Codevelopment of a Shared Decision-Making Resource Platform for Women and Girls in 3 Low- and Middle-Income Countries (ENGAGEEs): Protocol for a Participatory Research Project (Preprint)
Notice bibliographique
Résumé
BACKGROUND Women and girls around the world face significant barriers in participating in health care decisions, particularly in low- and middle-income countries. Despite growing interest in shared decision-making (SDM), little is known about its implementation in these countries, and no rigorous assessment of the decision-making needs of women and girls in these contexts has been conducted. There is little SDM training and there are few decision-support tools (DSTs) specifically designed for health care decision-making by women and girls in these countries. DSTs (paper or digital) present options and probabilities and help users articulate their values and preferences. OBJECTIVE We aim to codevelop an SDM resource platform, including locally relevant DSTs and instructional materials, to support SDM with women and girls in Brazil, Cameroon, and Senegal. METHODS We will conduct a 4-phase participatory research project. We will use the Gender-Based Analysis Plus tool to support inclusive participatory research throughout the study. First, we will follow the Integrated Knowledge Translation framework to form a local steering committee in each country, including patients and community representatives, health and social service professionals, and decision-makers. Second, we will follow the Ottawa Decision Support Framework to conduct individual interviews and focus groups to identify the decision-making needs of women and girls. We will include 20 women and girls, along with their family members, 15 health and social service professionals, and 15 representatives of community-based organizations in each country (n=150). The Double Diamond human-centered design framework will be used to codevelop a digital SDM resource platform where DSTs and instructional materials for SDM training can be made accessible. Finally, we will assess the scalability of the platform by using the Innovation Scalability Self-Administered Questionnaire. We will report our study by using the Standards for Reporting Qualitative Research guideline and the Guidance for Reporting Involvement of Patients and the Public. RESULTS Financial support for this project was received on February 1, 2023. This protocol was submitted during data collection but before analysis. Data collection began in January 2025. By July 2025, 92 of the 150 participants had been recruited. We expect to publish our results in December 2026. CONCLUSIONS Ultimately, more women and girls from low- and middle-income countries will be involved in health care decisions, and more clinical teams will be able to integrate SDM into their care practices. The local steering committees will ensure equitable partnerships and the SDM resource platform will promote more inclusive approaches to SDM worldwide. The scalability assessment will help us plan to expand the impact of the platform to other regions. CLINICALTRIAL INTERNATIONAL REGISTERED REPORT DERR1-10.2196/78618
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 | 0,072 | 0,055 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,053 | 0,008 |
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 ».