Community case management of malaria: exploring support, capacity and motivation of community medicine distributors in Uganda
Notice bibliographique
Résumé
BACKGROUND: In Uganda, community services for febrile children are expanding from presumptive treatment of fever with anti-malarials through the home-based management of fever (HBMF) programme, to include treatment for malaria, diarrhoea and pneumonia through Integrated Community Case Management (ICCM). To understand the level of support available, and the capacity and motivation of community health workers to deliver these expanded services, we interviewed community medicine distributors (CMDs), who had been involved in the HBMF programme in Tororo district, shortly before ICCM was adopted. METHODS: Between October 2009 and April 2010, 100 CMDs were recruited to participate by convenience sampling. The survey included questionnaires to gather information about the CMDs' work experience and to assess knowledge of fever case management, and in-depth interviews to discuss experiences as CMDs including motivation, supervision and relationships with the community. All questionnaires and knowledge assessments were analysed. Summary contact sheets were made for each of the 100 interviews and 35 were chosen for full transcription and analysis. RESULTS: CMDs faced multiple challenges including high patient load, limited knowledge and supervision, lack of compensation, limited drugs and supplies, and unrealistic expectations of community members. CMDs described being motivated to volunteer for altruistic reasons; however, the main benefits of their work appeared related to 'becoming someone important', with the potential for social mobility for self and family, including building relationships with health workers. At the time of the survey, over half of CMDs felt demotivated due to limited support from communities and the health system. CONCLUSIONS: Community health worker programmes rely on the support of communities and health systems to operate sustainably. When this support falls short, motivation of volunteers can wane. If community interventions, in increasingly complex forms, are to become the solution to improving access to primary health care, greater attention to what motivates individuals, and ways to strengthen health system support are required.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».