Challenges to achieving appropriate and equitable access to Caesarean section: ethnographic insights from rural Pakistan
Notice bibliographique
Résumé
Access to Caesarean section (C-section) remains inadequate for some groups of women while others have worryingly high rates. Understanding differential receipt demands exploration of the socio-cultural, and political economic, characteristics of the health systems that produce them. This extensive institutional ethnography investigated under- and over-receipt of C-section in two rural districts in Pakistan - Jhelum and Layyah. Data were collected between November and July 2013 using semi-structured interviews from a randomly selected sample of 11 physicians, 38 community midwives, 18 Lady Health Visitors and nurses and 15 Traditional Birth Attendants. In addition, 78 mothers, 35 husbands and 23 older women were interviewed. The understandings of birth by C-section held by women and their family members were heavily shaped by gendered constructions of womanhood, patient-provider power differentials and financial constraints. They considered C-section an expensive and risky procedure, which often lacked medical justification, and was instead driven by profit motive. Physicians saw C-section as symbolizing obstetric skill and status and a source of legitimate income. Physician views and practices were also shaped by the wider health care system characterized by private practice, competition between providers and a lack of regulation and supervision. These multi-layered factors have resulted in both unnecessary intervention, and missed opportunities for appropriate C-sections. The data indicate a need for synergistic action at patient, provider and system levels. Recommendations include: improving physician communication with patients and family so that the need for C-section is better understood as a life-saving procedure, challenging negative attitudes and promoting informed decision-making by mothers and their families, holding physicians accountable for their practice and introducing price caps and regulations to limit financial incentives associated with C-sections. The current push for privatization of health care in low-income countries also needs scrutiny given its potential to encourage unnecessary intervention.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».