Brief interventions for smoking and alcohol associated with the COVID-19 pandemic: a population survey in England.

BACKGROUND: Following the onset of the COVID-19 pandemic, in March 2020 health care delivery underwent considerable changes. It is unclear how this may have affected the delivery of Brief Interventions (BIs) for smoking and alcohol. We examined the impact of the COVID-19 pandemic on the receipt of BIs for smoking and alcohol in primary care in England and whether certain priority groups (e.g., less advantaged socioeconomic positions, or a history of a mental health condition) were differentially affected. METHODS: We used nationally representative data from a monthly cross-sectional survey in England between 03/2014 and 06/2022. Monthly trends in the receipt of BIs for smoking and alcohol were examined using generalised additive models among adults who smoked in the past-year (weighted N = 31,390) and those using alcohol at increasing and higher risk levels (AUDIT score 38, weighted N = 22,386), respectively. Interactions were tested between social grade and the change in slope after the onset of the COVID-19 pandemic, and results reported stratified by social grade. Further logistic regression models assessed whether changes in the of receipt of BIs for smoking and alcohol, respectively, from 12/2016 to 01/2017 and 10/2020 to 06/2022 (or 03/2022 in the case of BIs for alcohol), depended on history of a mental health condition. RESULTS: The receipt of smoking BIs declined from an average prevalence of 31.8% (95%CI 29.4-35.0) pre-March 2020 to 24.4% (95%CI 23.5-25.4) post-March 2020. The best-fitting model found that after March 2020 there was a 12-month decline before stabilising by June 2022 in social grade ABC1 at a lower level (~ 20%) and rebounding among social grade C2DE (~ 27%). Receipt of BIs for alcohol was low (overall: 4.1%, 95%CI 3.9-4.4) and the prevalence was similar pre- and post-March 2020. CONCLUSIONS: The receipt of BIs for smoking declined following March 2020 but rebounded among priority socioeconomic groups of people who smoked. BIs for alcohol among those who use alcohol at increasing and higher risk levels were low and there was no appreciable change over time. Maintaining higher BI delivery among socioeconomic and mental health priority groups of smokers and increasing and higher risk alcohol users is important to support reductions in smoking and alcohol related inequalities.

Evaluating the Acceptability of the Drink Less App and the National Health Service Alcohol Advice Web Page: Qualitative Interview Process Evaluation.

BACKGROUND: The extent to which interventions are perceived as acceptable to users impacts engagement and efficacy. OBJECTIVE: In this study, we evaluated the acceptability of (1) the smartphone app Drink Less (intervention) and (2) the National Health Service (NHS) alcohol advice web page (usual digital care and comparator) among adult drinkers in the United Kingdom participating in a randomized controlled trial evaluating the effectiveness of the Drink Less app. METHODS: A subsample of 26 increasing- and higher-risk drinkers (Alcohol Use Disorders Identification Test score≥8) assigned to the intervention group (Drink Less; n=14, 54%; female: n=10, 71%; age: 22-72 years; White: n=9, 64%) or usual digital care group (NHS alcohol advice web page; n=12, 46%; female: n=5, 42%; age: 23-68 years: White: n=9, 75%) took part in semistructured interviews. The interview questions were mapped on to the 7 facets of acceptability according to the Theoretical Framework of Acceptability: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs, and self-efficacy. Alongside these constructs, we also included a question on perceived personal relevance, which previous research has linked to acceptability and engagement. Framework and thematic analysis of data was undertaken. RESULTS: The Drink Less app was perceived as being ethical, easy, user-friendly, and effective for the period the app was used. Participants reported particularly liking the tracking and feedback sections of the app, which they reported increased personal relevance and which resulted in positive affect when achieving their goals. They reported no opportunity cost. Factors such as negative affect when not meeting goals and boredom led to disengagement in the longer term for some participants. The NHS alcohol advice web page was rated as being easy and user-friendly with no opportunity costs. However, the information presented was not perceived as being personally relevant or effective in changing drinking behavior. Most participants reported neutral or negative affect, most participants thought the alcohol advice web page was accessible, and some participants reported ethical concerns around the availability of suggested resources. Some participants reported that it had acted as a starting point or a signpost to other resources. Participants in both groups discussed motivation to change and contextual factors such as COVID-19 lockdowns, which influenced their perceived self-efficacy regardless of their assigned intervention. CONCLUSIONS: Drink Less appears to be an acceptable digital intervention among the recruited sample. The NHS alcohol advice web page was generally considered unacceptable as a stand-alone intervention among the recruited sample, although it may signpost and help people access other resources and interventions.

Bot or Not? Detecting and Managing Participant Deception When Conducting Digital Research Remotely: Case Study of a Randomized Controlled Trial.

