Despite evidence that there is a link between exposure to alcohol-related content on social media and alcohol use, there has been less focus on testing the underlying mechanisms that explain the link. Findings from the primary studies that test the mechanisms are fragmented and inconsistent, with no systematic synthesis to date. We aimed to identify what mediators had been tested that may explain the link between exposure to alcohol-related content on social media with alcohol use. We conducted a systematic search of five major databases (MEDLINE, PsycINFO, CINAHL, Web of Science, and ProQuest). Article selection and data extraction were performed independently by at least two reviewers. The pooled indirect effect of social media alcohol exposure via the selected mediators was estimated using a two-stage meta-analytic structural equation modeling approach. Of the 397 articles screened, 10 studies met the inclusion criteria. Overall, social norms were the most common mediator examined. Our meta-analysis found significant indirect associations between social media alcohol exposure and alcohol use via descriptive norms (B = 0.07; 95% CI: 0.05-0.10) and injunctive norms (B = 0.05; 95% CI: 0.02-0.07). Other mediators identified included drinking motives, alcohol-related beliefs (e.g., "drinking makes socialising easier"), drinking identity, and poster prototypes (i.e., perceptions of the typical people who post alcohol-related content). Exposure to alcohol-related content on social media was indirectly associated with alcohol use through psychosocial factors, mainly perceived social norms. Norms-focused strategies (e.g., personalized normative feedback) may be a useful component of multi-component interventions, alongside approaches targeting other pathways.

BACKGROUND:Resilience, defined as the capacity to recover from difficulties or to adapt well to stressors, challenges, and adversities in life, is increasingly studied, yet its role in a range of alcohol-related outcomes remains unclear, including alcohol consumption, risky drinking, and alcohol use disorder. This review synthesises available evidence while considering variability across populations, contexts, and measurement approaches. METHODS:We systematically searched MEDLINE, PsycINFO, CINAHL, and Web of Science for observational studies examining the relationship between individual-level resilience and alcohol-related outcomes. Two independent reviewers screened records and extracted data, with disagreements resolved by consensus. We included studies published on or after 1 January 2014 that reported an association or provided sufficient data to determine its direction. Random-effects meta-analysis was used to estimate pooled associations for studies reporting comparable effect sizes (odds ratios or correlation coefficients), and narrative synthesis was used for studies not amenable to meta-analysis. RESULTS:A total of 66 studies met the inclusion criteria and were included in the review. Approximately two-fifths (42.6%) were conducted in high school or college student populations, and 65.3% were conducted in high-income countries, primarily the United States. Meta-analysis of 24 studies showed that higher resilience was associated with lower odds of alcohol-related outcomes (pooled OR = 0.91, 95% CI = 0.87-0.95), although the observed heterogeneity was substantial (I2 = 99.9%, p < 0.001). Consistent with this, the narrative synthesis indicated that associations between resilience and alcohol outcomes varied by life stage, high-risk or clinically vulnerable populations, cultural context, and resilience dimensions, with emotion-regulation and coping-related components showing more consistent protective associations than competence- or achievement-oriented traits. CONCLUSION:While resilience shows a small protective association with alcohol use and related harms, but effects are highly context-dependent and specific by dimension. Given most evidence is cross-sectional with substantial heterogeneity, resilience should not be considered as a standalone target for prevention. Future research should prioritise longitudinal designs, standardised measurement and a clear differentiation between resilience components to clarify how specific dimensions of resilience influence alcohol outcomes across diverse populations. Prospero Registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD42024520281.

Alcohol consumption is one of the leading risk factors for morbidity and mortality worldwide. Alcohol marketing communications play a central role in shaping social norms and drinking behaviors. The rapid expansion of digital media has transformed alcohol promotion, increasing its reach, personalization, and integration into daily life. Exposure to alcohol marketing communications is associated with earlier initiation of drinking, increased consumption, and more intense drinking patterns, particularly among adolescents and young adults. Alcohol marketing communication, including in the digital environment, is a significant and modifiable determinant of consumption, for which legal regulation is essential.

