Introduction: The nicotine–metabolite ratio (NMR) predicts treatment response and is related to treatment side effect severity. Sleep disturbance may be one important side effect, but understanding sleep disturbance effects on smoking cessation is complicated by the fact that nicotine withdrawal also produces sleep disturbance.

Aims: To evaluate the effects of withdrawal and treatment side effects on sleep disturbance.

Methods: This is a secondary analysis of data from a clinical trial (Lerman et al., 2015) of 1,136 smokers randomised to placebo (n = 363), transdermal nicotine (TN; n = 381), or varenicline (n = 392) and stratified based on NMR (559 slow metabolisers; 577 normal metabolisers). Sleep disturbance was assessed at baseline and at 1-week following the target quit date (TQD). We also examined whether sleep disturbance predicted 7-day point-prevalence abstinence at end-of-treatment (EOT).

Results: The varenicline and TN groups exhibited greater increases in sleep disturbance (vs. placebo; treatment × time interaction; p = 0.005), particularly among those who quit smoking at 1-week post-TQD. There was a main effect of NMR (p = 0.04), but no interactions with treatment. TN and varenicline attenuated withdrawal symptoms unrelated to sleep (vs. placebo). Greater baseline sleep disturbance predicted relapse at EOT (p = 0.004).

Conclusions: Existing treatments may not mitigate withdrawal-related sleep disturbance and adjunctive treatments that target sleep disturbance may improve abstinence rates.

Introduction: Waking at night to smoke can also serve as an indicator of dependence and treatment success.

Aims: We sought to examine whether night smoking is associated with features of smoking behaviour in a non-treatment-seeking sample of adult smokers in the general population.

Methods: Data for this study come from 1,062 current smokers obtained from an opt-in online panel in July 2010. Night smoking and night craving to smoke were assessed by questionnaire, and dependence was assessed by the Fagerstrom Test for Nicotine Dependence (FTND). Relationships were assessed using linear, logistic, and negative binomial regression.

Findings: Overall, 20.6% reported that they woke at night to smoke. FTND scores were substantially higher in those reporting night smoking. Those who reported night cravings were more likely to report quit intentions. Night smokers made 3.6 actual quit attempts (95% CI: 2.8, 4.5) per year, adjusted for other model factors, compared to 2.7 (2.2, 3.2) attempts for night cravers and 2.2 (1.8, 2.7) attempts for smokers who reported neither.

Conclusions: Overall, night smokers reported higher nicotine dependence than cravers and those who experienced neither. The current study adds to a growing literature pointing to the importance of overnight smoking as an indicator of nicotine dependence.

Introduction: Tobacco use is common among people who have been in prison. The relationship between social stressors, risky health behaviours, and smoking cessation has not been studied in people recently released from prison. Studying this relationship could yield information that guides strategic and cost-effective tobacco cessation interventions for an under-resourced population.

Methods: One hundred and forty-three smokers were interviewed 7 to 21 days after they had been released from USA prisons. Independent variables included employment status, housing security, relationship problems, educational achievement, risky drinking behaviour, recent drug use, history of drug dependence, and depression. The primary outcome was ‘trying to quit smoking.’ Data were analysed using Pearson chi-square tests and single and multivariable logistic regression models.

Results: Of those who had to quit smoking due to tobacco-free prison policies, 98% reported relapsing on tobacco after release. Trying to quit smoking was associated with the absence of risky drinking behaviour in the past 30 days (adjusted odds ratio [AOR] 6.44, 95% confidence interval [CI] 2.02–20.48).

Conclusions: The absence of risky drinking behaviour is associated with trying to quit smoking among people recently released from prison. Further research may determine whether interventions addressing risky alcohol use can reduce smoking relapse.

The case study received ethics approval from Sydney Local Health District Ethics Review Committee.

Introduction: Despite the public health relevance of smoking in adolescents and emerging adults, this group remains understudied and underserved. High technology utilisation among this group may be harnessed as a tool for better understanding of smoking, yet little is known regarding the acceptability of mobile health (mHealth) integration.

Methods: Participants (ages 14–21 years) enrolled in a smoking cessation clinical trial provided feedback on their technology utilisation, perceptions, and attitudes; and interest in remote monitoring for smoking. Characteristics that predicted greater technology acceptability for smoking treatment were also explored.

