Gender and Drug Use Discrimination Among People Who Inject Drugs: An Intersectional Approach Using the COSINUS Cohort
Bibliographic record
Abstract
Ilhame Anwar,1 Aissatou Faye,1 Jessica Pereira Gonçalves,1 Laélia Briand Madrid,1 Gwenaëlle Maradan,2 Laurence Lalanne,3,4,* Marie Jauffret-Roustide,5– 7,* Marc Auriacombe,8– 10,* Perrine Roux1 1Aix Marseille Univ, Inserm, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l’Information Médicale, ISSPAM, Marseille, France; 2ORS PACA, Observatoire régional de la santé Provence-Alpes-Côte d’Azur, Marseille, France; 3INSERM 1114, Department of Psychiatry and Addictology, University Hospital of Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, 67000, France; 4Department of Psychiatry and Addictology, University Hospital of Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, 67000, France; 5CERMES3 (Inserm U988/UMR CNRS 8211/EHESS/Paris Descartes University), Paris, France; 6British Columbia Center on Substance Use, Vancouver, Canada; 7Baldy Center on Law and Social Policy, Buffalo University, New York, NY, USA; 8Univ. Bordeaux, Bordeaux, France; 9Addiction Team (Laboratoire de psychiatrie)/SANPSY, CNRS USR 3413, Bordeaux, France; 10Pôle Addictologie, CH Charles Perrens and CHU de Bordeaux, Bordeaux, France*These authors contributed equally to this workCorrespondence: Ilhame Anwar, Sciences Economiques et Sociales de la Santé et Traitement de l’Information Médicale (SESSTIM), Faculté des sciences médicales et paramédicales, 27 Bd Jean Moulin 13385 Marseille Cedex 5, Marseille, France, Email ilhame.anwar@inserm.frPurpose: Injection drug use is strongly associated with stigmatization by loved ones, healthcare providers, and society in general. This stigmatization can have negative consequences on the health of people who inject drugs (PWID) and limit their access to care. Women who inject drugs face greater stigma than men because of gendered social norms and the intersectional effect between gender and drug use identities. For this analysis, we aimed to study discrimination - which is closely linked to stigmatization - experienced by PWID, considering the intersectionality between drug use discrimination and gender discrimination in the French context.Methods: We used data from the COSINUS cohort study, conducted between June 2016 and May 2019 in four French cities. We selected 427 of the 665 PWID who regularly injected drugs enrolled in COSINUS, at three months of follow-up, and performed multivariable logistic regression to identify factors associated with self-reported drug use discrimination.Results: Women comprised 20.6% of the study sample. Sixty-nine percent of the participants declared drug use discrimination and 15% gender discrimination. In the multivariable regression analysis, PWID who had hurried injection out of fear of being seen were almost twice as likely to have experienced drug use discrimination (OR [95% CI]: 1.77 [1.15, 2.74], p = 0.010). Likewise, women experiencing gender discrimination were almost three times as likely to have experienced drug use discrimination (OR [95% CI]: 2.84 [1.07,7.56], p=0.037).Conclusion: Women who inject drugs experienced gender and drug use intersectional discrimination. This could be a reason for the low attendance rates of women in healthcare settings. In addition, discrimination negatively impacted injection drug use practices (eg, hurried injection), particularly for people with unstable housing who injected in public spaces. We recommend introducing adapted services in healthcare facilities for women who inject drugs, and creating a favorable social and physical environment for all PWID in order to improve their health and access to care.Keywords: gender, injection drug use, intersectionality, discrimination
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".