BACKGROUND: Evaluating digital interventions using remote methods enables the recruitment of large numbers of participants relatively conveniently and cheaply compared with in-person methods. However, conducting research remotely based on participant self-report with little verification is open to automated "bots" and participant deception. OBJECTIVE: This paper uses a case study of a remotely conducted trial of an alcohol reduction app to highlight and discuss (1) the issues with participant deception affecting remote research trials with financial compensation; and (2) the importance of rigorous data management to detect and address these issues. METHODS: We recruited participants on the internet from July 2020 to March 2022 for a randomized controlled trial (n=5602) evaluating the effectiveness of an alcohol reduction app, Drink Less. Follow-up occurred at 3 time points, with financial compensation offered (up to £36 [US $39.23]). Address authentication and telephone verification were used to detect 2 kinds of deception: "bots," that is, automated responses generated in clusters; and manual participant deception, that is, participants providing false information. RESULTS: Of the 1142 participants who enrolled in the first 2 months of recruitment, 75.6% (n=863) of them were identified as bots during data screening. As a result, a CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) was added, and after this, no more bots were identified. Manual participant deception occurred throughout the study. Of the 5956 participants (excluding bots) who enrolled in the study, 298 (5%) were identified as false participants. The extent of this decreased from 110 in November 2020, to a negligible level by February 2022 including a number of months with 0. The decline occurred after we added further screening questions such as attention checks, removed the prominence of financial compensation from social media advertising, and added an additional requirement to provide a mobile phone number for identity verification. CONCLUSIONS: Data management protocols are necessary to detect automated bots and manual participant deception in remotely conducted trials. Bots and manual deception can be minimized by adding a CAPTCHA, attention checks, a requirement to provide a phone number for identity verification, and not prominently advertising financial compensation on social media. TRIAL REGISTRATION: ISRCTN Number ISRCTN64052601; https://doi.org/10.1186/ISRCTN64052601.

Potential Explanations for Conflicting Findings on Abrupt Versus Gradual Smoking Cessation: A Population Study in England.

INTRODUCTION: Observational and trial evidence conflict on the efficacy of two contrasting behavioral approaches to quitting smoking-gradual and abrupt. Observational data suggest an abrupt approach to quitting is superior to a gradual approach, whilst trials show no difference. One potential explanation is self-selection in observational data, whereby people can choose their quit approach, and those who find it harder to quit may be more likely to choose a gradual quit approach. This study aims to investigate potential explanations for these conflicting findings. AIMS AND METHODS: This study aims to investigate potential explanations for these conflicting findings. We used observational data from a nationally representative sample of adults in England from November 2006 to February 2020 who reported smoking and had made at least one quit attempt in the past year (n = 21 542). We used logistic regression models to assess the association between abrupt versus gradual quit attempts and quit success, adjusting for sociodemographic, smoking, and quit attempt characteristics. FINDINGS: Abrupt, versus gradual, attempts were associated with improved quit success in an unadjusted model (odds ratio = 2.02, 95% CI = 1.86 to 2.19). This association remained after adjusting for a broad range of relevant confounders (odds ratio = 1.75, 95% CI = 1.59 to 1.93). CONCLUSIONS: Among a representative sample of adults who had smoked and made a quit attempt in the past year, there was evidence of an association between abrupt attempts and quit success before and after adjusting for relevant confounders. This suggests that the differences in quit success seen between abrupt and gradual quit attempt types are not completely driven by self-selection in observational data. IMPLICATIONS: We investigated explanations for conflicting findings on the efficacy of gradual versus abrupt approaches to quitting smoking between trial and observational data. Despite adjusting observational data for sociodemographic, smoking, and quit attempt characteristics, an association between abrupt quitting and quit success remained. Therefore, differences in quit success were not completely driven by the self-selection of a gradual approach by people who found it especially difficult to quit or differences in the use of quitting aids. However, characteristics adjusted for were limited by the data available, and future research should continue to investigate the difference in findings across study types to inform cessation support.

Exploring changes in temporary abstinence in increasing and higher risk drinkers in England and Dry January participation in users of the Try Dry app in the UK between 2020 and 2021.

BACKGROUND: We looked at changes in the prevalence of increasing and higher risk drinkers reporting a reduction attempt motivated by temporary abstinence and changes in prevalence of use of the official app accompanying Dry January between 2020 vs 2021, following the onset of the COVID-19 pandemic. We also explored potential shifts in the sociodemographic composition of both groups. METHODS: We analysed data from: i) 1863 increasing and higher risk drinkers (defined as ≥ 8 on the AUDIT) responding to a nationally representative survey of adults in England in January and February 2020 and 2021, and ii) 104,598 users of the 'Try Dry' app, the official aid to those participating in Dry January 2020 and 2021 in the UK. We used logistic regression to examine shifts in the prevalence of increasing and higher risk drinkers reporting a reduction attempt motivated by temporary abstinence and explored whether there were shifts in the characteristics of this group in terms of AUDIT score, number of last year reduction attempts, smoking status, living alone, living with children, reducing alcohol consumption due to future health motives, age, sex, and occupational social grade between 2020 and 2021. We used t-tests and chi-squared tests to compare the prevalence of users of the 'Try Dry' app in 2020 and 2021 and examine whether the two groups differed in terms of age and sex. RESULTS: The proportion of increasing and higher risk drinkers reporting a reduction attempt motivated by temporary abstinence increased from 4% in 2020 to 8% in 2021 (OR = 2.07, 95% CI = 1.38-3.11, p < .001) with no changes detected in sociodemographic composition. The number of Try Dry app users in 2021 increased by 34.8% relative to 2020. App users in 2021 were two years older on average [p < .001, d = .02], with a 2% increase in the proportion of female app users [p < .001, vs. < .01]. CONCLUSIONS: Higher participation in Dry January 2021 relative to 2020 indicates increased engagement with a period of temporary abstinence following the COVID-19 related lockdowns in England and the UK, which is positive in the wider context of increasing alcohol consumption throughout the pandemic.

