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Aims: To measure the association between problem gambling severity and 19 different gambling activities among emerging adults (aged 16–26). Design: An online non‐probability longitudinal survey collecting data in two waves: wave 1, July/August 2019; wave 2, July/October 2020. Setting: Great Britain Participants: A total of 2080 young adults participating in both waves. Measurements Problem gambling scores were collected using the Problem Gambling Severity Index (PGSI). Binary variables recorded past year participation in 19 different gambling forms, ranging from lotteries to online casino and gambling‐like practices within digital games (e.g. loot box purchase, skin betting). Controls included socio‐demographic/economic characteristics, the Eysenck Impulsivity Scale and the number of gambling activities undertaken. Findings Zero inflated negative binomial model lacked evidence of an effect between past year participation in any individual activities and subsequent PGSI scores. However, negative binomial random effects models for current gamblers (n = 497) showed that skin betting (incidence‐rate ratio [IRR] = 2.32; 95% CI = 1.69–3.19), fixed odd betting terminals (IRR = 2.21, 95% CI = 1.61–3.05), slot/fruit machines (IRR = 1.43, 95% CI = 1.07–1.91), online betting on horse/dog races (IRR = 1.53, 95% CI = 1.17–2.00) and online betting on non‐sports events (IRR = 1.44, 95% CI = 1.11–1.89) were associated with increased PGSI scores. Online casino gambling had a significant interaction by wave; the impact of online casino betting in wave 2 on PGSI scores increased by a factor of 1.61. Conclusions: Past year participation of young adults (aged 16–26) in certain forms of gambling does not appear to be associated with future Problem Gambling Severity Index scores. Among young adults who are current gamblers, past year participation in certain land‐based (e.g. electronic gaming machines) and online forms (e.g. skin betting) of gambling appears to be strongly associated with elevated Problem Gambling Severity Index scores. [ABSTRACT FROM AUTHOR]

Aims: To estimate recent trends in the prevalence of disposable e‐cigarette vaping in Great Britain, overall and across ages, and to measure these trends in the context of changes in smoking and vaping prevalence. Design: The Smoking Toolkit Study, a monthly representative cross‐sectional survey. Setting: Great Britain. Participants: A total of 36 876 adults (≥ 18 years) completed telephone interviews between January 2021 and April 2022. Measurements Current e‐cigarette vapers were asked which type of device they mainly use. We estimated age‐specific monthly time trends in the prevalence of current disposable e‐cigarette use among vapers and inhaled nicotine use (vaping/smoking), smoking and vaping among adults. Findings From January 2021 to April 2022, there was an 18‐fold increase in the percentage of vapers who used disposables, rising from 1.2 to 22.2% [prevalence ratio (PR) = 18.0; 95% compatibility interval (CI) = 9.18–49.0]. Growth in disposable e‐cigarette vaping was most pronounced in younger adults (interaction P‐value = 0.013): for example, the percentage of 18‐year‐old vapers using disposables rose from 0.4 to 54.8% (PR = 129; 95% CI = 28.5–4520), while it rose from 2.1 to 10.0% (PR = 4.73; 95% CI = 2.06–23.6) among 45‐year‐old vapers. However, the overall percentage of people currently using any inhaled nicotine remained stable over time both among all adults (20.0 versus 21.2%; PR = 1.06; 95% CI = 0.92–1.22) and among 18‐year‐olds (30.2 versus 29.7%; PR = 0.99; 95% CI = 0.80–1.22). In 18‐year‐olds, vaping prevalence grew (11.3 versus 17.7%; PR = 1.57; 95% CI = 1.12–2.29), and there was imprecise evidence for a decline in smoking (24.5 versus 19.5%; PR = 0.80; 95% CI = 0.63–1.04). In 45‐year‐olds, there was relatively little change in vaping (PR = 1.08; 95% CI = 0.88–1.33) or smoking prevalence (PR = 1.01; 95% CI = 0.88–1.16). Conclusions: Use of disposable e‐cigarettes in Great Britain grew rapidly between 2021 and 2022, especially among younger adults, but the overall prevalence of inhaled nicotine use was stable over time. Most young adult vapers in Great Britain now use disposable products. [ABSTRACT FROM AUTHOR]

