories over time. METHODS: High school students (N = 808, 53% female) completed surveys across 3 waves (2013, 2014, and 2015) in 3 public schools in Connecticut. Using autoregressive cross-lagged models, we examined bidirectional relationships between past-month cigarette and e-cigarette use over time. Models were adjusted for covariates related to tobacco use (ie, sex, race/ethnicity, socioeconomic status, and use of other tobacco products). RESULTS: Past-month e-cigarette use predicted future cigarette use (wave 1–2: odds ratio [OR] = 7.08, 95% confidence interval [CI] = 2.34–21.42; wave 2–3: OR = 3.87, 95% CI = 1.86–8.06). However, past-month cigarette use did not predict future e-cigarette use (wave 1–2: OR = 2.02, 95% CI = 0.67–6.08; wave 2–3: OR = 1.90, 95% CI = 0.77–4.71). Additionally, frequency of cigarette and e-cigarette use increased over time. By wave 3, 26% of cigarette users and 20.5% of e-cigarette users reported using 21–30 days out of the past month. CONCLUSIONS: E-cigarette use was associated with future cigarette use across 3 longitudinal waves, yet cigarette use was not associated with future e-cigarette use. Future research needs to examine mechanisms through which e-cigarette use leads to cigarette use. E-cigarette regulation and prevention programs may help prevent future use of cigarettes among youth.

Exploring the Utility of Web-Based Social Media Advertising to Recruit Adult Heavy-Drinking Smokers for Treatment

Background Identifying novel ways to recruit smokers for treatment studies is important. In particular, certain subgroups of adult smokers, such as heavy-drinking smokers, are at increased risk for serious medical problems and are less likely to try quitting smoking, so drawing this hard-to-reach population into treatment is important for improving health outcomes. Objective This study examined the utility of Facebook advertisements to recruit smokers and heavy-drinking smokers for treatment research and evaluated smoking and alcohol use and current treatment goals among those who responded to the Web-based survey. Methods Using Facebook’s advertising program, 3 separate advertisements ran for 2 months targeting smokers who were thinking about quitting. Advertisements were shown to adult (at least 18 years of age), English-speaking Facebook users in the greater New Haven, Connecticut, area. Participants were invited to complete a Web-based survey to determine initial eligibility for a smoking cessation research study. Results Advertisements generated 1781 clicks and 272 valid, completed surveys in 2 months, with one advertisement generating the most interest. Facebook advertising was highly cost-effective, averaging

Independent and interactive effects of real-time risk factors on later temptations and lapses among smokers trying to quit

0.27 per click,

Effect of Varenicline Combined With Medical Management on Alcohol Use Disorder With Comorbid Cigarette Smoking: A Randomized Clinical Trial

1.76 per completed survey, and