Jamie Brown

Associations Between E-Cigarette Type, Frequency of Use, and Quitting Smoking: Findings From a Longitudinal Online Panel Survey in Great Britain

Introduction: E-cigarettes can be categorized into two basic types, (1) cigalikes, that are disposable or use pre-filled cartridges and (2) tanks, that can be refilled with liquids. The aims of this study were to examine: (1) predictors of using the two e-cigarette types, and (2) the association between type used, frequency of use (daily vs. non-daily vs. no use), and quitting. Methods: Online longitudinal survey of smokers in Great Britain was first conducted in November 2012. Of 4064 respondents meeting inclusion criteria at baseline, this study included (N = 1643) current smokers followed-up 1 year later. Type and frequency of e-cigarette use were measured at follow-up. Results: At follow-up, 64% reported no e-cigarette use, 27% used cigalikes, and 9% used tanks. Among e-cigarette users at follow-up, respondents most likely to use tanks versus cigalikes included: 40–54 versus 18–24 year olds and those with low versus moderate/high education. Compared to no e-cigarette use at follow-up, non-daily cigalike users were less likely to have quit smoking since baseline (P = .0002), daily cigalike or non-daily tank users were no more or less likely to have quit (P = .3644 and P = .4216, respectively), and daily tank users were more likely to have quit (P = .0012). Conclusions: Whether e-cigarette use is associated with quitting depends on type and frequency of use. Compared with respondents not using e-cigarettes, daily tank users were more likely, and non-daily cigalike users were less likely, to have quit. Tanks were more likely to be used by older respondents and respondents with lower education.

Real‐world effectiveness of e‐cigarettes when used to aid smoking cessation: a cross‐sectional population study

Background and Aims Electronic cigarettes (e-cigarettes) are rapidly increasing in popularity. Two randomized controlled trials have suggested that e-cigarettes can aid smoking cessation, but there are many factors that could influence their real-world effectiveness. This study aimed to assess, using an established methodology, the effectiveness of e-cigarettes when used to aid smoking cessation compared with nicotine replacement therapy (NRT) bought over-the-counter and with unaided quitting in the general population. Design and Setting A large cross-sectional survey of a representative sample of the English population. Participants The study included 5863 adults who had smoked within the previous 12 months and made at least one quit attempt during that period with either an e-cigarette only (n = 464), NRT bought over-the-counter only (n = 1922) or no aid in their most recent quit attempt (n = 3477). Measurements The primary outcome was self-reported abstinence up to the time of the survey, adjusted for key potential confounders including nicotine dependence. Findings E-cigarette users were more likely to report abstinence than either those who used NRT bought over-the-counter [odds ratio (OR) = 2.23, 95% confidence interval (CI) = 1.70–2.93, 20.0 versus 10.1%] or no aid (OR = 1.38, 95% CI = 1.08–1.76, 20.0 versus 15.4%). The adjusted odds of non-smoking in users of e-cigarettes were 1.63 (95% CI = 1.17–2.27) times higher compared with users of NRT bought over-the-counter and 1.61 (95% CI = 1.19–2.18) times higher compared with those using no aid. Conclusions Among smokers who have attempted to stop without professional support, those who use e-cigarettes are more likely to report continued abstinence than those who used a licensed NRT product bought over-the-counter or no aid to cessation. This difference persists after adjusting for a range of smoker characteristics such as nicotine dependence.

Prevalence and characteristics of e-cigarette users in Great Britain: Findings from a general population survey of smokers

