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Enregistrement W2319075216 · doi:10.1136/sextrans-2013-051184.0022

S03.3 Addressing gender-based violence to reduce risk of STI and HIV

2013· article· en· W2319075216 sur OpenAlexaboutno aff
A. Amin, Claudia Moreno

Notice bibliographique

RevueSexually Transmitted Infections · 2013
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSex work and related issues
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineGonorrheaDomestic violencePopulationDemographySexual violenceSyphilisSex workChlamydiaEnvironmental healthPoison controlHuman immunodeficiency virus (HIV)Injury preventionImmunology

Résumé

récupéré en direct d'OpenAlex

Background Gender-based violence, and gender inequality more broadly, has been found to be associated with increased risk of sexually transmitted infections (STI) including HIV among women and girls as well as among key vulnerable groups such as sex workers. This paper presents the evidence of the increased risk of STI and HIV associated with gender-based violence; and looks at potential pathways by which gender-based violence and STI and HIV are linked. Methods A systematic review and meta-analysis of studies that measure the association between intimate partner violence and STI and HIV was conducted by the London School of Hygiene and Tropical Medicine and WHO as part of work feeding into the Global Burden of Disease Study estimates on violence against women and its health impacts. Another systematic review of studies that measure association between violence against sex workers and STI and HIV was also conducted by the University of British Columbia, Vancouver and WHO. Other studies and literature were reviewed to identify potential pathways to explain the links between gender-based violence and HIV. Results The results of the systematic review show that best estimate of association between physical and/or sexual intimate partner violence and HIV was an odds ratio (OR) of 1.52 (95% CI = 1.03 to 2.23) for HIV, from studies from generalized and concentrated HIV epidemics and slightly higher for syphilis, chlamydia or gonorrhea. . These studies, however, are mainly cross sectional population-based surveys among women in the general population. The systematic review of violence against sex workers shows that sex workers from India and US who experience sexual violence have between 2 and 3-fold increased risk of HIV sero-positivity. Sex workers who experience any form of physical or sexual violence by any perpetrator in studies from India (Karnataka), Thailand, USA (San Francico) also showed increased risk of STI sero-positivity. Studies suggest 4 potential pathways linking gender-based violence and STI/HIV. First, sexual violence can be directly associated with increased STI and HIV transmission. There are also several indirect mechanisms; these include a history of violence in childhood or adolescence being linked to increased sexual risk taking later; and difficulties in negotiation of condom use with the partner. Also, men who perpetrate violence are also more likely to engage in sexual risk taking. Third, fear of violence can prevent women and sex workers from seeking or accessing HIV information and services. Lastly, violence can be an outcome of diagnosis and disclosure of HIV status. Conclusion Interventions to address the HIV epidemic among women and among sex workers need to address violence as a risk factor. In each setting, interventions need to be based on an understanding of the potential pathways that link violence against women and sex workers to STI and HIV infection. HIV prevention, treatment, and care programmes for women and for sex workers can integrate violence prevention into their risk-reduction counselling and communication, work with men and boys to promote gender equality and reduce violence perpetration, empower women, girls and sex workers, address harmful gender norms that perpetuate the acceptability of violence, and address the harmful use of alcohol. Laws and policies that criminalize sex workers and that perpetuate gender-based discrimination against women and girls also need to be addressed.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,367
Score d'incertitude au seuil0,680

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,028
Tête enseignante GPT0,309
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations8
Publié2013
Routes d'admission1
Résumé présentoui

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