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Enregistrement W4382542110 · doi:10.1093/jsxmed/qdad068.028

(029) Prevalence of Sexual Pain Among Cis-Gender Muslim Women in North America

2023· article· en· W4382542110 sur OpenAlexaboutno aff
Syed Rahman, Nadiah Mohajir, Hassoum Ceesay, M Bdaiwi, Y Khayr, W Akthar

Notice bibliographique

RevueThe Journal of Sexual Medicine · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueSexual function and dysfunction studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSnowball samplingSexual dysfunctionOutreachPopulationMedicineReproductive healthReligiosityHealth careCross-sectional studyPsychiatryClinical psychologyFamily medicinePsychologyDemographyEnvironmental healthSocial psychologyPolitical scienceSociology

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Muslim women represent an underserved and underrepresented minority in North America. It is well documented that unconscious bias impacts the quality of healthcare delivery in the U.S. Stigmas related to sexual health in the Islamic culture may detrimentally impact a Muslim woman's ability to seek care as well. The prevalence rates of lifetime sexual pain disorders among all women, in general, are poorly studied and rates vary from 6 to 40% depending on the study. Even less has been studied in this population with an isolated study from one clinic demonstrating about a 14% prevalence of sexual pain in Muslim women with sexual dysfunction. It is important to understand the burden of sexual pain and dysfunction among Muslim women to improve the quality of their care. Objectives The objective of this study was to investigate the prevalence of sexual violence, sexual dysfunction, and spiritual abuse among Muslims aged 18-45 and understanding the barriers to seek healthcare and assistance. Methods A national cross-sectional, IRB approved study was implemented to investigate the above. Through the use of the Qualtrics online platform, a 151- question survey was designed and implemented which included questions about demographics as well as questions about religiosity, sexual dysfunction, sexual pain, varying types of sexual abuse, and follow-up treatment. Participants were recruited using a snowball sampling approach via social media, listserv outreach, office visits, and mobilizing key community partners to help disseminate the survey. Descriptive statistics were utilized to better understand the prevalence and will further attempt to examine the correlation between barriers to seeking assistance and identity, attitudes, and experiences of sexual violence. Results From March 2020 until November 2020, a total of 704 Muslims ranged from 18-45 years old across the United States and Canada responded to the survey. Of those, 86% identified themselves as cis-gender women. Of those women, 47% chose to answer the questions regarding sexual dysfunction and sexual pain and almost half of the respondents (42%) admitted to having a history of sexual pain and dysfunction. Among those women who had a history of sexual pain, 65% admitted that they had never sought help for their pain from any healthcare provider. Conclusions Sexual pain and sexual dysfunction are under-reported among Muslim women and there are clear barriers that need to be overcome to alleviate their suffering. This is the first national study of its kind that has looked at sexual dysfunction and sexual pain, specifically, and is a great stepping stone to further analysis and investigation. At least half of the cis-gender women in this national survey admitted to some experience with sexual dysfunction, more specifically sexual pain, in their lifetime and more than two-thirds of those did not seek treatment. Cultural and religious stigmas, as well as possible barriers to seeking healthcare by lack of cultural competence training by many providers, may be contributing to their lack of follow up for treatment. With additional studies and analysis as well as building awareness, we can better understand how to eliminate barriers and stigmas and increase education for this population. Disclosure No.

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)0,004
score de la tête « metaresearch » (Gemma)0,002
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,228
Score d'incertitude au seuil0,707

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,057
Tête enseignante GPT0,305
Écart entre enseignants0,248 · 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

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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