Background E-cigarettes may be effective smoking cessation aids and their use by smokers has been growing rapidly. It is important to observe and assess natural patterns in the use of e-cigarettes whilst experimental data accumulates. This paper reports the prevalence of e-cigarette awareness, beliefs and usage, including brand choice, and characterises the socio-demographic and smoking profile associated with current use, among the general population of smokers and recent ex-smokers. Methods Data were obtained from 3538 current and 579 recent ex-smokers in a cross-sectional online survey of a national sample of smokers in Great Britain in November and December 2012. Differences between current and recent ex-smokers in the prevalence of e-cigarette awareness, beliefs and usage were examined and the socio-demographic and smoking profile associated with current use of e-cigarettes was assessed in a series of simple and multiple logistic regressions. Results Ninety-three percent of current and recent ex-smokers (n = 3841) were aware of e-cigarettes. Approximately a fifth (n = 884) were currently using e-cigarettes, whilst just over a third (n = 1507) had ever used them. Sixty-seven percent of the sample (n = 2758) believed e-cigarettes to be less harmful than cigarettes; however, almost a quarter (n = 994) remained unsure. Among both current and recent ex-smokers, the most popular reasons for using were health, cutting down and quitting (each > 80%) and 38% used the brand ‘E-lites’. Among current smokers who were aware of but had never used e-cigarettes, approximately half (n = 1040) were interested in using them in the future. Among current smokers, their use was associated with higher socio-economic status (OR = 1.48, 95%CI = 1.25–1.75), smoking more cigarettes (OR = 1.02, 95%CI = 1.01–1.03) and having a past-year quit attempt (OR = 2.82, 95%CI = 2.38–3.34). Conclusions There is a near universal awareness of e-cigarettes and their use appears to be common among smokers in Great Britain although a quarter of all smokers are unsure as to whether e-cigarettes are less harmful than cigarettes. E-lites – a brand that delivers a low dose of nicotine – is the most popular. E-cigarette users appear to have higher socio-economic status, to smoke more cigarettes per day and to have attempted to quit in the past year.

Is the use of electronic cigarettes while smoking associated with smoking cessation attempts, cessation and reduced cigarette consumption? A survey with a 1‐year follow‐up

Abstract Aims To use a unique longitudinal data set to assess the association between e‐cigarette use while smoking with smoking cessation attempts, cessation and substantial reduction, taking into account frequency of use and key potential confounders. Design Web‐based survey, baseline November/December 2012, 1‐year follow‐up in December 2013. Setting Great Britain. Participants National general population sample of 4064 adult smokers, with 1759 (43%) followed‐up. Measurements Main outcome measures were cessation attempt, cessation and substantial reduction (≥50% from baseline to follow‐up) of cigarettes per day (CPD). In logistic regression models, cessation attempt in the last year (analysis n = 1473) and smoking status (n = 1656) at follow‐up were regressed on to baseline e‐cigarette use (none, non‐daily, daily) while adjusting for baseline socio‐demographics, dependence and nicotine replacement (NRT) use. Substantial reduction (n = 1042) was regressed on to follow‐up e‐cigarette use while adjusting for baseline socio‐demographics and dependence and follow‐up NRT use. Findings Compared with non‐use, daily e‐cigarette use at baseline was associated with increased cessation attempts [odds ratio (OR) = 2.11, 95% confidence interval (CI) = 1.24–3.58, P = 0.006], but not with cessation at follow‐up (OR = 0.62, 95% CI = 0.28–1.37, P = 0.24). Non‐daily use was not associated with cessation attempts or cessation. Daily e‐cigarette use at follow‐up was associated with increased odds of substantial reduction (OR = 2.49, 95% CI = 1.14–5.45, P = 0.02), non‐daily use was not. Conclusions Daily use of e‐cigarettes while smoking appears to be associated with subsequent increases in rates of attempting to stop smoking and reducing smoking, but not with smoking cessation. Non‐daily use of e‐cigarettes while smoking does not appear to be associated with cessation attempts, cessation or reduced smoking.

Association between electronic cigarette use and changes in quit attempts, success of quit attempts, use of smoking cessation pharmacotherapy, and use of stop smoking services in England: time series analysis of population trends.

Objectives To estimate how far changes in the prevalence of electronic cigarette (e-cigarette) use in England have been associated with changes in quit success, quit attempts, and use of licensed medication and behavioural support in quit attempts. Design Time series analysis of population trends. Participants Participants came from the Smoking Toolkit Study, which involves repeated, cross sectional household surveys of individuals aged 16 years and older in England. Data were aggregated on about 1200 smokers quarterly between 2006 and 2015. Monitoring data were also used from the national behavioural support programme; during the study, 8 029 012 quit dates were set with this programme. Setting England. Main outcome measures Prevalence of e-cigarette use in current smokers and during a quit attempt were used to predict quit success. Prevalence of e-cigarette use in current smokers was used to predict rate of quit attempts. Percentage of quit attempts involving e-cigarette use was also used to predict quit attempts involving use of prescription treatments, nicotine replacement therapy (NRT) on prescription and bought over the counter, and use of behavioural support. Analyses involved adjustment for a range of potential confounders. Results The success rate of quit attempts increased by 0.098% (95% confidence interval 0.064 to 0.132; P<0.001) and 0.058% (0.038 to 0.078; P<0.001) for every 1% increase in the prevalence of e-cigarette use by smokers and e-cigarette use during a recent quit attempt, respectively. There was no clear evidence for an association between e-cigarette use and rate of quit attempts (β 0.025; 95% confidence interval −0.035 to 0.085; P=0.41), use of NRT bought over the counter (β 0.006; −0.088 to 0.077; P=0.89), use of prescription treatment (β −0.070; −0.152 to 0.013; P=0.10), or use of behavioural support (β −0.013; −0.102 to 0.077; P=0.78). A negative association was found between e-cigarette use during a recent quit attempt and use of NRT obtained on prescription (β −0.098; −0.189 to −0.007; P=0.04). Conclusion Changes in prevalence of e-cigarette use in England have been positively associated with the success rates of quit attempts. No clear association has been found between e-cigarette use and the rate of quit attempts or the use of other quitting aids, except for NRT obtained on prescription, where the association has been negative. Study registration The analysis plan was preregistered (https://osf.io/fbgj2/).

