Assessment of Mental and Chronic Health Conditions as Determinants of Health Care Needs and Digital Innovations for Women With Sexual Dysfunction: Cross-Sectional Population-Based Survey Study in Germany
Notice bibliographique
Résumé
Background: A chronic health condition (CHC) is a recognized risk factor for experiencing problems in sexual function (PSF). According to the International Classification of Diseases, 11th Revision (ICD-11), the development of severe symptoms of sexual distress is the defining criterion for clinically relevant sexual dysfunction. Data on the contribution of specific CHCs to clinically relevant sexual dysfunction symptoms and related health care needs are limited, hindering targeted interventions. Objective: This study examines the prevalence of PSF, sexual dysfunction, and sexual distress; assesses associations with CHC status; evaluates sexual dysfunction diagnoses; and explores health care preferences. Methods: Data collection in this cross-sectional population-based survey study was based on a questionnaire developed with patient and public involvement and administered by YouGov to a representative sample of adults in Germany. Analyses included 1970 women with and without CHCs and different CHC subgroups (mental health-related, gynecological, cardiovascular and metabolic, infectious and inflammatory, cancer, pain-related, and neurological). The outcomes measured were PSF, clinically relevant sexual dysfunction symptoms, sexual distress (Female Sexual Distress Scale-Desire/Arousal/Orgasm [FSDS-DAO]), and self-reported sexual dysfunction diagnoses. Multivariable regression and network analysis explored associations among CHC subgroups, PSF, sexual dysfunction, and FSDS-DAO scores. Results: Among 1970 cisgender women (mean age 49.6, SD 16.0 years), 1186 (60.2%) reported CHCs. The 6-month PSF prevalence was 75.2% (820/1090) in women with CHCs and 62.5% (399/638) in women without CHCs. Clinically relevant sexual dysfunction symptoms were less prevalent (CHC: 202/1046, 19.3% vs no CHC: 68/601, 11.3%). Multivariable regression models showed an association between sexual dysfunction and CHCs (odds ratio [OR] 2.56, 95% CI 1.90-3.49), which was the strongest for women with mental health-related CHCs (OR 2.31, 95% CI 1.70-3.13) and cancer CHCs (OR 2.00, 95% CI 1.45-2.78). Being in a relationship was a protective factor for clinically relevant distress among women with CHCs. Network analysis showed positive associations of PSF with gynecological and mental health-related CHCs and of sexual dysfunction with mental health-related, gynecological, and cancer CHCs. Women with sexual dysfunction symptoms reported low rates of sexual dysfunction diagnosis (CHC: 39/200, 19.4% vs no CHC: 6/55, 10.7%) and treatment (CHC: 16/146, 11.0% vs no CHC: 3/40, 7.0%). Gynecologists were the preferred health care providers for sexual dysfunction. The most commonly reported unmet need was a lack of information. Digital solutions, such as apps and websites with exercises, were desired as health care innovations. Conclusions: The burden of CHCs on women's sexual health extends beyond functional sexual impairment, with high rates of clinically relevant sexual distress. Cancer and mental health conditions are the strongest predictors of sexual dysfunction. Despite the high prevalence of sexual dysfunction in women with CHCs, access to diagnosis and treatment is limited. Digital offerings could help address these unmet needs.
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) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 ».