Results: Participants (N = 87) averaged 19 years old and were mostly male (67%). Technology utilisation was high for smart phone ownership (93%), Internet use (98%), and social media use (94%). Despite this, only one-third of participants had ever searched the Internet for cessation tips or counselling (33%). Participants showed interest in mHealth-enabled treatment (48%) and felt that it could be somewhat helpful (83%). Heavier smokers had more favourable attitudes toward technology-based treatment, as did those with smartphones and unlimited data.

Conclusions: Our results demonstrate high technology utilisation, favourable attitudes towards technology, and minimal concerns. Technology integration among this population should be pursued, though in a tailored fashion, to accomplish the goal of providing maximally effective, just-in-time interventions.

Introduction: Suboptimal use of nicotine replacement therapy (NRT) may pose a significant barrier to smokers attempting to quit. We examined NRT use as a predictor of smoking abstinence and heavy drinking in a randomised trial of hazardous drinkers who contacted the NY State Smokers’ quitline for smoking cessation assistance.

Methods: Participants (N = 1,948) received either Tobacco Only Counselling or Alcohol + Tobacco Counselling (ATC), both in addition to a 2-week supply of NRT. NRT use, smoking status, and heavy drinking days were assessed by self-report at the 7-month follow-up.

Results: Of those smokers who completed the 7-month follow-up (N = 843), 53.1% used all of the NRT and 40.6% used some. Those who used all of the NRT were more likely to be abstinent from smoking than those who used some, and more likely to report no heavy drinking days than those who used some or none.

Conclusions: Approximately half of the heavy drinking smokers calling the quitline are willing to use the 2-week supply of free NRT, and most will at least try it. Those who reported using all of the NRT were more likely to report smoking abstinence and no heavy drinking days at the 7-month follow-up.

Introduction: The current study examined the level of agreement in expired-air carbon monoxide (CO) values, focusing especially on those confirming abstinence, between the two most commonly used CO monitors, the Vitalograph BreathCO and the Bedfont piCO+ Smokerlyzer.

Methods: Expired-air samples were collected via both monitors from adult dependent smokers (44 M, 34 F) participating in studies using CO values to confirm abstinence durations of: 24 hours, 12 hours, or no abstinence. All met DSM-IV nicotine dependence criteria and had a mean (SD) Fagerström Test of Cigarette Dependence score of 5.1 (1.8). Paired data collected across multiple visits were analyzed by regression-based Bland–Altman method of Limits of Agreement (LoA).

Findings: Analysis indicated a lack of agreement in CO measurement between monitors. Overall, the Bedfont monitor gave mean (±SEM) readings 3.83 (±0.23) ppm higher than the Vitalograph monitor. Mean differences between monitors were larger for those ad lib smoking (5.65 ± 0.38 ppm) than those abstaining 12–24 hours (1.71 ± 0.13 ppm). Yet, there also was not consistent agreement in classification of 24-hour abstinence between monitors.

Conclusions: Systematic differences in CO readings demonstrate these two very common monitors may not result in interchangeable values, and reported outcomes in smoking research based on CO values may depend on the monitor used.

Introductions: Healthcare workers use less tobacco than other working populations. In contrast, US military members use more tobacco than civilians. Military healthcare workers, therefore, represent a unique group with regard to occupational factors that may influence tobacco use.

Aims/Methods: Records of workers at a military community hospital were reviewed to describe tobacco use. An anonymous survey assessed impressions of a worksite policy change that prohibited tobacco use anywhere on hospital grounds.

Results: Hospital staff included 2,074 professionals. Tobacco use was significantly associated with male sex and being a military enlisted worker. In fact, 37% of male enlisted members used tobacco; fewer than 10% of all other workers used tobacco. Among 232 survey respondents, 61% agreed with tobacco-restrictive worksite policies, but only 33% thought policies were effective. Nearly one-third of tobacco users reported decreasing use in the past year. In multivariable modelling, changing habits in response to worksite policy was the only factor significantly associated with decreased tobacco use.

Conclusions: Tobacco use among US military healthcare workers varies markedly by demographic characteristics. Male, military enlisted workers use tobacco at very high rates, paralleling the troops they serve. Implementation of tobacco-restrictive worksite policies is associated with decreased tobacco use in this population.