Aims: To investigate changes in alcohol consumption during the first months of the COVID‐19 pandemic in Europe as well as its associations with income and experiences of distress related to the pandemic.Design: Cross‐sectional on‐line survey conducted between 24 April and 22 July 2020.Setting: Twenty‐one European countries.Participants: A total of 31 964 adults reporting past‐year drinking.Measurements: Changes in alcohol consumption were measured by asking respondents about changes over the previous month in their drinking frequency, the quantity they consumed and incidence of heavy episodic drinking events. Individual indicators were combined into an aggregated consumption‐change score and scaled to a possible range of −1 to +1. Using this score as the outcome, multi‐level linear regressions tested changes in overall drinking, taking into account sampling weights and baseline alcohol consumption [Alcohol Use Disorder Identification Test (AUDIT‐C)] and country of residence serving as random intercept. Similar models were conducted for each single consumption‐change indicator.Findings: The aggregated consumption‐change score indicated an average decrease in alcohol consumption of −0.14 [95% confidence interval (CI) = −0.18, −0.10]. Statistically significant decreases in consumption were found in all countries, except Ireland (−0.08, 95% CI = −0.17, 0.01) and the United Kingdom (+0.10, 95% CI = 0.03, 0.17). Decreases in drinking were mainly driven by a reduced frequency of heavy episodic drinking events (−0.17, 95% CI = −0.20, −0.14). Declines in consumption were less marked among those with low‐ or average incomes and those experiencing distress.Conclusions: On average, alcohol consumption appears to have declined during the first months of the COVID‐19 pandemic in Europe. Both reduced availability of alcohol and increased distress may have affected consumption, although the former seems to have had a greater impact in terms of immediate effects.

Evidence suggests that changes in alcohol consumption during the first months of the COVID-19 pandemic were unevenly distributed over consumer groups. We investigated possible inter-country differences in how changes in alcohol consumption are contingent on initial consumption (before or at the start of the pandemic), and how changes in consumption translate into possible changes in the prevalence of heavy drinking. We used data from the European Survey on Alcohol use and COVID-19 (ESAC) conducted in Czechia, Denmark, Finland, Germany, Norway, Poland, Spain, and the UK (N = 31921). Past-year alcohol consumption and changes in consumption were measured by AUDIT-C. Drinking habits were compared according to percentiles of pre-pandemic consumption levels, below versus above the 90th percentile. Across countries, drinkers in the highest 10% for pre-pandemic consumption increased their drinking during the pandemic, whereas absolute changes among those initially drinking below this level were modest. The percentage of people reporting >28 alcohol units/week increased significantly in seven of eight countries. During the first months of the COVID-19 pandemic, alcohol consumption in the upper decile of the drinkers increased as did the prevalence of heavy drinkers, in contrast with a declining consumption in other groups in the sample.

Background and aims: The current level of knowledge concerning the effect of socioeconomic status (SES) on internet use, gambling, and substance use in structurally disadvantaged regions is scarce. The objective of this study was an investigation of the relationship between SES and risky internet use, gambling and substance use in a structurally disadvantaged region in Central Europe. Methods: A cross-sectional survey was conducted among high school students (n = 1063) in a Czech structurally disadvantaged region in autumn 2017. Binary Logistic Regression models were applied to data from the modified Excessive Internet Use scale (mEIUS), a standard tool for measuring the risk of addictive behavior on the internet and the risk of excessive gaming. Other data were collected using the Lie/Bet (problematic gambling), CAGE (acronym of the key words: cut, angry, guilty and eye-opener), and the Cannabis Abuse Screening Test (CAST) (problematic alcohol/cannabis use) tools. Results: There were statistically significant differences between at-risk and not-at-risk groups in addictive behavior on the internet and gaming, while none were found in problematic gambling. Individual dimensions of SES showed significant effects on substance use. Regarding parenting styles, significant differences were found only in the risk of addictive behavior on the internet or gaming between the authoritarian and authoritative styles. Being engaged in behavioral addictions with one´s parents increased the odds of the behavioral addiction risk and decreased the odds of the substance addiction risk. Engagement with one´s parents in substance addictions decreased the odds of the behavioral addiction risk and increased the odds of the substance addiction risk. Discussion and Conclusions: The results point at specific relations between SES and the risk of addictive behaviors on the internet and gaming within structurally disadvantaged regions. The results of SES and/or structurally disadvantaged region measures obtained in research, policy-making, and care-provision may improve the focus of actions taken.

The objective of the paper is to evaluate the quality of systemic change management (CHM) and readiness for change in five Central European countries. The secondary goal is to identify trends and upcoming changes in the field of digital innovations in healthcare. The results show that all compared countries (regardless of their historical context) deal with similar CHM challenges with a rather similar degree of success. A questionnaire distributed to hospitals clearly showed that there is still considerable room for improvement in terms of the use of specific CHM tools. A review focused on digital innovations based on the PRISMA statement showed that there are five main directions, namely, data collection and integration, telemedicine, artificial intelligence, electronic medical records, and M-Health. In the hospital environment, there are considerable reservations in applying change management principles, as well as the absence of a systemic approach. The main factors that must be monitored for a successful and sustainable CHM include a clearly defined and widely communicated vision, early engagement of all stakeholders, precisely set rules, adaptation to the local context and culture, provision of a technical base, and a step-by-step implementation with strong feedback.

Background: Amphetamine-type stimulants (ATS) are globally widely used. Scientific literature generally defines four phases of substance use (initiation, continuation, increase and decrease); however, there is limited understanding of what influences these different phases of ATS use. The ATTUNE study investigated which factors shape individual phases of use, or ATS use patterns. In this article, we report on these phases into and out of ATS use, and propose a set of recommendations for prevention, harm reduction and treatment of the different phases of ATS use. Methods: Qualitative, semi-structured interviews (n = 237) were conducted in five different European countries with participants who had used ATS, varying from a few times in a lifetime to daily. Results: Amphetamine and MDMA were the most commonly used ATS. Yet, types of ATS used differed between the countries. We found that people who use ATS have various motives for and dynamic patterns of ATS use with alternating phases of increase, continuation, decrease and sometimes dependence. Cessation was pursued in different ways and for diverse reasons, such as mental health problems and maturing out. Availability seemed not an issue, regardless of the type of ATS, phase or country. Conclusions: These findings demonstrate that tailor-made interventions are needed for the diverse types of people who use ATS and different phases or patterns of ATS use, to reduce possible harms of use. We recommended a set of interventions for the different ATS phases. These include drug checking services, peer-led information, self-management of ATS use, mental health support to help people cope with stressful life events and prevent uncontrolled use, and follow-up support after treatment.