Risk factors for childhood illness and death in rural Uttar Pradesh, India: perspectives from the community, community health workers and facility staff
Notice bibliographique
Résumé
BACKGROUND: Uttar Pradesh (UP), India continues to have a high burden of mortality among young children despite recent improvement. Therefore, it is vital to understand the risk factors associated with under-five (U5) deaths and episodes of severe illness in order to deliver programs targeted at decreasing mortality among U5 children in UP. However, in rural UP, almost every child has one or more commonly described risk factors, such as low socioeconomic status or undernutrition. Determining how risk factors for childhood illness and death are understood by community members, community health workers and facility staff in rural UP is important so that programs can identify the most vulnerable children. METHODS: This qualitative study was completed in three districts of UP that were part of a larger child health program. Twelve semi-structured interviews and 21 focus group discussions with 182 participants were conducted with community members (mothers and heads of households with U5 children), community health workers (CHWs; Accredited Social Health Activists and Auxiliary Nurse Midwives) and facility staff (medical officers and staff nurses). All interactions were recorded, transcribed and translated into English, coded and clustered by theme for analysis. The data presented are thematic areas that emerged around perceived risk factors for childhood illness and death. RESULTS: There were key differences among the three groups regarding the explanatory perspectives for identified risk factors. Some perspectives were completely divergent, such as why the location of the housing was a risk factor, whereas others were convergent, including the impact of seasonality and certain occupational factors. The classic explanatory risk factors for childhood illness and death identified in household surveys were often perceived as key risk factors by facility staff but not community members. However, overlapping views were frequently expressed by two of the groups with the CHWs bridging the perspectives of the community members and facility staff. CONCLUSION: The bridging views of the CHWs can be leveraged to identify and focus their activities on the most vulnerable children in the communities they serve, link them to facilities when they become ill and drive innovations in program delivery throughout the community-facility continuum.
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,006 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,003 |
| 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 ».