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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]

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]