Motives for alcohol use, risky drinking patterns and harm reduction practices among people who experience homelessness and alcohol dependence in Montreal
Bibliographic record
Abstract
Abstract Background People experiencing homelessness are disproportionately affected by the harms related to alcohol use. Their alcohol dependence is associated with numerous physical and mental health problems, and strikingly high rates of alcohol related mortality. To develop interventions and treatments to address this problem, recent research has examined the patterns of alcohol use of people experiencing homeless. However, only a few studies have incorporated the perspective of these persons to identify such patterns and the ways in which they manage the harms associated to their alcohol use. To fill this gap, we conducted a qualitative study with a group of people (n = 34) experiencing homeless in Montreal (Canada). In doing so, we also explored how patterns of alcohol use are tied to their motives for drinking, as well as their harm reduction practices. Methods We used qualitative methods, including semi-structured interviews and focus groups. Results The participants identified four motives for drinking, including coping with painful memories, coping with harsh living conditions, socializing and belonging, as well as enjoying and having fun. They also defined five risky patterns of alcohol use linked to these motives: 1) binge drinking; 2) mixing alcohol with drugs; 3) non-beverage alcohol drinking; 4) not ensuring alcohol to prevent withdrawn; and 5) drinking in public settings. Additionally, they enacted practices oriented to reduce the harms associated to their alcohol use, including planning how much to drink, ensuring alcohol availability, hiding to drink, hiding drinks, drinking alone, drinking/hanging out with others, drinking non-beverage alcohol, taking benzodiazepines, cocaine or other stimulant drugs. Conclusion By shedding light on the associations between motives for drinking, risky drinking and harm reduction practices we aim to showcase the rationale behind the participants alcohol use to inform policies and interventions tailored to their needs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".