A Feminine Care Clinical Research Program Transforms Women’s Lives
Notice bibliographique
Résumé
Feminine hygiene products and menstruation education have transformed the lives of women throughout the world. The P&G Feminine Care Clinical Innovation Research Program has played a key role by expanding scientific knowledge as well as developing technical insights and tools for the development of feminine hygiene products. The aim has been to meet the needs of women throughout their life stages, advancing their urogenital health beyond just menstruation, as well as helping to understand the role of sex hormones in various important health issues that women face. This review article highlights key contributions and research findings in female hygiene products, urogenital health research, and method development. The clinical research team focused on utilizing the results of clinical safety studies to advance the acceptance of feminine hygiene products world-wide. Key findings include that perception of skin sensitivity is not limited to the facial area, but is also relevant to the body and the genital area. Also, they shed light on the role of estrogen in autoimmune diseases as well as premenstrual syndrome. Efforts in the method development area focused on innovative tools that are reliable, predictive of clinical trial results and capable of measuring wear comfort, genital skin health, and the impact of product use on the consumer's quality of life. A novel method, behind-the-knee (BTK) test, developed to model irritation under normal wear conditions, was the first to account for both chemical and mechanical sources of irritation. The method has been accepted by the FDA as a substitute in clinical trials in some cases, and by American Society for Testing and Materials as a global standard test method. Additional proprietary methods were developed to enhance visual grading of irritation using cross-polarized light, to measure the amount of lotion transferred from sanitary pads, and to evaluate the skin mildness. Finally, the Farage Quality of Life tool was created to measure consumer's well-being. Based on the results of this extensive clinical research and the newly developed testing methods, the changing needs of women throughout their life stages are better met.
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 | 0,019 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 ».