Prospective Cohort Study of the Effectiveness of Smoking Cessation Treatments Used in the "Real World"

Objective To estimate the “real-world” effectiveness of commonly used aids to smoking cessation in England by using longitudinal data. Patients and Methods We conducted a prospective cohort study in 1560 adult smokers who participated in an English national household survey in the period from November 2006 to March 2012, responded to a 6-month follow-up survey, and made at least 1 quit attempt between the 2 measurements. The quitting method was classified as follows: (1) prescription medication (nicotine replacement therapy [NRT], bupropion, or varenicline) in combination with specialist behavioral support delivered by a National Health Service Stop Smoking Service; (2) prescription medication with brief advice; (3) NRT bought over the counter; (4) none of these. The primary outcome measure was self-reported abstinence up to the time of the 6-month follow-up survey, adjusted for key potential confounders including cigarette dependence. Results Compared with smokers using none of the cessation aids, the adjusted odds of remaining abstinent up to the time of the 6-month follow-up survey were 2.58 (95% CI, 1.48-4.52) times higher in users of prescription medication in combination with specialist behavioral support and 1.55 (95% CI, 1.11-2.16) times higher in users of prescription medication with brief advice. The use of NRT bought over the counter was associated with a lower odds of abstinence (odds ratio, 0.68; 95% CI, 0.49-0.94). Conclusion Prescription medication offered with specialist behavioral support and that offered with minimal behavioral support are successful methods of stopping cigarette smoking in England.

Internet-based intervention for smoking cessation (StopAdvisor) in people with low and high socioeconomic status: a randomised controlled trial

BACKGROUND Internet-based interventions for smoking cessation could help millions of people stop smoking at very low unit costs; however, long-term biochemically verified evidence is scarce and such interventions might be less effective for smokers with low socioeconomic status than for those with high status because of lower online literacy to engage with websites. We aimed to assess a new interactive internet-based intervention (StopAdvisor) for smoking cessation that was designed with particular attention directed to people with low socioeconomic status. METHODS We did this online randomised controlled trial between Dec 6, 2011, and Oct 11, 2013, in the UK. Participants aged 18 years and older who smoked every day were randomly assigned (1:1) to receive treatment with StopAdvisor or an information-only website. Randomisation was automated with an unseen random number function embedded in the website to establish which treatment was revealed after the online baseline assessment. Recruitment continued until the required sample size had been achieved from both high and low socioeconomic status subpopulations. Participants, and researchers who obtained data and did laboratory analyses, were masked to treatment allocation. The primary outcome was 6 month sustained, biochemically verified abstinence. The main secondary outcome was 6 month, 7 day biochemically verified point prevalence. Analysis was by intention to treat. Homogeneity of intervention effect across the socioeconomic subsamples was first assessed to establish whether overall or separate subsample analyses were appropriate. The study is registered as an International Standard Randomised Controlled Trial, number ISRCTN99820519. FINDINGS We randomly assigned 4613 participants to the StopAdvisor group (n=2321) or the control group (n=2292); 2142 participants were of low socioeconomic status and 2471 participants were of high status. The overall rate of smoking cessation was similar between participants in the StopAdvisor and control groups for the primary (237 [10%] vs 220 [10%] participants; relative risk [RR] 1·06, 95% CI 0·89-1·27; p=0·49) and the secondary (358 [15%] vs 332 [15%] participants; 1·06, 0·93-1·22; p=0·37) outcomes; however, the intervention effect differed across socioeconomic status subsamples (1·44, 0·99-2·09; p=0·0562 and 1·37, 1·02-1·84; p=0·0360, respectively). StopAdvisor helped participants with low socioeconomic status stop smoking compared with the information-only website (primary outcome: 90 [8%] of 1088 vs 64 [6%] of 1054 participants; RR 1·36, 95% CI 1·00-1·86; p=0·0499; secondary outcome: 136 [13%] vs 100 [10%] participants; 1·32, 1·03-1·68, p=0·0267), but did not improve cessation rates in those with high socioeconomic status (147 [12%] of 1233 vs 156 [13%] of 1238 participants; 0·95, 0·77-1·17; p=0·61 and 222 [18%] vs 232 [19%] participants; 0·96, 0·81-1·13, p=0·64, respectively). INTERPRETATION StopAdvisor was more effective than an information-only website in smokers of low, but not high, socioeconomic status. StopAdvisor could be implemented easily and made freely available, which would probably improve the success rates of smokers with low socioeconomic status who are seeking online support. FUNDING National Prevention Research Initiative.

