Prévention du chemsex : état des lieux des connaissances, attitudes et pratiques des équipes officinales vis-à-vis des usagers du chemsex dans la région Auvergne-Rhône-Alpes
Bibliographic record
Abstract
Chemsex, which is booming in France and all around the world, has become a public health issue, which is why a prevention and harm reduction resolution was proposed to the French National Assembly in 2024. A literature review was carried out at the start of this project to establish precise definitions, study epidemiology, summarize practices and risks for each substance used, and determine patients' expectations and the challenges facing pharmacies. According to recent studies, a third to a quarter of users seek advice from healthcare professionals; and given the dispensing pharmacist's position as an easily accessible healthcare professional, it is important that he or she is able to answer certain questions and guide patients showing signs of vulnerability. We therefore conducted a survey of knowledge, attitudes and practices among pharmacists, pharmacy technicians and pharmacy students in the Auvergne-Rhône-Alpes region, using the KAP (Knowledge, Attitude and Practice) method validated by the WHO (World Health Organization). The results showed a need in terms of knowledge and posture. The survey showed that pharmacy teams were willing to take on new missions of prevention and reduction of risks related to the practice of Chemsex despite the difficulties encountered, notably lack of time, resources and confidentiality, and despite the taboo nature of the practice. Other projects could be considered such as the promotion of qualitative surveys, among patients who practise Chemsex, in order to investigate expectations and, thus, adapt intervention offers; or pharmacological studies to remedy the lack of data. It would also be interesting to establish a reference framework for management with recommendations validated by health authorities, Guides for preventive and supportive interviews and directories to direct patients to other more specialized health professionals. It is important today that the pharmacist works in coordination with other health professionals and community associations to ensure optimal care for these patients in a holistic approach given the complexity of the phenomenon.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".