67 Using deliberative priority-setting to improve gestational diabetes education
Notice bibliographique
Résumé
Objectives Gestational diabetes mellitus (GDM) education is an important component of GDM management. While pregnancy is thought to be a generally positive experience for women, those with GDM are asked to manage their pregnancy under constant self-discipline to avoid pregnancy complications from hyperglycemia. For many with GDM, this experience is overwhelming. The guidance provided by a multidisciplinary health care team in delivering gestational diabetes education and acknowledging the emotional impact of a diagnosis has shown to improve self-care behaviours and subsequent birth outcomes. This study aims to explore GDM education and care experiences amongst women diagnosed with GDM attending publicly provided education classes at diabetes clinics in Edmonton, Alberta, Canada. Method Deliberative priority-setting was the methodology used as described by the Canadian Institute of Health Research (CIHR) to establish a dialogue throughout six working sessions with 5 women with GDM and 7 diabetes health care providers. Iterative working sessions assessed opinions on educational material provided in classes, feelings and emotions surrounding GDM, and how the healthcare system can improve to better meet their needs. Each session was transcribed and a priority-setting and website assessment surveys were conducted. Results We identified twelve priorities from the priority-setting survey that women wanted to be addressed beyond the existing GDM classes. These include future impacts of GDM on mother and child, blood glucose number interpretation; insulin administration instruction; GDM pathophysiology; how to manage GDM when basic necessities and support are unavailable; language and culture-specific materials; mental health and emotional management and ensuring consistent communication and messaging from health care providers. The working sessions also revealed that the www.diabetes-pregnancy.ca website is a commonly used resource across clinics in this region, however, not all clinicians provided or recommended women visit this site. Through the website assessment survey, women identified inconsistencies within content compared to what was delivered in class and were more interested in having access to site content that focus on patient narrative through text and videos that is relatable to with practical advice that can be applied to daily self-management. Conclusions A priority-setting partnership between women with GDM, healthcare providers, and researchers allowed for honest dialogue on issues relevant to health care providers and women living with GDM. This identified issues that were not adequately addressed in the existing standard GDM education. Women with GDM and health care providers identified the need for consistent and readily accessible information and determined a priority list of items that they would find most helpful. The use of an online resource that women can access before and after attending a GDM education class may help solidify learning and improve self-care behaviours.
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 | 0,050 | 0,072 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,007 | 0,005 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,002 | 0,012 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».