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Record W4392713192 · doi:10.2147/ijwh.s448147

Gender and Drug Use Discrimination Among People Who Inject Drugs: An Intersectional Approach Using the COSINUS Cohort

2024· article· en· W4392713192 on OpenAlexaff
I. Anwar, Aissatou Faye, Jessica Pereira Gonçalves, Laélia Briand Madrid, Gwenaëlle Maradan, Laurence Lalanne, Marie Jauffret‐Roustide, Marc Auriacombe, Perrine Roux

Bibliographic record

VenueInternational Journal of Women s Health · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsBritish Columbia Centre on Substance Use
FundersInstitut pour la Recherche en Santé PubliqueÉcole des Hautes Études en Santé PubliqueMission Interministérielle de Lutte Contre les Drogues et les Conduites Addictives
KeywordsMedicineContext (archaeology)Logistic regressionIntersectionalityCohortDrugStigma (botany)Health careDemographyPsychiatryInternal medicineSociologyGender studies

Abstract

fetched live from OpenAlex

Purpose: 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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.057
GPT teacher head0.377
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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