BACKGROUND AND AIMS:Thanks to smart devices, social media and streaming platforms, watching videos, like movies or short social media clips, has become extremely popular. Alcohol portrayals are frequent in videos, yet their prevalence is difficult to quantify using traditional methods such as manual coding. Artificial intelligence (AI) offers a scalable solution to analyse large volumes of video images. This study aimed to compare the accuracy of three AI models in detecting alcohol presence in video images. METHOD:Experimental evaluation of three models: one supervised deep learning model (ABIDLA2) and two zero-shot learning models (ZSL-CLIP and ZSL-LLaVA). The models were tested on datasets of video frames that had been annotated by researchers for whether they included alcohol or not. Three datasets of increasing complexity were used: (1) a Google/Bing image set of clearly visible alcohol and non-alcohol images; (2) a set of movie frames manually annotated as containing or not containing alcohol; and (3) a contextually challenging set of movie frames from alcohol-related settings (e.g. bars, parties) that may or may not include visible alcohol. Model performance was assessed using accuracy, unweighted average recall (UAR) and F1 score, representing the balance between precision and recall. Execution time per frame was also measured to evaluate computational efficiency. RESULTS:Across the three datasets, ABIDLA2, ZSL-CLIP and ZSL-LLaVA achieved percentage accuracies of 90%, 91% and 92% on the Google/Bing images; 70%, 65% and 95% on the diverse movie-scene dataset; and 67%, 63% and 94% on the most complex alcohol-related dataset, respectively. In terms of execution time, ABIDLA2 processed a single frame the fastest (0.21 seconds), followed by ZSL-LLaVA (0.45 seconds), while ZSL-CLIP was the slowest (0.58 seconds). CONCLUSION:Automated artificial intelligence (AI) models appear to be able to detect alcohol imagery in videos at large scale with high accuracy and in near real time. Of the three AI models tested, ZSL-LLaVA achieved the best balance between accuracy and speed. Offering a cost- and time-efficient alternative to labour-intensive manual coding, ZSL-LLaVA could be used to monitor alcohol-related visual content in videos across diverse media platforms.

INTRODUCTION:The growing accessibility of movies through streaming platforms has expanded audience reach, but also increases exposure to alcohol portrayals, which is an established risk factor for alcohol use. Hence, estimating alcohol depictions is important yet challenging due to the time and labor involved. Artificial Intelligence offers a scalable solution for analysing movie frames; however, processing every frame of a full-length movie at 25 frames per second (fps) requires extensive computational resources. Thus, we aimed to test whether lower-frequency sampling would affect the accuracy of alcohol exposure estimates. METHODS:We analysed 20 feature-length movies with varying known alcohol visibility and analysed each frame using zero-shot predictions from a LLaVA v1.6 model (accuracy = 95%) as our baseline. We applied uniform downsampling from 25 fps (full-framerate) to 1 fps and sparse interval sampling of 1 frame per N seconds (N = 1,2,…,10), measuring both alcohol-proportion estimates and execution time. To assess the sampling-induced error, we computed the difference score, as the difference between sampled and full-frame alcohol proportions. RESULTS:A sampling frequency of 1 fps yielded an average difference score below 0.10 compared to the full-frame analysis, while reducing execution time by 25-fold. Error increased at sparser intervals, reaching a difference score of 0.46 at one frame per 10 s. DISCUSSION AND CONCLUSION:Reducing the sampling frequency from 25 to 1 fps resulted in only a minimal loss of accuracy but a substantial reduction in execution time. This finding supports 1 fps as a practical and scalable sampling frequency for large-scale movie alcohol exposure estimation.

BACKGROUND AND OBJECTIVES:On social media, people are expected to disclose any sponsored content. However, celebrities who own alcohol brands and make posts promoting their brands may circumvent these disclosure policies, potentially exposing young audiences to alcohol marketing. This study examined the extent to which celebrities promoted their own alcohol brands on Instagram, whether they disclosed the content as sponsored, and whether the posts were visible to underage users. METHODS:Through systematic Google searches, we identified 112 celebrities who own alcohol brands. We retrieved 85 673 of their Instagram posts published between January 1, 2020, and December 31, 2023. Alcohol-brand posts were identified through text-pattern matching. We checked the accessibility of alcohol-brand posts to underage users using a simulated 15-year-old account. RESULTS:Among 112 celebrities (mean age = 50.8 years; 72.3% male), 42 (37.5%) explicitly mentioned their brand in their Instagram bio, and 84 (75%) referenced their own alcohol brand in at least 1 post during the study period. Of the 85 673 total posts, 3.4% mentioned a celebrity's alcohol brand. Concerningly, only 1.7% of these alcohol-brand posts included a clear disclosure in the caption and 98% (646/660) of sampled alcohol-brand posts were visible to a simulated 15-year-old account. CONCLUSIONS:Celebrities' posts about their own alcohol brands were common and accessible to underage users. Policymakers should implement stricter regulations on alcohol promotions on social media to protect adolescents from exposure to alcohol-related content.

