Harm from the drinking of people you know: A range of effects from different relationships

AIMS

To describe the range of effects experienced due to the drinking of people respondents know and analyze risk and protective factors for harm from the drinking of partners and household members, other relatives and friends and co-workers.

DESIGN, SETTING AND PARTICIPANTS

Surveys of 2574 participants' experiences were obtained from two samples: 1000 people responded to random digitally dialled Australian mobile calls and 1574 participants responded from the Life in AustraliaTM panel survey.

MEASUREMENTS

Respondents were asked whether they had been negatively affected in the previous 12 months by the drinking of persons they knew who were 'a heavy drinker or drank a lot sometimes' and the nature of these harms. Weighted logistic regressions were used to analyze differences in rates of key negative outcomes from known others' drinking by gender, age and socio-economic status.

FINDINGS

Almost two thirds [60.2%; 95% confidence interval (CI) = 57.7%-62.7%] of participants reported having heavy drinkers in their lives and 21.8% (95% CI = 19.8%-23.9%) reported being negatively affected by the drinking of people they knew well in some way. Participants reported a gamut of effects, including, most commonly, adverse social effects: having to transport relatives and friends who had been drinking, role failure and faults, being emotionally hurt or neglected, serious arguments, family problems, having to care for drinkers and verbal abuse. Less commonly, respondents reported physical or sexual harm, property damage, financial stress and threats from others' drinking. Women (odds ratio = 1.49; 95% CI = 1.13-1.95), younger people, rural, Australian-born (vs. respondents born overseas in non-English speaking countries) and more frequent drinkers were more likely to report harm from a drinker they knew than their counterparts after adjusting for other variables in the model.

CONCLUSIONS

Australians appear to be commonly adversely affected by the drinking of people they know. Harms from known drinkers are more likely to be experienced by women than men, particularly from the people they live with and other relatives.

How to apply zero-shot learning to text data in substance use research: An overview and tutorial with media data

A vast amount of media-related text data is generated daily in the form of social media posts, news stories or academic articles. These text data provide opportunities for researchers to analyse and understand how substance-related issues are being discussed. The main methods to analyse large text data (content analyses or specifically trained deep-learning models) require substantial manual annotation and resources. A machine-learning approach called 'zero-shot learning' may be quicker, more flexible and require fewer resources. Zero-shot learning uses models trained on large, unlabelled (or weakly labelled) data sets to classify previously unseen data into categories on which the model has not been specifically trained. This means that a pre-existing zero-shot learning model can be used to analyse media-related text data without the need for task-specific annotation or model training. This approach may be particularly important for analysing data that is time critical. This article describes the relatively new concept of zero-shot learning and how it can be applied to text data in substance use research, including a brief practical tutorial.

Exploring the relationship between solitary drinking and living without other adults on alcohol consumption during the COVID-19 pandemic

AIMS

The COVID-19 pandemic presents the opportunity to learn about solitary drinking as many people were forced to spend time at home. The aim of this study is to examine the relationship between solitary drinking and living without other adults on alcohol consumption.

METHODS

A longitudinal study with four survey waves (between May and November 2020) obtained seven-day drinking diary data from Australian adults living in New South Wales. In May, a convenience sample of 586 participants (Mage = 35.3, SD = 14.8; 65.3% women) completed the first wave. Participants then completed a survey in June (n = 319, 54.4% response rate), July/August (n = 225, 38.4% response rate), and November (n = 222, 37.9% response rate). Information about alcohol consumption including risky drinking (more than four drinks on one occasion), household structure, solitary drinking, and demographics were collected. We conducted random-effects panel bivariate and multivariable regression analyses predicting the number of standard drinks and risky drinking.

RESULTS

Participants with solitary drinking occasions consumed more and had more risky drinking occasions than participants with no solitary drinking occasions, which was also found to be the case during lockdown. Living without other adults was associated with less consumption and less risky drinking than living with other adults. However, participants who lived without other adults and had frequent solitary drinking occasions (solitary drinking in >50% drinking occasions) reported more consumption than participants without a solitary drinking occasion.

CONCLUSIONS

Individuals who consume alcohol alone and live without other adults or spend long periods of time at home may be more at risk of alcohol-related harm.

The burden of alcohol-related caring for others in Australia in the 2021 pandemic period

OBJECTIVE

The magnitude of caring for others due to excessive alcohol use is unclear in Australia and internationally. This study explores the prevalence, sociodemographic predictors, and consequences of informal care for others due to alcohol use.

METHOD

A survey on harm from others' drinking was conducted among 2,574 Australian adults in November 2021 from national random digit dial and "Life in Australia" panel samples to elicit representative data. Respondents who indicated they had "heavy drinker/s" in their lives (n= 1,585), were asked about their experience of caring for these drinkers and their dependents in the last 12 months. Weighted logistic and linear regressions examined a) sociodemographic factors associated with informal care due to others' drinking, and b) the impact of the caregiving burden on caregiver's financial status, overall health, and quality of life.

RESULTS

Overall, 20% of participants reported caregiving responsibilities arising from others' drinking. Older age, unemployment, residing in capital cities and reporting birth in a non-English speaking background country were associated with a reduced likelihood of caregiving, whereas higher education and more frequent risky drinking were associated with an increased likelihood. Caregivers reported significantly higher financial disadvantage, a lower quality of life and poorer overall health.

CONCLUSIONS

One in five adults reported caring for drinkers in the previous 12 months, with this associated with negative consequences for those providing care. Service providers, health promotion practitioners and policy makers should focus upon younger age groups, those who live in regional areas, and those born in Australia who are at greater risk of being burdened by caregiving due to others' alcohol use.