The Effect of the First UK COVID-19 Lockdown on Users of the Drink Less App: Interrupted Time Series Analysis of Sociodemographic Characteristics, Engagement, and Alcohol Reduction.

BACKGROUND: The first UK COVID-19 lockdown had a polarizing impact on drinking behavior and may have impacted engagement with digital interventions to reduce alcohol consumption. OBJECTIVE: We examined the effect of lockdown on engagement, alcohol reduction, and the sociodemographic characteristics of users of the popular and widely available alcohol reduction app Drink Less. METHODS: This was a natural experiment. The study period spanned 468 days between March 24, 2019, and July 3, 2020, with the introduction of UK lockdown measures beginning on March 24, 2020. Users were 18 years or older, based in the United Kingdom, and interested in drinking less. Interrupted time series analyses using generalized additive mixed models (GAMMs) were conducted for each outcome variable (ie, sociodemographic characteristics, app downloads and engagement levels, alcohol consumption, and extent of alcohol reduction) for existing (downloaded the app prelockdown) and new (downloaded the app during the lockdown) users of the app. RESULTS: Among existing users of the Drink Less app, there were increases in the time spent on the app per day (B=0.01, P=.01), mean units of alcohol recorded per day (B>0.00 P=.02), and mean heavy drinking (>6 units) days (B>0.00, P=.02) during the lockdown. Previous declines in new app downloads plateaued during the lockdown (incidence rate ratio [IRR]=1.00, P=.18). Among new app users, there was an increase in the proportion of female users (B>0.00, P=.04) and those at risk of alcohol dependence (B>0.00, P=.01) and a decrease in the proportion of nonmanual workers (B>-0.00, P=.04). Among new app users, there were step increases in the mean number of alcohol units per day (B=20.12, P=.03), heavy-drinking days (B=1.38, P=.01), and the number of days the app was used (B=2.05, P=.02), alongside a step decrease in the percentage of available screens viewed (B=-0.03, P=.04), indicating users were using less of the intervention components within the app. CONCLUSIONS: Following the first UK lockdown, there was evidence of increases in engagement and alcohol consumption among new and existing users of the Drink Less app.

The impact of celebrity influence and national media coverage on users of an alcohol reduction app: a natural experiment.

BACKGROUND: Smartphone apps are increasingly used for health-related behaviour change and people discover apps through different sources. However, it is unclear whether users differ by mode of app discovery. Drink Less is an alcohol reduction app that received national media coverage in the UK caused by celebrity influence (a male TV and radio national broadcaster, aged 51). Our aim was to compare users who discovered the app before and after this coverage. METHODS: A natural experiment assessing the impact of media coverage of Drink Less on users' socio-demographic and drinking characteristics, app engagement levels, and extent of alcohol reduction. The study period was from 17th May 2017 to 23rd January 2019, with media coverage starting on 21st August 2018. Users were 18 years or over, based in the UK and interested in drinking less. Interrupted time series analyses using Generalised Additive Mixed Models were conducted for each outcome variable aggregated at the weekly level. RESULTS: In 66 weeks prior to the media coverage, 8617 users downloaded the app and 18,959 in 23 weeks afterwards. There was a significant step-level increase in users' mean age (B = 8.17, p < .001) and a decrease in the percentage of female users (B = -27.71, p < .001), though these effects dissipated non-linearly over time. No effect of media coverage was detected on employment type or on the percentage of at-risk drinkers, though the mean Alcohol Use Disorders Identification Test score was lower after the media coverage (B = -1.43, p = .031). There was a step-level increase in app engagement - number of sessions (B = 3.45, p = .038) and number of days used (B = 2.30, p = .005) - which continued to increase over time following quadratic trends. CONCLUSIONS: Celebrity influence leading to national media coverage in the UK of the Drink Less app was associated with more people downloading the app who were male, older and engaged with the app; and did not appear to impact employment inequality.

Understanding the Association Between Spontaneous Quit Attempts and Improved Smoking Cessation Success Rates: A Population Survey in England With 6-Month Follow-up.

