Prevalence and patterns of gender-based violence across adolescent girls and young women in Mombasa, Kenya
Notice bibliographique
Résumé
BACKGROUND: We sought to estimate the prevalence and describe heterogeneity in experiences of gender-based violence (GBV) across subgroups of adolescent girls and young women (AGYW). METHODS: We used data from a cross-sectional bio-behavioural survey among 1299 AGYW aged 14-24 in Mombasa, Kenya in 2015. Respondents were recruited from hotspots associated with sex work, and self-selected into one of three subgroups: young women engaged in casual sex (YCS), young women engaged in transactional sex (YTS), and young women engaged in sex work (YSW). We compared overall and across subgroups: prevalence of lifetime and recent (within previous year) self-reported experience of physical, sexual, and police violence; patterns and perpetrators of first and most recent episode of physical and sexual violence; and factors associated with physical and sexual violence. RESULTS: The prevalences of lifetime and recent physical violence were 18.0 and 10.7% respectively. Lifetime and recent sexual violence respectively were reported by 20.5 and 9.8% of respondents. Prevalence of lifetime and recent experience of police violence were 34.7 and 25.8% respectively. All forms of violence were most frequently reported by YSW, followed by YTS and then YCS. 62%/81% of respondents reported having sex during the first episode of physical/sexual violence, and 48%/62% of those sex acts at first episode of physical/sexual violence were condomless. In the most recent episode of violence when sex took place levels of condom use remained low at 53-61%. The main perpetrators of violence were intimate partners for YCS, and both intimate partners and regular non-client partners for YTS. For YSW, first-time and regular paying clients were the main perpetrators of physical and sexual violence. Alcohol use, ever being pregnant and regular source of income were associated with physical and sexual violence though it differed by subgroup and type of violence. CONCLUSIONS: AGYW in these settings experience high vulnerability to physical, sexual and police violence. However, AGYW are not a homogeneous group, and there are heterogeneities in prevalence and predictors of violence between subgroups of AGYW that need to be understood to design effective programmes to address violence.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».