The prevalence of alcohol references in music and their effect on people's drinking behavior: A systematic review and meta-analysis

Understanding the prevalence of alcohol references in music and their impact on alcohol drinking behavior is important given the increased accessibility to daily music listening with the proliferation of smart devices. In this review, we estimate the pooled prevalence of alcohol references in music and its association with drinking behavior. Systematic searches were conducted across four major databases (MEDLINE, PsycINFO, EMBASE, and CINHAL). Articles were selected following duplicate checking, title and abstract screening, and full-text review. Studies reporting the prevalence of alcohol-referencing music and/or investigating its association with drinking behavior were included. Pooled prevalence with 95% confidence intervals (CIs) were computed using a random effects model. Of 1007 articles identified, 26 met inclusion criteria and 23 studies comprising 12,224 songs were eligible for meta-analysis. The overall pooled prevalence of alcohol references in music (including lyrics and videos) was 24.0% (95% CI: 19.0%-29.0%). The pooled prevalence was 22.0% (95% CI: 16.0%-29.0%) for only lyrics, 25.0% (95% CI: 18.0%-33.0%) for only the visual elements of music videos, and 29.0% (95% CI: 21.0%-38.0%) for both the lyrical content and the visual components. Only three studies assessed the relationship between listening to music with alcohol references and drinking behavior, and all three reported a positive association. Whereas almost a quarter of all songs included references to alcohol, public health preventive measures are needed to reduce alcohol exposure from music. Future research is needed to understand fully the effect of music with alcohol references on drinking behavior.

The promise of zero-shot learning for alcohol image detection: comparison with a task-specific deep learning algorithm

Exposure to alcohol content in media increases alcohol consumption and related harm. With exponential growth of media content, it is important to use algorithms to automatically detect and quantify alcohol exposure. Foundation models such as Contrastive Language-Image Pretraining (CLIP) can detect alcohol exposure through Zero-Shot Learning (ZSL) without any additional training. In this paper, we evaluated the ZSL performance of CLIP against a supervised algorithm called Alcoholic Beverage Identification Deep Learning Algorithm Version-2 (ABIDLA2), which is specifically trained to recognise alcoholic beverages in images, across three tasks. We found ZSL achieved similar performance compared to ABIDLA2 in two out of three tasks. However, ABIDLA2 outperformed ZSL in a fine-grained classification task in which determining subtle differences among alcoholic beverages (including containers) are essential. We also found that phrase engineering is essential for improving the performance of ZSL. To conclude, like ABIDLA2, ZSL with little phrase engineering can achieve promising performance in identifying alcohol exposure in images. This makes it easier for researchers, with little or no programming background, to implement ZSL effectively to obtain insightful analytics from digital media. Such analytics can assist researchers and policy makers to propose regulations that can prevent alcohol exposure and eventually prevent alcohol consumption.

Drinking before sporting events in Australia: An ecological momentary assessment study

This study investigates the individual and event-level correlates of drinking prior to attending Australian Football League (AFL) games among a sample of Australian spectators.

A total of 30 adults (20% female, mean age = 32) completed a series of questionnaires (n = 417) before, during, and after an AFL match on a Friday, Saturday, or Sunday. Cluster-adjusted regression analyses were conducted to examine the impact of individual-level (age, gender, drinking habits) and event-level factors (time and day of game, location of viewing the game, viewing with friends or family) on drinking prevalence and the number of drinks consumed prior to the game.

41.4% of participants engaged in drinking before attending an AFL match with a mean of 2.3 drinks consumed by those who reported pre-game consumption. Those aged 30 and over were significantly more likely to engage in pre-game consumption (OR = 14.44, p = 0.024) and consumed significantly more pre-game (B = 1.39, p = 0.030). Drinking before the game was significantly more likely before night games than daytime games (OR = 5.24, p = 0.039). Those who watched the game on-premise consumed significantly more before the game than those who watched the game at a private residence or at home (B = 1.06, p = 0.030). Those who watched games with family also drank significantly less prior to the game than those who attended without family (B=-1.35, p = 0.010).

Addressing the contextual factors associated with drinking before the sporting events, such as the time of the game, may assist with efforts to reduce risky alcohol consumption and related harm.

Commercial Advertising of Alcohol: Using Law to Challenge Public Health Regulation

In most countries, the alcohol industry enjoys considerable freedom to market its products. Where government regulation is proposed or enacted, the alcohol industry has often deployed legal arguments and used legal forums to challenge regulation. Governments considering marketing regulation must be cognizant of relevant legal constraints and be prepared to defend their policies against industry legal challenges.

Mental health of college students during the COVID-19 epidemic in China

OBJECTIVES

To assess the psychological status of college students in China during the COVID-19 outbreak, and offer some theoretical evidence for psychological intervention of college students.

METHODS

An online survey was conducted from May 10, 2020 to June 10, 2020. Anxiety symptoms were measured by the Generalized Anxiety Disorder 7-Item Scale (GAD-7). Categorical data were reported as number and percentage, while continuous data were reported as mean ± SD. Multivariate logistic regression models were used to evaluate the association between different factors and anxiety symptoms.

RESULTS

A total of 89,588 college students participated in the current study, among which 36,865 students (41.1%) reported anxiety symptoms. Multivariate logistic regression analysis revealed that the risk factors for anxiety symptoms included the age of 26-30 (OR=1.456), sophomore (OR=1.038), junior (OR=1.087) and senior grades (OR=1.161), a higher paternal education level (OR=1.055), low economic status (OR=1.520), and low social support (OR=1.542).

CONCLUSIONS

About two-fifths of Chinese college students experienced anxiety symptoms during the COVID-19 epidemic. Timely and appropriate psychological interventions for college students should be implemented to reduce the psychological harm caused by COVID-19 epidemic.