There is moderate-quality evidence that digital interventions may lower alcohol consumption, with an average reduction of up to three (UK) standard drinks per week compared to control participants. Substantial heterogeneity and risk of performance and publication bias may mean the reduction was lower. Low-quality evidence from fewer studies suggested there may be little or no difference in impact on alcohol consumption between digital and face-to-face interventions.The BCTs of behaviour substitution, problem solving and credible source were associated with the effectiveness of digital interventions to reduce alcohol consumption and warrant further investigation in an experimental context.Reporting of theory use was very limited and often unclear when present. Over half of the interventions made no reference to any theories. Limited reporting of theory use was unrelated to heterogeneity in intervention effectiveness.

Aim To examine changes in smoking, drinking and quitting/reduction behaviour following the COVID‐19 lockdown in England. Design/setting Monthly cross‐sectional surveys representative of the adult population in England, aggregated before (April 2019–February 2020) versus after (April 2020) lockdown. Participants A total of 20 558 adults (≥ 16 years). Measurements The independent variable was the timing of the COVID‐19 lockdown (before versus after March 2020). Dependent variables were: prevalence of smoking and high‐risk drinking, past‐year cessation and quit attempts (among past‐year smokers), past‐year attempts to reduce alcohol consumption (among high‐risk drinkers) and use of evidence‐based (e.g. prescription medication/face‐to‐face behavioural support) and remote support [telephone support/websites/applications (apps)] for smoking cessation and alcohol reduction (among smokers/high‐risk drinkers who made a quit/reduction attempt). Covariates included age, sex, social grade, region and level of nicotine and alcohol dependence (as relevant). Findings The COVID‐19 lockdown was not associated with a significant change in smoking prevalence [17.0% (after) versus 15.9% (before), odds ratio (OR) = 1.09, 95% CI = 0.95–1.24], but was associated with increases in quit attempts [39.6 versus 29.1%, adjusted odds ratio (ORadj) = 1.56, 95% CI = 1.23–1.98], quit success (21.3 versus 13.9%, ORadj = 2.01, 95% CI = 1.22–3.33) and cessation (8.8 versus 4.1%, ORadj = 2.63, 95% CI = 1.69–4.09) among past‐year smokers. Among smokers who tried to quit, there was no significant change in use of evidence‐based support (50.0 versus 51.5%, ORadj = 1.10, 95% CI = 0.72–1.68) but use of remote support increased (10.9 versus 2.7%, ORadj = 3.59, 95% CI = 1.56–8.23). Lockdown was associated with increases in high‐risk drinking (38.3 versus 25.1%, OR = 1.85, CI = 1.67–2.06), but also alcohol reduction attempts by high‐risk drinkers (28.5 versus 15.3%, ORadj = 2.16, 95% CI = 1.77–2.64). Among high‐risk drinkers who made a reduction attempt, use of evidence‐based support decreased (1.2 versus 4.0%, ORadj = 0.23, 95% CI = 0.05–0.97) and there was no significant change in use of remote support (6.9 versus 6.1%, ORadj = 1.32, 95% CI = 0.64–2.75). Conclusions Following the March 2020 COVID‐19 lockdown, smokers and high‐risk drinkers in England were more likely than before lockdown to report trying to quit smoking or reduce alcohol consumption and rates of smoking cessation and use of remote cessation support were higher. However, high‐risk drinking prevalence increased post‐lockdown and use of evidence‐based support for alcohol reduction by high‐risk drinkers decreased with no compensatory increase in use of remote support.

