Understanding factors influencing antibiotic prescribing behaviour in rural China: a qualitative process evaluation of a cluster randomized controlled trial
Notice bibliographique
Résumé
Objectives We conducted a qualitative process evaluation embedded in a cluster randomized controlled trial in rural Guangxi China, which successfully reduced antibiotic use for children upper respiratory tract infections. This study aims to report on the factors that influenced behaviour change among providers and caregivers in the intervention arm, and to explore contextual considerations which may have influenced trial outcomes. Methods A total of 35 in-depth interviews were carried out with hospital directors, doctors, and caregivers of children. Participants were recruited from six purposively selected facilities, including two higher performing and two lower performing facilities per trial results. Interviews were conducted in Chinese and translated to English. We also observed guideline training sessions and prescription peer review meetings. Data were analysed using framework analysis. Results Intervention-arm doctors described that training sessions improved their knowledge, skills and confidence in appropriate prescribing. This was contrasted by control arm participants who did not receive training and reported less agency in reducing prescribing rates. Prescription peer review meetings were seen as an opportunity for further education, action planning and goal setting, particularly in high performing hospitals, where these meetings were led by senior doctors who were perceived to have relevant clinical experience. Caregiver participants reported that intervention educational materials were helpful but they identified information from doctors was more useful. Providers and caregivers also described contextual health system factors, including hospital competition, short consultation times, and antibiotic availability without prescription, which shaped care preferences. Conclusions This qualitative process evaluation identified a range of factors that may have influenced behaviour among providers and caregivers leading to observed changes in reducing inappropriate antibiotic prescribing in China. Future interventions to reduce antibiotic prescribing should consider system level and wider contextual factors to better understand behaviours and patient care preferences.
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 | 0,020 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 |
| 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 ».