INTRODUCTION: Almost half of smoking quit attempts are "spontaneous" (initiated as soon as the decision to quit has been made) and are associated with increased success rates. This study aimed to assess to what extent other factors may account for this association. METHODS: Data were used from respondents to a survey representative of the adult population in England from 2006 to 2016. We included 2018 respondents who were current smokers at baseline and had attempted to quit between baseline and 6-month follow-up. Logistic regression models assessed the association between quit success and spontaneous quit attempts while adjusting for smoking, sociodemographic, and quit attempt characteristics. RESULTS: Spontaneous quit attempts were associated with greater odds of quit success (OR = 1.31, 95% CI = 1.07 to 1.60) but the association was not significant in the fully adjusted model (ORadj = 1.19, 95% CI = 0.95 to 1.49). In this adjusted model, those who attempted to quit without cutting down first (ORadj = 3.08, 95% CI = 2.46 to 3.88) and were male (ORadj = 1.44, 95% CI = 1.16 to 1.80) had greater odds of success; although a greater number of attempts in the past 6 months, stronger urges to smoke (strong vs. none), higher daily cigarette consumption, and lower social grade (E vs. AB) were associated with lower odds of success (ORadj range = 0.32-0.98, p < .030). Quit attempts made without cutting down first were correlated with spontaneous quit attempts (r = .150, p < .001) and appeared to account for the diminished association between spontaneous quitting and success (ORadj = 1.18, 95% CI = 0.96 to 1.46). CONCLUSIONS: The increased success rate of spontaneous quit attempts appears to be because spontaneous quit attempts are more likely to be made without cutting down first. IMPLICATIONS: The apparent benefit of spontaneous over planned quit attempts may be attributable to the former being more likely to involve quitting without cutting down first (ie, abrupt cessation) than cutting down first (ie, gradual cessation) and so this may be a more useful target for advice to improve the chances of successful quitting.

Trends in and Correlates of Use of Roll-Your-Own Cigarettes: A Population Study in England 2008-2017.

INTRODUCTION: Understanding the use of cheaper roll-your-own (RYO) cigarettes may have implications for tobacco tax policy. We examined trends in RYO cigarette use in England between 2008 and 2017, and characterized users' sociodemographic and smoking profiles. METHODS: We used data from 211 469 respondents to a survey representative of the adult (≥16 years) population. In current smokers across the entire study period (n = 43 389), we assessed multivariable associations between cigarette type (RYO or factory-made [FM]) and sociodemographic and smoking characteristics. Among current smokers in 2008 and 2017 (n = 7685), we tested interactions between year and cigarette type to assess the stability of each characteristic. RESULTS: Between 2008 and 2017, FM cigarette use declined from 15.3% to 9.2% whereas RYO use increased from 6.7% to 8.1%. Greater odds of RYO use were observed among younger, male smokers from lower social grades, who were more addicted and used electronic cigarettes (ORrange = 1.28-1.86, p < .001). Lower odds of RYO use were observed among nondaily smokers, those with high motivation to stop, and higher spending on smoking (ORrange = 0.46-0.89, p ≤ .001). The RYO smoker profile was relatively stable between 2008 and 2017. However, compared with FM use, RYO use increased in younger (p < .001) and female (p = .019) smokers, and there was a relatively smaller decline in the proportion cutting down or trying to quit (p = .004). CONCLUSION: In England, RYO use increased when overall smoking prevalence and FM use decreased. The profile of RYO smokers remained relatively stable, with users typically younger, male, more addicted, deprived, spending less on smoking, and less inclined to quit than FM smokers. IMPLICATIONS: This population-based study provides novel insight into recent trends in RYO use in England, providing an up-to-date understanding of the profile of RYO smokers. Without the consistent application of tax across the range of combustible products, smokers who are more dependent are able to capitalize on the lower cost of RYO in order to continue smoking, undermining the potential benefit of taxation on cessation.

Engagement With a Behavior Change App for Alcohol Reduction: Data Visualization for Longitudinal Observational Study.

BACKGROUND: Behavior change apps can develop iteratively, where the app evolves into a complex, dynamic, or personalized intervention through cycles of research, development, and implementation. Understanding how existing users engage with an app (eg, frequency, amount, depth, and duration of use) can help guide further incremental improvements. We aim to explore how simple visualizations can provide a good understanding of temporal patterns of engagement, as usage data are often longitudinal and rich. OBJECTIVE: This study aims to visualize behavioral engagement with Drink Less, a behavior change app to help reduce hazardous and harmful alcohol consumption in the general adult population of the United Kingdom. METHODS: We explored behavioral engagement among 19,233 existing users of Drink Less. Users were included in the sample if they were from the United Kingdom; were 18 years or older; were interested in reducing their alcohol consumption; had a baseline Alcohol Use Disorders Identification Test score of 8 or above, indicative of excessive drinking; and had downloaded the app between May 17, 2017, and January 22, 2019 (615 days). Measures of when sessions begin, length of sessions, time to disengagement, and patterns of use were visualized with heat maps, timeline plots, k-modes clustering analyses, and Kaplan-Meier plots. RESULTS: The daily 11 AM notification is strongly associated with a change in engagement in the following hour; reduction in behavioral engagement over time, with 50.00% (9617/19,233) of users disengaging (defined as no use for 7 or more consecutive days) 22 days after download; identification of 3 distinct trajectories of use, namely engagers (4651/19,233, 24.18% of users), slow disengagers (3679/19,233, 19.13% of users), and fast disengagers (10,903/19,233, 56.68% of users); and limited depth of engagement with 85.076% (7,095,348/8,340,005) of screen views occurring within the Self-monitoring and Feedback module. In addition, a peak of both frequency and amount of time spent per session was observed in the evenings. CONCLUSIONS: Visualizations play an important role in understanding engagement with behavior change apps. Here, we discuss how simple visualizations helped identify important patterns of engagement with Drink Less. Our visualizations of behavioral engagement suggest that the daily notification substantially impacts engagement. Furthermore, the visualizations suggest that a fixed notification policy can be effective for maintaining engagement for some users but ineffective for others. We conclude that optimizing the notification policy to target both effectiveness and engagement is a worthwhile investment. Our future goal is to both understand the causal effect of the notification on engagement and further optimize the notification policy within Drink Less by tailoring to contextual circumstances of individuals over time. Such tailoring will be informed from the findings of our micro-randomized trial (MRT), and these visualizations were useful in both gaining a better understanding of engagement and designing the MRT.

