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Enregistrement W4410207457 · doi:10.1001/jamanetworkopen.2025.9486

Experiences of Care and Gaslighting in Patients With Vulvovaginal Disorders

2025· article· en· W4410207457 sur OpenAlexaff
Chailee Moss, Arthi Chinna-Meyyappan, Gabriela Skovronsky, Jessica Holloway, S Lorenzini, Na''imah Muhammad, I Kopits, Sara Perelmuter, Leia Mitchell, Jill M. Krapf, Caroline F. Pukall, Andrew T. Goldstein

Notice bibliographique

RevueJAMA Network Open · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueMenopause: Health Impacts and Treatments
Établissements canadiensQueen's University
Organismes subventionnairesStatens beredning för medicinsk och social utvärderingCelldex TherapeuticsNational Vulvodynia Association
Mots-clésVulvodyniaMedicineReferralDistressFamily medicineDescriptive statisticsClinical psychologySurgeryPelvic pain

Résumé

récupéré en direct d'OpenAlex

Importance: Medical gaslighting, in which a patient's concerns are dismissed without proper evaluation, has been described anecdotally in vulvovaginal patient care, but has not been quantified. Objective: To use a patient-centered instrument to measure adverse experiences in vulvovaginal care. Design, Setting, and Participants: Common themes from National Vulvodynia Association patient testimonials were used to design a mixed-methods measure of patient experience that included both quantitative and qualitative questions. An instrument was created and submitted to officers from the National Vulvodynia Association and Tight-Lipped, another patient advocacy organization, for feedback. The measure was then completed by patients before their first appointment at a vulvovaginal disorder referral clinic from August 2023 to February 2024. Exposure: Participation in the survey. Main Outcomes and Measures: The primary outcome was the incidence of reported clinician behavior and consequent distress as reported on the survey instrument. Quantitative data were analyzed using simple descriptive statistics (mean [SD], median [IQR], and percentage). Narrative responses provided by patients were analyzed using the clinical-qualitative method for content analysis. Results: A total of 520 patients completed surveys; 5 were eliminated because the patient was younger than 18 years, 6 were eliminated for duplication, 6 were eliminated because they had no past clinician, and 56 were eliminated for completely blank responses. Thus, surveys of 447 patients (mean [SD] age, 41.7 [15.2] years) were analyzed (86% response rate). Patients had a mean (SD) of 5.50 (4.53) past clinicians. Patients reported that a mean (SD) of 43.5% (33.9%) of past practitioners were supportive, 26.6% (31.7%) were belittling, and 20.5% (30.9%) did not believe the patient. In total, 186 patients (41.6%) were told they just needed to relax more, 92 (20.6%) were recommended to drink alcohol, 236 (52.8%) considered ceasing care because their concerns were not addressed, 92 (20.6%) were referred to psychiatry without medical treatment, 72 (16.8%) felt unsafe during a medical encounter, and 176 (39.4%) said they were made to feel crazy, the most distressing surveyed behavior (rated at a mean [SD] of 7.39 [3.06] of 10 on a numerical rating scale of distress). A total of 1150 quotations were analyzed qualitatively; common themes included lack of clinician knowledge (247 quotations) and dismissive behaviors (211 quotations). Conclusions and Relevance: In this cross-sectional study, a patient-centered measure of adverse experiences in vulvovaginal care was developed. Participants reported common past experiences with gaslighting and substantial distress; they frequently considered ceasing care. There is an urgent need for education supporting a biopsychosocial, trauma-informed approach to vulvovaginal pain and continued development of validated instruments to quantify patient experiences.

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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,227

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
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 Opus0,010
Tête enseignante GPT0,303
Écart entre enseignants0,293 · 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

Citations13
Publié2025
Routes d'admission1
Résumé présentoui

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