Aim: To measure the cost‐effectiveness of adding text message (TMB), exercise (EB) and abstinent‐contingent financial incentive‐based (CFIB) stop smoking interventions to standard smoking cessation support for pregnant women in England. Design: Modelling cost‐effectiveness outcomes by separately adding three cessation interventions to standard cessation care offered to pregnant women in England. English National Health Service Stop Smoking Services (NHS SSS) statistics from 2019 to 2020 were used for estimating the base quit rate. Intervention effectiveness and cost data for interventions were taken from trial reports. Cost‐effectiveness was derived using the economics of smoking in pregnancy (ESIP) model from a health service and personal social services perspective. Interventions were compared with each other as well as against standard cessation care. Setting English NHS SSS. Participants/cases: A total of 13 799 pregnant women who accessed NHS SSS. Interventions and comparator; comparator: standard stop smoking support comprising behavioural intervention and an offer of nicotine replacement therapy (NRT). Three additive interventions were TMB, EB and CFIB. Measurements Incremental cost‐effectiveness ratios per quality‐adjusted life‐years gained for both mothers and offspring over their life‐times; return on investment (ROI); and cost‐effectiveness acceptability curves (CEACs). Findings The addition of any of the interventions compared with standard care alone was preferred, but only significant for the addition of CFIB, with the CEAC suggesting an at least 90% chance of being favoured to standard care alone. When compared against each other CFIB appeared to yield the largest returns, but this was not significant. The estimated ROI for CFIB was £2 [95% confidence interval (CI) = £1–3] in health‐care savings for every £1 spent by the NHS on the cessation intervention. Conclusions: For a health system which currently provides behavioural support and an offer of nicotine replacement therapy as standard stop smoking support for pregnant women, the greatest economic gains would be provided by operating an abstinent‐contingent financial incentives scheme alongside this. [ABSTRACT FROM AUTHOR]

Background and Aims: Loot boxes are purchasable randomised rewards in video games that share structural and psychological similarities with gambling. Systematic review evidence has established reproducible associations between loot box purchasing and both problem gambling and problem video gaming. We aimed to measure the association between loot box engagement and socioeconomic correlates. Design The study was a cross‐sectional online survey using the recruitment platform, Prolific. Setting: United Kingdom (UK). Participants: A cohort of 16 196 UK adults (18 + years) self‐reporting as video gamers. Measurements Respondents were asked about their game‐related purchasing behaviour (including loot boxes), recent monthly spend on loot boxes and gambling engagement (gambling in any form; gambling online; playing 'social casino' games). A range of demographic variables were simultaneously captured, including age, sex, ethnicity, earnings, employment and educational attainment. Findings Overall, 17.16% of gamers in our cohort purchased loot boxes, with a mean self‐reported monthly spend of £29.12. These loot box purchasers are more likely to gamble (45.97% gamble) than people who make other types of game‐related purchases (on aggregate, 28.13% of non‐loot box purchasers gamble), and even greater still than those who do not make any game related purchases (24.38% gamble P < 0.001). Loot box engagement (as binary yes/no or as monthly spend normalised to earnings) was significantly associated with younger age (P < 0.001 and P < 0.001; respectively, for binary yes/no and monthly spend, adjusted for false discovery rate correction), male sex (P < 0.001 and P = 0.025), non‐university educational attainment (P < 0.001 and P < 0.001) and unemployment (P = 0.003 and P = < 0.001). Lower earners spent a higher proportion of monthly earnings on loot boxes (P < 0.001). Conclusions: The demographic associations of video game loot box engagement (younger age, male sex, non‐university educational attainment and unemployment) mirror those of other addictive and problematic behaviours, including disordered gambling, drug and alcohol misuse. [ABSTRACT FROM AUTHOR]