Investigating Characteristics of Quality Peer Mentors With Spinal Cord Injury.

OBJECTIVE: To identify characteristics (1) of high- and low-quality spinal cord injury (SCI) peer mentors; (2) that should be used to match SCI peer mentors and mentees. DESIGN: The study was conducted in partnership with three Canadian provincial SCI organizations using an integrated knowledge translation approach. The Delphi exercise was completed in three rounds. In Round 1, people with SCI completed a thought-listing exercise to identify characteristics of high- and low-quality peer mentors and for matching. In Rounds 2 and 3, people with SCI and community organization staff rated characteristics from the previous round on an 11-point scale. After the final round, the remaining characteristics were thematically analyzed. SETTING: Community-based peer mentorship programs in three Canadian provinces. PARTICIPANTS: People with SCI and SCI community organization staff (Round 1, n=45; Round 2, n=27; Round 3, n=25). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Consensus-based list of characteristics. RESULTS: Participants reached consensus on 215 characteristics of quality peer mentors and 11 characteristics for peer mentor-mentee matching (ICC=0.96). A consensus-based characterization of high- and low-quality peer mentorship was created and included six overarching themes: competencies, personality characteristics, emotional state, mentor outlook, reason for mentoring, and role model. CONCLUSION: A consensus-based characterization of quality peer mentorship was co-developed with input from over 50 members of the SCI community. Findings highlight that peers have both interpersonal and intrapersonal characteristics that contribute to quality mentorship. The findings highlighted the importance of matching mentors on lived experience and shared interests. Findings will inform future research and SCI peer mentorship programs.

Assessing the Psychometric Properties of the Digital Behavior Change Intervention Engagement Scale in Users of an App for Reducing Alcohol Consumption: Evaluation Study.

BACKGROUND: The level and type of engagement with digital behavior change interventions (DBCIs) are likely to influence their effectiveness, but validated self-report measures of engagement are lacking. The DBCI Engagement Scale was designed to assess behavioral (ie, amount, depth of use) and experiential (ie, attention, interest, enjoyment) dimensions of engagement. OBJECTIVE: We aimed to assess the psychometric properties of the DBCI Engagement Scale in users of a smartphone app for reducing alcohol consumption. METHODS: Participants (N=147) were UK-based, adult, excessive drinkers recruited via an online research platform. Participants downloaded the Drink Less app and completed the scale immediately after their first login in exchange for a financial reward. Criterion variables included the objectively recorded amount of use, depth of use, and subsequent login. Five types of validity (ie, construct, criterion, predictive, incremental, divergent) were examined in exploratory factor, correlational, and regression analyses. The Cronbach alpha was calculated to assess the scale's internal reliability. Covariates included motivation to reduce alcohol consumption. RESULTS: Responses on the DBCI Engagement Scale could be characterized in terms of two largely independent subscales related to experience and behavior. The experiential and behavioral subscales showed high (α=.78) and moderate (α=.45) internal reliability, respectively. Total scale scores predicted future behavioral engagement (ie, subsequent login) with and without adjusting for users' motivation to reduce alcohol consumption (adjusted odds ratio [ORadj]=1.14; 95% CI 1.03-1.27; P=.01), which was driven by the experiential (ORadj=1.19; 95% CI 1.05-1.34; P=.006) but not the behavioral subscale. CONCLUSIONS: The DBCI Engagement Scale assesses behavioral and experiential aspects of engagement. The behavioral subscale may not be a valid indicator of behavioral engagement. The experiential subscale can predict subsequent behavioral engagement with an app for reducing alcohol consumption. Further refinements and validation of the scale in larger samples and across different DBCIs are needed.

Behavior Change Techniques Used in Digital Behavior Change Interventions to Reduce Excessive Alcohol Consumption: A Meta-regression.