BACKGROUND:Exposure to alcohol portrayals in movies has been associated with increased alcohol use. Several studies have examined the prevalence and frequency of alcohol portrayals in movies, but systematic synthesis of this evidence is lacking. This review aimed to estimate the pooled proportion of movies that portrayed alcohol and the average frequency of such portrayals per movie. METHODS:Systematic searches were conducted across three major databases (MEDLINE, PsycINFO, and Web of Science). Eligible articles were selected through title and abstract screening, and full-text review. Studies that assessed and reported the prevalence of alcohol portrayals in movies were eligible and included. Pooled prevalence with 95% confidence intervals was computed using a random effects model. RESULTS:A meta-analysis of 20 studies showed that 84.0% of movies portrayed alcohol at least once (95% CI: 78.0-89.0). We found that 24.0% (95% CI: 16.0-33.0) of 5-minute movie segments portrayed alcohol. The pooled estimate of mean number of alcohol portrayal scenes per movie was 21.3 (95% CI: 3.7-46.4), and alcohol portrayed on screen for 263.1 s per movie (95% CI: 184.5-341.7). Narrative synthesis showed that most studies were conducted in the United States, majority employed cross-sectional content analysis designs, and varied in how alcohol portrayals was operationalised, with most reporting presence and frequency metrics, while additional features such as branding or valence were inconsistently measured. CONCLUSIONS:Media consumption, especially movies, has proliferated and diversified during the last decades due to the surge of smart devices and online streaming platforms. This study revealed that the vast majority of movies portrayed alcohol and alcohol portrayal appears frequently. Given the well-established link between on-screen alcohol portrayal and subsequent drinking behaviours, policy should aim to target alcohol portrayal in movies (i.e., include alcohol portrayal when classifying movies, ban alcohol product placement). PROSPERO REGISTRATION NUMBER:CRD42024525561.

INTRODUCTION:Using Diffusion of Innovations Theory, we investigated whether countries with higher innovation capacity showed earlier tipping points (shift from increasing to decreasing drunkenness) and steeper declines in adolescent drunkenness (2002-2022). Innovation capacity likely facilitates these shifts through knowledge generation, policy implementation, and norm diffusion. METHODS:Trends in adolescent drunkenness were examined across 46 countries using six cross-sectional school-based survey waves from the international HBSC study (N = 319,843 15-year-olds). Data were complemented by country-level innovation capacity, per capita GDP, and Gini-coefficients. Two-level random effects models tested cross-level interactions between innovation capacity and linear and quadratic time trends in adolescent drunkenness frequency. RESULTS:Significant small-to-moderate cross-level interactions were found. Countries with high innovation capacity showed immediate linear declines (B = -.217, SE = .083), that flattened or showed an upward shift by 2022 (B = .031, SE = .007). Countries with low innovation capacity displayed an inverted U-shape trend in the early 2000s with a later tipping point (B = -.006, SE = .002). A steeper linear decline was observed for countries with higher (vs. lower) innovation capacity from their respective tipping point onward (B = -.273, SE = .083). DISCUSSION:Innovation capacity may accelerate adoption and diffusion of healthier behaviors through more rapid translation of health evidence into effective policy, parenting, and norms. While countries with high innovation capacity showed earlier declines, their initially higher levels of drunkenness may have created greater urgency for action. Earlier peaks and subsequent faster reductions in future alcohol-related health care needs are expected in these countries, though the possible recent trend reversal warrants close monitoring.

AIMS:Preliminary evidence suggests that exposure to alcohol-related content in popular music is associated with drinking behaviour, especially amongst young people. Guided by Uses and Gratifications Theory, which posits that audiences select music to satisfy psychological and social needs, alcohol references, and specific audio features may co-occur as part of shared emotional and social experiences. This study assessed whether song audio features are associated with alcohol references in lyrics and whether they could support population-level surveillance of alcohol-related media exposure. METHODS:We analyzed 6110 Billboard Top 100 songs released between 1959 and 2020, extracting Spotify audio features for each track. Logistic regression models were used to examine associations between audio features and the presence of alcohol references in lyrics. RESULTS:Alcohol references were found in 16.1% of songs, with prevalence increasing significantly over time. Songs with higher danceability (OR = 1.35, P < .001), speechiness (OR = 1.39, P < .001), liveness (OR = 1.09, P = .021), positive valence (OR = 1.11, P = .041) and major mode (OR = 1.18, P = .042) more likely to contain alcohol references. Higher acousticness (OR = 0.82, P < .001) and instrumentalness (OR = 0.85, P = .015) were associated with lower odds. Loudness, tempo, and energy were not significantly associated. CONCLUSIONS:Audio features may help identify songs more likely to contain alcohol references in music and may have potential utility for monitoring alcohol-related messaging across large volumes of popular music. Such tools could complement broader public health efforts to reduce alcohol exposure, especially amongst young people.