Background and Aims: The three-question Alcohol Use Disorders Identification Test (AUDIT-C) is frequently used in healthcare for screening and brief advice about levels of alcohol consumption. AUDIT-C scores (0-12) provide feedback as categories of risk rather than estimates of actual alcohol intake, an important metric for behaviour change. The study aimed to (i) develop a continuous metric from the Extended AUDIT-C expressed in United Kingdom (UK) units (8 g pure ethanol), offering equivalent accuracy, and providing a direct estimator of weekly alcohol consumption (EWAC) and (ii) evaluate the EWAC's bias and error using the graduated-frequency (GF) questionnaire as a reference standard of alcohol consumption. Design: Cross-sectional diagnostic study based on a nationally-representative survey. Settings: Community dwelling households in England. Participants: A total of 22 404 household residents aged =16 years reporting drinking alcohol at least occasionally. Measurements: Computer-assisted personal interviews consisting of (i) AUDIT questionnaire with extended response items (the 'Extended AUDIT') and (ii) GF. Primary outcomes were: mean deviation <1 UK unit (metric of bias); root-mean-square deviation <2 UK units (metric of total error) between EWAC and GF. The secondary outcome was the receiver operating characteristic area under the curve for predicting alcohol consumption in excess of 14 and 35 UK units. Findings: EWAC had a positive bias of 0.2 UK units (95% CI = 0.08, 0.4) compared with GF. Deviations were skewed: whereas the mean error was 11 UK units/week [9.5, 11.9], in half of participants the deviation between EWAC and GF was between 0 and 2.1 UK units/week. EWAC predicted consumption in excess of 14 UK units/week with a significantly greater area under the curve (0.918 [0.914, 0.923]) than AUDIT-C (0.870 [0.864, 0.876]) or the full AUDIT (0.854 [0.847, 0.860]). Conclusions: A new estimator of weekly alcohol consumption, which uses answers to the Extended AUDIT-C, meets the targeted bias tolerance. It is superior in accuracy to AUDIT-C and the full 10-item AUDIT when predicting consumption thresholds, making it a reliable complement to the Extended AUDIT-C for health promotion interventions. [ABSTRACT FROM AUTHOR]

Background and Aims: Given the decline in alcohol consumption and rise in technological use among young people, there is a need to investigate whether technology use might influence how young people drink. This study explores how social media use and changes in social media use over time could affect alcohol use among youths. Design The UK Household Longitudinal Study (Understanding Society). Setting: United Kingdom. Participants: Participants aged 10–15 (n = 4093) and 16–19 (n = 2689) from the youth and main survey interviewed in 2011–13, and followed‐up in 2014–16 (aged 10–15 n = 2588, aged 16–19 n = 1057). Measurements Self‐reported social media usage on an average day (no profile/non‐daily/less than an hour/1–3/4+ hours use), drinking frequency (never/one to three times/weekly) and binge drinking frequency (never/one to two/three/more than three times) in the past month. Covariates included sex, age, educational status, household income, urban/rural, number of friends and life satisfaction. Findings Among 10–15‐year‐olds, compared with those who used social media for less than an hour, those with no profile [odds ratio (OR) = 0.41, 95% confidence interval (CI) = 0.25–0.67] and non‐daily users (OR = 0.49, 95% CI = 0.33–0.72) had a lower risk of drinking at least monthly, whereas those with 1–3 hours' use (OR = 1.44, 95% CI = 1.14–1.81) and 4+ hours' use (OR = 2.08, 1.47–2.95) had a greater risk. Among participants aged 16–19, a lower risk of binge drinking three or more times per month was found for those with no profile [relative risk ratios (RRR) = 0.29, 95% CI = 0.17–0.48] and a higher risk for those with 4+ hours' use (RRR = 1.47, 95% CI = 1.03–2.09). Longitudinally, among 10–15‐year‐olds, those who had increased their social media usage versus no change were more likely to have increased their drinking frequency (OR = 1.89, 95% CI = 1.45–2.46). Some social media use at baseline (rather than none) was predictive of increased drink and binge drinking frequency over time among youths and young adults. Conclusions: Heavier social media use was associated with more frequent alcohol consumption among young people in the United Kingdom. [ABSTRACT FROM AUTHOR]