Background: Digital behavior change interventions (DBCIs) appear to reduce alcohol consumption, but greater understanding is needed of their mechanisms of action. Purpose: To describe the behavior change techniques (BCTs) used in DBCIs and examine whether individual BCTs, the inclusion of more BCTs or more Control Theory congruent BCTs is associated with increased effectiveness. Methods: Forty-one randomized control trials were extracted from a Cochrane review of alcohol reduction DBCIs and coded for up to 93 BCTs using an established and reliable method. Random effects unadjusted and adjusted meta-regression models were performed to assess associations between BCTs and intervention effectiveness. Results: Interventions used a mean of 9.1 BCTs (range 1-22), 23 different BCTs were used in four or more trials. Trials that used "Behavior substitution" (-95.112 grams per week [gpw], 95% CI: -162.90, -27.34), "Problem solving" (-45.92 gpw, 95% CI: -90.97, -0.87) and "Credible source" (-32.09 gpw, 95% CI: -60.64, -3.55) were significantly associated with greater alcohol reduction than trials without these BCTs. The "Behavior substitution" result should be treated as preliminary because it was reported in only four trials, three of which were conducted by the same research group. "Feedback" was used in 98% of trials (n = 41); other Control Theory congruent BCTs were used less frequently: for example, "Goal setting" 43% (n = 18) and "Self-monitoring" 29%, (n = 12). Conclusions: "Behavior substitution," "Problem solving," and "Credible source" were associated with greater alcohol reduction. Many BCTs were used infrequently in DBCIs, including BCTs with evidence of effectiveness in other domains, such as "Self-monitoring" and "Goal setting."

Reported Theory Use by Digital Interventions for Hazardous and Harmful Alcohol Consumption, and Association With Effectiveness: Meta-Regression.

BACKGROUND: Applying theory to the design and evaluation of interventions is likely to increase effectiveness and improve the evidence base from which future interventions are developed, though few interventions report this. OBJECTIVE: The aim of this paper was to assess how digital interventions to reduce hazardous and harmful alcohol consumption report the use of theory in their development and evaluation, and whether reporting of theory use is associated with intervention effectiveness. METHODS: Randomized controlled trials were extracted from a Cochrane review on digital interventions for reducing hazardous and harmful alcohol consumption. Reporting of theory use within these digital interventions was investigated using the theory coding scheme (TCS). Reported theory use was analyzed by frequency counts and descriptive statistics. Associations were analyzed with meta-regression models. RESULTS: Of 41 trials involving 42 comparisons, half did not mention theory (50% [21/42]), and only 38% (16/42) used theory to select or develop the intervention techniques. Significant heterogeneity existed between studies in the effect of interventions on alcohol reduction (I2=77.6%, P<.001). No significant associations were detected between reporting of theory use and intervention effectiveness in unadjusted models, though the meta-regression was underpowered to detect modest associations. CONCLUSIONS: Digital interventions offer a unique opportunity to refine and develop new dynamic, temporally sensitive theories, yet none of the studies reported refining or developing theory. Clearer selection, application, and reporting of theory use is needed to accurately assess how useful theory is in this field and to advance the field of behavior change theories.

Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations.

BACKGROUND: Excessive alcohol use contributes significantly to physical and psychological illness, injury and death, and a wide array of social harm in all age groups. A proven strategy for reducing excessive alcohol consumption levels is to offer a brief conversation-based intervention in primary care settings, but more recent technological innovations have enabled people to interact directly via computer, mobile device or smartphone with digital interventions designed to address problem alcohol consumption. OBJECTIVES: To assess the effectiveness and cost-effectiveness of digital interventions for reducing hazardous and harmful alcohol consumption, alcohol-related problems, or both, in people living in the community, specifically: (i) Are digital interventions more effective and cost-effective than no intervention (or minimal input) controls? (ii) Are digital interventions at least equally effective as face-to-face brief alcohol interventions? (iii) What are the effective component behaviour change techniques (BCTs) of such interventions and their mechanisms of action? (iv) What theories or models have been used in the development and/or evaluation of the intervention? Secondary objectives were (i) to assess whether outcomes differ between trials where the digital intervention targets participants attending health, social care, education or other community-based settings and those where it is offered remotely via the internet or mobile phone platforms; (ii) to specify interventions according to their mode of delivery (e.g. functionality features) and assess the impact of mode of delivery on outcomes. SEARCH METHODS: We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, ERIC, HTA and Web of Knowledge databases; ClinicalTrials.com and WHO ICTRP trials registers and relevant websites to April 2017. We also checked the reference lists of included trials and relevant systematic reviews. SELECTION CRITERIA: We included randomised controlled trials (RCTs) that evaluated the effectiveness of digital interventions compared with no intervention or with face-to-face interventions for reducing hazardous or harmful alcohol consumption in people living in the community and reported a measure of alcohol consumption. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by The Cochrane Collaboration. MAIN RESULTS: We included 57 studies which randomised a total of 34,390 participants. The main sources of bias were from attrition and participant blinding (36% and 21% of studies respectively, high risk of bias). Forty one studies (42 comparisons, 19,241 participants) provided data for the primary meta-analysis, which demonstrated that participants using a digital intervention drank approximately 23 g alcohol weekly (95% CI 15 to 30) (about 3 UK units) less than participants who received no or minimal interventions at end of follow up (moderate-quality evidence).Fifteen studies (16 comparisons, 10,862 participants) demonstrated that participants who engaged with digital interventions had less than one drinking day per month fewer than no intervention controls (moderate-quality evidence), 15 studies (3587 participants) showed about one binge drinking session less per month in the intervention group compared to no intervention controls (moderate-quality evidence), and in 15 studies (9791 participants) intervention participants drank one unit per occasion less than no intervention control participants (moderate-quality evidence).Only five small studies (390 participants) compared digital and face-to-face interventions. There was no difference in alcohol consumption at end of follow up (MD 0.52 g/week, 95% CI -24.59 to 25.63; low-quality evidence). Thus, digital alcohol interventions produced broadly similar outcomes in these studies. No studies reported whether any adverse effects resulted from the interventions.A median of nine BCTs were used in experimental arms (range = 1 to 22). 'B' is an estimate of effect (MD in quantity of drinking, expressed in g/week) per unit increase in the BCT, and is a way to report whether individual BCTs are linked to the effect of the intervention. The BCTs of goal setting (B -43.94, 95% CI -78.59 to -9.30), problem solving (B -48.03, 95% CI -77.79 to -18.27), information about antecedents (B -74.20, 95% CI -117.72 to -30.68), behaviour substitution (B -123.71, 95% CI -184.63 to -62.80) and credible source (B -39.89, 95% CI -72.66 to -7.11) were significantly associated with reduced alcohol consumption in unadjusted models. In a multivariable model that included BCTs with B > 23 in the unadjusted model, the BCTs of behaviour substitution (B -95.12, 95% CI -162.90 to -27.34), problem solving (B -45.92, 95% CI -90.97 to -0.87), and credible source (B -32.09, 95% CI -60.64 to -3.55) were associated with reduced alcohol consumption.The most frequently mentioned theories or models in the included studies were Motivational Interviewing Theory (7/20), Transtheoretical Model (6/20) and Social Norms Theory (6/20). Over half of the interventions (n = 21, 51%) made no mention of theory. Only two studies used theory to select participants or tailor the intervention. There was no evidence of an association between reporting theory use and intervention effectiveness. AUTHORS' CONCLUSIONS: 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.