Summative assessments are more powerful drivers of student learning than resource intensive teaching formats

BackgroundElectrocardiogram (ECG) interpretation is a core clinical skill that needs to be acquired during undergraduate medical education. Intensive teaching is generally assumed to produce more favorable learning outcomes, but recent research suggests that examinations are more powerful drivers of student learning than instructional format. This study assessed the differential contribution of teaching format and examination consequences to learning outcome regarding ECG interpretation skills in undergraduate medical students.MethodsA total of 534 fourth-year medical students participated in a six-group (two sets of three), partially randomized trial. Students received three levels of teaching intensity: self-directed learning (two groups), lectures (two groups) or small-group peer teaching facilitated by more advanced students (two groups). One of the two groups on each level of teaching intensity was assessed in a formative, the other in a summative written ECG examination, which provided a maximum of 1% credit points of the total curriculum. The formative examination provided individual feedback without credit points. Main outcome was the correct identification of ≥3 out of 5 diagnoses in original ECG tracings. Secondary outcome measures were time spent on independent study and use of additional study material.ResultsCompared with formative assessments, summative assessments increased the odds of correctly identifying at least three out of five ECG diagnoses (OR 5.14; 95% CI 3.26 to 8.09), of spending at least 2 h/week extra on ECG self-study (OR 4.02; 95% CI 2.65 to 6.12) and of using additional learning material (OR 2.86; 95% CI 1.92 to 4.24). Lectures and peer teaching were associated with increased learning effort only, but did not augment examination performance.ConclusionsMedical educators need to be aware of the paramount role of summative assessments in promoting student learning. Consequently, examinations within medical schools need to be closely matched to the desired learning outcomes. Shifting resources from implementing innovative and costly teaching formats to designing more high-quality summative examinations warrants further investigation.

Perceived relative harm of electronic cigarettes over time and impact on subsequent use. A survey with 1-year and 2-year follow-ups.

Highlights • A cohort of smokers and ex-smokers was followed over a period of two years.• Perceived harm of electronic cigarettes relative to cigarettes increased over time.• Smoking cessation ande-cigarette use predicted subsequent perceived relative harm.• Perceived relative harm predicted subsequent use of e-cigarettes in non-users.

Development of StopAdvisor: A theory-based interactive internet-based smoking cessation intervention

ABSTRACTReviews of internet-based behaviour-change interventions have shown that they can be effective but there is considerable heterogeneity and effect sizes are generally small. In order to advance science and technology in this area, it is essential to be able to build on principles and evidence of behaviour change in an incremental manner. We report the development of an interactive smoking cessation website, StopAdvisor, designed to be attractive and effective across the social spectrum. It was informed by a broad motivational theory (PRIME), empirical evidence, web-design expertise, and user-testing. The intervention was developed using an open-source web-development platform, ‘LifeGuide’, designed to facilitate optimisation and collaboration. We identified 19 theoretical propositions, 33 evidence- or theory-based behaviour change techniques, 26 web-design principles and nine principles from user-testing. These were synthesised to create the website, ‘StopAdvisor’ (see http://www.lifeguideonline.org/player/play/stopadvisordemonstration). The systematic and transparent application of theory, evidence, web-design expertise and user-testing within an open-source development platform can provide a basis for multi-phase optimisation contributing to an ‘incremental technology’ of behaviour change.