Use of alcohol, tobacco, cannabis, and other substances during the first wave of the SARS-CoV-2 pandemic in Europe: a survey on 36,000 European substance users
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: SARS-CoV-2 reached Europe in early 2020 and disrupted the private and public life of its citizens, with potential implications for substance use. The objective of this study was to describe possible changes in substance use in the first months of the SARS-CoV-2 pandemic in Europe. METHODS: Data were obtained from a cross-sectional online survey of 36,538 adult substance users from 21 European countries conducted between April 24 and July 22 of 2020. Self-perceived changes in substance use were measured by asking respondents whether their use had decreased (slightly or substantially), increased (slightly or substantially), or not changed during the past month. The survey covered alcohol (frequency, quantity, and heavy episodic drinking occasions), tobacco, cannabis, and other illicit drug use. Sample weighted data were descriptively analysed and compared across substances. RESULTS: Across all countries, use of all substances remained unchanged for around half of the respondents, while the remainder reported either a decrease or increase in their substance use. For alcohol use, overall, a larger proportion of respondents indicated a decrease than those reporting an increase. In contrast, more respondents reported increases in their tobacco and cannabis use during the previous month compared to those reporting decreased use. No distinct direction of change was reported for other substance use. CONCLUSIONS: Our findings suggest changes in use of alcohol, tobacco and cannabis during the initial months of the pandemic in several European countries. This study offers initial insights into changes in substance use. Other data sources, such as sales statistics, should be used to corroborate these preliminary findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it