Quality of Pre-Service Midwifery Education in Public and Private Midwifery Schools in Afghanistan: A Cross Sectional Survey
Notice bibliographique
Résumé
Abstract Background Midwives are the key skilled birth attendants in Afghanistan. Rapid assessment of public and private midwifery education schools was conducted in 2017 to examine compliance with national educational standards. Aim was to assess midwifery education to inform Afghanistan Nurses and Midwives Council and other stakeholders priorities for improving quality of midwifery education. Methods A cross-sectional assessment was conducted from September 12–December 17, 2017, using a modified Midwifery Education Rapid Assessment Tool to assess education quality aspects related to infrastructure, management, teachers, preceptors, clinical practice sites, curriculum and students in 29 midwifery schools. A purposive sample of six Institute of Health Sciences schools, seven Community Midwifery Education schools and 16 private midwifery schools was used. Participants were midwifery school staff, students and clinical preceptors. Results Libraries were available in 28/29 (97%) schools, active skills labs in 20/29 (69%), childbirth simulators in 17/29 (59%) and newborn resuscitation models in 28/29 (97%). School managers were midwives in 21/29 (72%) schools. Median numbers of students per teacher and students per preceptor were 8 (range 2–50) and 6 (range 2–20). There were insufficient numbers of teachers practicing midwifery (132/163; 81%), trained in teaching skills (113/163; 69%) and trained in emergency obstetric and newborn care (88/163; 54%). There was an average of 13 students at clinical sites in each shift. Students managed an average of 15 births independently during their training, while 40 births are required. Twenty-four percent (7/29) of schools used the national 2015 curriculum alone or combined with an older one. Ninety-one percent (633/697) of students reported access to clinical sites and skills labs. Students mentioned, however, insufficient clinical practice, lack of education materials, transport facilities and disrespect from school teachers, preceptors and clinical site providers as challenges. Conclusions Positive findings included availability of required infrastructure, amenities, approved curricula in 7 of the 29 midwifery schools, appropriate clinical sites and students’ commitment to work as midwives upon graduation. Gaps identified were use of different often outdated curricula, inadequate clinical practice, underqualified teachers and preceptors and failure to graduate all students with sufficient skills such as independently having supported 40 births.
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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».