Thanks to the popularity of smartphones with high-quality cameras and social media platforms, an exceptional amount of image data is generated and shared daily. This visual data can provide unprecedented insights into daily life and can be used to help answer research questions in psychology. However, the traditional methods used to analyze visual data are burdensome and are either time-intensive (e.g., content analysis) or require technical training (e.g., developing and training deep learning models). Zero-shot learning, where a pretrained model is used without any additional training, requires less technical expertise and may be a particularly attractive method for psychology researchers aiming to analyze image data. In this tutorial, we aim to provide an overview and step-by-step guide on how to analyze visual data with zero-shot learning. Specifically, we demonstrate how to use two popular models (Contrastive Language-Image Pretraining and Large Language and Vision Assistant) to identify a beverage in an image from a data set where we manipulated the type of beverage present, the setting, and the prominence of the beverage in the image (foreground, midground, background). To guide researchers through this process, we provide open code and data on GitHub and as a Google Colab notebook. Finally, we discuss how to interpret and report accuracy, how to create a validation data set, what steps need to be taken to implement the models with new data, and discuss future challenges and limitations of the method. To conclude, zero-shot learning requires less technical expertise and may be a particularly attractive method for psychology researchers aiming to analyze image data. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Background Working mothers perform ‘double shifts’ of paid and domestic labour. Increased rates of employment among mothers in high income countries, and the impact of the alcohol industry actively promoting alcohol to working mothers, makes it crucial for preventative efforts to understand the factors driving alcohol use among this population. This systematic review of qualitative and quantitative studies provides an overview of the drinking patterns of working mothers and their predictors. Methods Four databases were systematically searched in August 2024. The population of interest were adult women in high income countries, who were both mothers of at least one dependent child and employed in any capacity. The methodological quality was assessed using the Mixed Methods Appraisal Tool. Following a convergent integrated approach, narrative synthesis was conducted for all studies. Results Of the 4623 records maintained for screening, 22 articles (15 quantitative and 7 qualitative) were included. Working mothers were more often drinkers and consumed a higher quantity per occasion (including binge and risky drinking) in comparison to mid-life women and non-working mothers. Alcohol use was also linked to managing emotional states, as a commodity to ‘cope’ with gendered norms. Living in a society with increased gender equity and being partnered or married had a protective effect on heavy drinking and consumed quantity. Conclusions Working mother’s drinking is governed by gender norms and expectations, and countries who advance policies to improve the acceptability and compatibility of motherhood and employment may reduce working mother’s alcohol use.

Ideals around femininity influence women's health behaviours, particularly for mothers facing hegemonic and gender normative pressures. This relationship becomes more complex when it comes to alcohol, where commercial, moral, health and pleasure-based discourses intersect. We examine how alcohol use is negotiated by employed mothers in the context of intensive motherhood, hegemonic femininity, neoliberal and postfeminist ideals. Drawing on interviews with 22 Australian working mothers, and informed by social constructionist and feminist epistemologies, we generated three themes. Women described managing the mental load of family life alongside paid employment, framing this as a matter of personal responsibility despite recognising gender inequalities. While alcohol symbolised freedom, defiance, and a way to reclaim identity, it was constantly negotiated in ways that aligned with 'good' motherhood, such as through controlled wine consumption, avoiding intoxication and prioritising caregiving duties. Amid women's constrained agency, alcohol use was perceived to offer a way to 'remake' motherhood. Ultimately, alcohol use functioned as both compliance and defiance, reproducing ideals around hegemonic femininity while allowing moments of autonomy. While women are encouraged, including by commercial actors, to express agency through alcohol use, this ignores the multiple social and institutional structures that underpin their lives and shape their drinking. We suggest that alcohol provides a useful lens into the contradictory and often restricting subject positions women negotiate, including the alignment between 'good' motherhood and neoliberal imperatives. Addressing these dynamics requires policies and strategies that recognise the gendered division of labour and support more equitable caregiving arrangements.

Objective: The federal Australian government has introduced legislation to require social media platforms to restrict access to their platforms for young people under 16 years of age. Amongst the conversations about protecting the health and wellbeing of young people, we have yet to see discussion on the impact of alcohol imagery as a pervasive ‘unhealthy’ industry on social media. This is problematic because young people consume a large amount of social media content and are exposed to glamorised alcohol depictions and targeted advertising. Conclusions: According to current regulations, the sponsoring of social media posts by alcohol companies should be declared, but enforcement of these requirements is challenging and most alcohol posts (whether sponsored or not) tend to glorify alcohol use. Better regulation, but not necessarily a social media ban, is needed to protect young viewers from pervasive alcohol exposure on social media.