BackgroundMobile phone apps have the potential to reduce excessive alcohol consumption cost-effectively. Although hundreds of alcohol-related apps are available, there is little information about the behavior change techniques (BCTs) they contain, or the extent to which they are based on evidence or theory and how this relates to their popularity and user ratings.ObjectiveOur aim was to assess the proportion of popular alcohol-related apps available in the United Kingdom that focus on alcohol reduction, identify the BCTs they contain, and explore whether BCTs or the mention of theory or evidence is associated with app popularity and user ratings.MethodsWe searched the iTunes and Google Play stores with the terms “alcohol” and “drink”, and the first 800 results were classified into alcohol reduction, entertainment, or blood alcohol content measurement. Of those classified as alcohol reduction, all free apps and the top 10 paid apps were coded for BCTs and for reference to evidence or theory. Measures of popularity and user ratings were extracted.ResultsOf the 800 apps identified, 662 were unique. Of these, 13.7% (91/662) were classified as alcohol reduction (95% CI 11.3-16.6), 53.9% (357/662) entertainment (95% CI 50.1-57.7), 18.9% (125/662) blood alcohol content measurement (95% CI 16.1-22.0) and 13.4% (89/662) other (95% CI 11.1-16.3). The 51 free alcohol reduction apps and the top 10 paid apps contained a mean of 3.6 BCTs (SD 3.4), with approximately 12% (7/61) not including any BCTs. The BCTs used most often were “facilitate self-recording” (54%, 33/61), “provide information on consequences of excessive alcohol use and drinking cessation” (43%, 26/61), “provide feedback on performance” (41%, 25/61), “give options for additional and later support” (25%, 15/61) and “offer/direct towards appropriate written materials” (23%, 14/61). These apps also rarely included any of the 22 BCTs frequently used in other health behavior change interventions (mean 2.46, SD 2.06). Evidence was mentioned by 16.4% of apps, and theory was not mentioned by any app. Multivariable regression showed that apps including advice on environmental restructuring were associated with lower user ratings (Β=-46.61, P=.04, 95% CI -91.77 to -1.45) and that both the techniques of “advise on/facilitate the use of social support” (Β=2549.21, P=.04, 95% CI 96.75-5001.67) and the mention of evidence (Β=1376.74, P=.02, 95%, CI 208.62-2544.86) were associated with the popularity of the app.ConclusionsOnly a minority of alcohol-related apps promoted health while the majority implicitly or explicitly promoted the use of alcohol. Alcohol-related apps that promoted health contained few BCTs and none referred to theory. The mention of evidence was associated with more popular apps, but popularity and user ratings were only weakly associated with the BCT content.

Our aim was to evaluate intervention components of an alcohol reduction app: Drink Less. Excessive drinkers (AUDIT> =8) were recruited to test enhanced versus minimal (reduced functionality) versions of five app modules in a 25 factorial trial. Modules were: Self-monitoring and Feedback, Action Planning, Identity Change, Normative Feedback, and Cognitive Bias Re-training. Outcome measures were: change in weekly alcohol consumption (primary); full AUDIT score, app usage, app usability (secondary). Main effects and two-way interactions were assessed by ANOVA using intention-to-treat. A total of 672 study participants were included. There were no significant main effects of the intervention modules on change in weekly alcohol consumption or AUDIT score. There were two-way interactions between enhanced Normative Feedback and Cognitive Bias Re-training on weekly alcohol consumption (F = 4.68, p = 0.03) and between enhanced Self-monitoring and Feedback and Action Planning on AUDIT score (F = 5.82, p = 0.02). Enhanced Self-monitoring and Feedback was used significantly more often and rated significantly more positively for helpfulness, satisfaction and recommendation to others than the minimal version. To conclude, in an evaluation of the Drink Less smartphone application, the combination of enhanced Normative Feedback and Cognitive Bias Re-training and enhanced Self-monitoring and Feedback and Action Planning yielded improvements in alcohol-related outcomes after 4-weeks.

BackgroundInterventions delivered by smartphone apps have the potential to help drinkers reduce their consumption of alcohol. To optimize engagement and reduce the high rates of attrition associated with the use of digital interventions, it is necessary to ensure that an app’s design and functionality is appropriate for its intended purposes and target population.AimsTo understand the usability of an app to help people reduce their alcohol consumption.MethodThe app, Drink Less, contains a core module focusing on goal setting, supplemented by five additional modules: self-monitoring and feedback, identity change, cognitive bias re-training, action planning, and social comparison. Two studies were conducted, a “think aloud” study performed with people using the app for the first time and a semistructured interview study performed after users had had access to the app for at least 2 weeks. A thematic analysis of the “think aloud” and interview transcripts was conducted by one coder and verified by a second.ResultsTwenty-four participants, half of whom were women and half from disadvantaged groups, took part in the two studies. Three main themes identified in the data were “Feeling lost and unsure of what to do next,” “Make the app easy to use,” and “Make the app beneficial and rewarding to use.” These themes reflected participants’ need for (i) guidance, particularly when first using the app or when entering data; (ii) the data entry process to be simple and the navigation intuitive; (iii) neither the amount of text nor range of options to be overwhelming; (iv) the app to reward them for effort and progress; and (v) it to be clear how the app could help alcohol reduction goals be reached.ConclusionFirst-time and experienced users want an alcohol reduction app to be easy, rewarding, and beneficial to use. An easy-to-use app would reduce user burden, offer ongoing help, and be esthetically pleasing. A rewarding and beneficial app would provide positive reinforcement, give feedback about progress, and demonstrate credibility. Users need help when first using the app, and they need a compelling reason to continue using it.