Evaluating the effectiveness of a smartphone app to reduce excessive alcohol consumption: protocol for a factorial randomised control trial.

BACKGROUND: Excessive alcohol consumption is a leading cause of death and morbidity worldwide and interventions to help people reduce their consumption are needed. Interventions delivered by smartphone apps have the potential to help harmful and hazardous drinkers reduce their consumption of alcohol. However, there has been little evaluation of the effectiveness of existing smartphone interventions. A systematic review, amongst other methodologies, identified promising modular content that could be delivered by an app: self-monitoring and feedback; action planning; normative feedback; cognitive bias re-training; and identity change. This protocol reports a factorial randomised controlled trial to assess the comparative potential of these five intervention modules to reduce excessive alcohol consumption. METHODS: A between-subject factorial randomised controlled trial. Hazardous and harmful drinkers aged 18 or over who are making a serious attempt to reduce their drinking will be randomised to one of 32 (2(5)) experimental conditions after downloading the 'Drink Less' app. Participants complete baseline measures on downloading the app and are contacted after 1-month with a follow-up questionnaire. The primary outcome measure is change in past week consumption of alcohol. Secondary outcome measures are change in AUDIT score, app usage data and usability ratings for the app. A factorial between-subjects ANOVA will be conducted to assess main and interactive effects of the five intervention modules for the primary and secondary outcome measures. DISCUSSION: This study will establish the extent to which the five intervention modules offered in this app can help reduce hazardous and harmful drinking. This is the first step in optimising and understanding what component parts of an app could help to reduce excessive alcohol consumption. The findings from this study will be used to inform the content of a future integrated treatment app and evaluated against a minimal control in a definitive randomised control trial with long-term outcomes. TRIAL REGISTRATION: ISRCTN40104069 Date of registration: 10/2/2016.

Behavior change techniques in popular alcohol reduction apps: content analysis.

BACKGROUND: Mobile 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. OBJECTIVE: Our 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. METHODS: We 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. RESULTS: Of 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. CONCLUSIONS: Only 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.

Prevalence and characteristics of co-occurrence of smoking and increasing-and-higher-risk drinking: A population survey in England.

BACKGROUND: Smoking and drinking alcohol both significantly contribute to mortality and morbidity, and there is a need to characterise the sociodemographic and health-related characteristics (e.g. mental distress) of people who do both in order to target resources. This study reports the prevalence and characteristics of adults in the general population in England who both drink alcohol at increasing-and-higher-risk levels and smoke. METHODS: We used cross-sectional data from a monthly, nationally representative survey of adults in England (n = 37,258; April 2020-March 2022). Weighted data were used to report prevalence and unweighted data were used to report descriptive statistics for sociodemographic and health-related characteristics. RESULTS: The prevalence of both smoking and increasing-and-higher-risk drinking was 4.6% (95% CI = 4.4-4.9; n = 1,574). They smoked a mean of 10.4 (SD = 8.86) cigarettes per day and had a mean AUDIT score of 12.8 (SD = 5.18). Nearly half (48.2%, n = 751) were trying to cut down on their smoking and 28.0% (n = 441) on their drinking. A quarter (25.3%, n = 397) had received General Practitioner advice on smoking while 8.7% (n = 76) had received advice on their drinking. Nearly half (48.6%, n = 745) reported experiencing psychological distress in the past month and 44.6% (n = 529) had a diagnosed mental health condition, both of which were higher than among all adults (28.1% and 29.1%, respectively). CONCLUSION: In England, from April 2020 to March 2022, the prevalence of both smoking and increasing-and-higher-risk drinking was 4.6%. This group appears to experience high rates of mental health problems and targeted support is needed.