Background and aims: Evidence on the effectiveness of electronic cigarettes (ECs) to facilitate abstinence from smoking is limited. The current study aimed to estimate the relative effectiveness of ECs and smoking cessation medication compared with using no help, accounting for frequency of use of ECs. Design Four consecutive wave‐to‐wave transitions (waves 1–2, 2–3, 3–4 or 4–5) of a longitudinal online survey collected between 2012 and 2017 were analysed. Time between waves ranged between 12 and 17 months. Cigarette smokers at the baseline wave who attempted to quit smoking between waves were included. Setting: United Kingdom Participants: A total of 1155 respondents (aged 18–81, 56.1% male, 64.6% in social grade C2DE, 93.8% white) provided 1580 pairs of observations for the primary analysis. Measurements Primary outcome: abstinence from smoking for at least 1 month at follow‐up; secondary outcome: at least 1 month's abstinence from smoking between baseline and follow‐up. The main predictor was stop smoking aid used (No help, nicotine replacement therapy only, smoking cessation medication only, disposable/cartridge EC, refill/modular EC, combination), adjusted for demographics. Findings: Primary Compared with using no help, the odds of abstinence were increased by daily use of disposable/cartridge ECs (OR = 3.31 (1.32, 8.26), P =.010) and daily use of refill/modular ECs (OR = 5.47 (2.70, 11.11), P <.001). Odds were reduced by non‐daily use of disposable/cartridge ECs (OR = 0.23 (0.08–0.63), P =.005), and by use of disposable/cartridge ECs to quit and no longer using at follow‐up (OR = 0.10 (0.16–0.62), P <.013). Secondary Results were similar to the primary outcome; however, odds of abstinence were also increased by use of smoking cessation medication (OR = 4.15 (1.79, 9.62), P =.001). Conclusions: When used daily, electronic cigarettes appear to facilitate abstinence from smoking when compared with using no help. [ABSTRACT FROM AUTHOR]

Background and Aims: Past research has found that young smokers are more likely to make quit attempts; however, there are conflicting findings regarding age and quit success. This study examined the degree to which smoker age is related to making quit attempts and quit success. Design Ten waves of the International Tobacco Control Policy Cohort survey (ITC‐4C) collected between 2002 and 2014, with nine wave‐to‐wave transitions with predictors at the first wave predicting quit attempts and success by the next wave. Setting: Canada, the United States, the United Kingdom and Australia. Participants: Data from 15 874 smokers categorized into four age groups at baseline (18–24, 25–39, 40–54 and 55+ years). Measurements Age, quit attempts and success (defined as ≥ 30 days abstinence confirmed, if possible, on a third wave for recent attempts). Findings Older smokers were more likely to smoke daily (χ2 = 1557.86, r = 0.136, P < 0.001) than younger smokers. Daily smokers were less likely to report quit attempts (38.1 versus 58.2%) and to achieve 30 days of abstinence (22.9 versus 34.3%) than non‐daily smokers. Older daily smokers were less likely to make quit attempts [0.61, confidence interval (CI) = 0.54–0.70, P < 0.001], even after controlling for indicators of nicotine dependence, country, sex, education, income, relationship status and household composition, than younger smokers. Younger smokers (< 25) were more likely to succeed for at least 30 days of abstinence, but only when compared with those aged 40–54 (OR = 0.83, 95% CI = 0.68–0.99). However, when controlling for heaviness of smoking the age effect disappeared. Significant interactions with age were found between age and intention when predicting quit attempts, and age and heaviness of smoking when predicting quit success. Conclusions: An international cohort study indicates that young smokers are more likely to attempt to quit and appear to have similar levels of success in abstaining from smoking compared with older smokers when controlling for dependence. Quit success in all ages is most predicted by lower levels of nicotine dependence. [ABSTRACT FROM AUTHOR]

The authors comment on consultation that the British government is undergoing via population surveys to reform the UK 2005 Gambling Act. Topics covered include the methodological limitations of the telephone surveys carried out by the Gambling Commission (GC) as well as the British Gambling Prevalence Survey (BGPS) and Health Survey England (HSE), the proneness to error of prevalence surveys, and the ability of the surveys to capture the true nature of the extent of gambling-related harm.