A Supplemental Women’s Health Questionnaire for Women Veterans With Military Environmental Exposures: Project Development and Implementation
Notice bibliographique
Résumé
Background: The number of women in the armed forces has steadily increased across all branches, even as the overall size of the military remains stable. The population of women veterans is also expanding. The existing literature has extensively reported the impact of military environmental exposures (MEEs) on adverse physical and mental health outcomes in service members and veterans; however, most of these studies focus on the experiences of men. In response to the growing need to address women-specific health care concerns, particularly for women with MEEs, the Women's Operational Military Exposure Network Center of Excellence (WOMEN CoE) developed and implemented the Women's Health Addendum (WHA). Objective: The primary objective of this project is to (1) describe the development and implementation of a comprehensive health questionnaire for women veterans, (2) systematically describe and characterize the health conditions of women seeking care for MEE-related health concerns, and (3) use findings to inform clinic policies and develop targeted programs. Methods: The WHA was introduced to assess the prevalence of health conditions that are female-specific, or disproportionately impact women; examine the relationship between these health conditions and MEEs; and use findings to improve care. The WHA was developed through an iterative process, incorporating literature review, veteran and clinician feedback, and clinical expertise. It consists of 81 questions across 7 categories related to health conditions across the lifespan and was implemented in 2 phases. Phase 1 was administered to women at the California War Related Illness and Injury Study Center (WRIISC), and phase 2 included women at the New Jersey and Washington, DC, WRIISC sites. Descriptive findings are presented here. Results: A total of 63 women participated in the program evaluation from October 2022 to April 2024. In phase 1, 39% (29/75) of the women who were invited agreed to participate. In phase 2, 34 (10%) of the 325 invited veterans responded. Several women's health conditions were reported, with approximately 97% (61/63) of women reporting at least one health condition and 87% (55/63) reporting 3 or more. Among respondents, the most prevalent conditions included sexual dysfunction (23/33, 70%), urinary incontinence (33/56, 59%), pelvic floor dysfunction (33/63, 52%), and pregnancy loss (20/45, 44%). Overall, more than 40% (3/7) of the most frequent conditions were related to urinary health and pelvic floor dysfunction. Conclusions: Findings highlight the need for services related to women's health, especially for this cohort with MEE concerns seen at a tertiary care center. Initial findings emphasize concerns that women have about fertility and MEE experienced during deployments. Next steps include administering the WHA to women at sister WRIISC sites in real time and establishing a wider distribution network for the WHA. Future efforts to further evaluate the relationship between MEE and women's health concerns are underway.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
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 source (Gemma direct ou Codex distillé), 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 ».