Social smoker identity and associations with smoking and quitting behaviour: A cross-sectional study in England.

BACKGROUND: 'Social smoking' typically occurs predominantly or exclusively in the presence of others who are smoking. Relatively little is known about changes in the prevalence of 'social smoking identity' over time and its association with other smoking-related correlates. METHODS: Data were from the Smoking Toolkit Study, a nationally-representative cross-sectional survey in England. Participants were 26,774 adults who currently smoked or had quit in the past year, surveyed between February-2014 and April-2021. We estimated the proportion identifying as having a social smoking identity, changes over time, and associations with smoking in social situations, cigarette dependence, motivation to stop, quit attempts and success. RESULTS: Of adults who currently smoked or had quit in the past year, 34.0% (95% Confidence Interval (CI)=33.5-34.6) identified as having a social smoking identity. There was a near linear increase in this proportion from 31.9% (95%CI=29.7-34.2) in February-2014 to 36.5% (95%CI=34.1-38.9) in April-2021. Adults who currenty smoked identifying as having a social smoking identity were less cigarette dependent (adjusted B=0.34, 95%CI=0.31-0.37) and more motivated to stop (aOR=1.20, 95%CI=1.15-1.26) than those who did not. Adults who currently smoked or had quit in the past year identifying as having a social smoking identity reported more smoking in social situations (aOR=6.45, 95%CI=6.13-6.80) and past-year quit attempts (aOR=1.22, 95%CI=1.14-1.30) than those who did not. Quit success was not associated with having a social smoking identity among adults who currently smoked or had quit in the past year and who had attempted to quit (aOR=0.90, 95%CI=0.79-1.02). CONCLUSIONS: An increasing proportion, over a third, of adults who currently smoked or had quit in the past year in England identify as having a social smoking identity. Despite being associated with lower dependence, greater motivation to quit and more quit attempts, social smoking identity is not associated with greater quit success, suggesting a complex interplay between identity and smoking-related behaviours.

Methodological Insights on Recruitment and Retention From a Remote Randomized Controlled Trial Examining the Effectiveness of an Alcohol Reduction App: Descriptive Analysis Study.

BACKGROUND: Randomized controlled trials (RCTs) with no in-person contact (ie, remote) between researchers and participants offer savings in terms of cost and time but present unique challenges. OBJECTIVE: The goal of this study is to examine the differences between different forms of remote recruitment (eg, National Health Service [NHS] website, social media, and radio advertising) in the proportion of participants recruited, demographic diversity, follow-up rates, and cost. We also examine the cost per participant of sequential methods of follow-up (emails, phone calls, postal surveys, and postcards). Finally, our experience with broader issues around study advertising and participant deception is discussed. METHODS: We conducted a descriptive analysis of 5602 increasing-and-higher-risk drinkers (Alcohol Use Disorders Identification Test score ≥8), taking part in a 2-arm, parallel group, remote RCT with a 1:1 allocation, comparing the intervention (Drink Less app) with usual digital care (NHS alcohol advice web page). Participants were recruited between July 2020 and March 2022 and compensated with gift vouchers of up to £36 (a currency exchange rate of £1=US $1.26988 is applicable) for completing follow-up surveys, with 4 stages of follow-up: email reminders, phone calls, postal survey, and postcard. RESULTS: The three main recruitment methods were advertisements on (1) social media (2483/5602, 44.32%), (2) the NHS website (1961/5602, 35.01%), and (3) radio and newspapers (745/5602, 13.3%), with the remaining methods of recruitment accounting 7.37% (413/5602) of the sample. The overall recruitment cost per participant varied from £0 to £11.01. Costs were greater when recruiting participants who were men (£0-£28.85), from an ethnic minority group (£0-£303.81), and more disadvantaged (£0-£49.12). Targeted approaches were useful for recruiting more men but less useful in achieving diversity in ethnicity and socioeconomic status. Follow-up at 6 months was 79.58% (4458/5602). Of those who responded, 92.4% (4119/4458) responded by email. Each additional stage of follow-up resulted in an additional 2-3 percentage points of the overall sample being followed up, although phone calls, postal surveys, and postcards were more resource intensive than email reminders. CONCLUSIONS: For remote RCTs, researchers could benefit from using a range of recruitment methods and cost-targeted approaches to achieve demographic diversity. Automated emails with substantial financial incentives for prompt completion can achieve good follow-up rates, and sequential, offline follow-up options, such as phone calls and postal surveys, can further increase follow-up rates but are comparatively expensive. We also make broader recommendations focused on striking the right balance when designing remote RCTs. Careful planning, ongoing maintenance, and dynamic decision-making are required throughout a trial to balance the competing demands of participation among those eligible, deceptive participation among those who are not eligible, and ensuring no postrandomization bias is introduced by data-checking protocols.