Validity and reliability of data collected by community health workers in rural and peri-urban contexts in Kenya
Notice bibliographique
Résumé
Reliability and validity of measurements are important for the interpretation and generalisation of research findings. Valid, reliable and comparable measures of health status of individuals are critical components of the evidence base for health policy. The need for sound information is especially urgent in the case of emerging diseases and other acute health threats, where rapid awareness, investigation and response can save lives and prevent broader national outbreaks and even global pandemics. Several successfully implemented health interventions have involved community health workers (CHWs) in reaching out to the community, and the Community Health Strategy is one such an intervention. The government of Kenya, through the Ministry of Public Health and Sanitation has rolled out the strategy as a way of improving health care at the household level. It involves CHWs collecting health status data at the household level, which is presented at community meetings in which the community discusses the results, identifies action areas, and plans activities for improving their health status. Ten percent of all households visited by CHWs for data collection in different sites (rural and peri-urban) were systematically selected and visited a second time by technically trained research team members. The test-retest method was applied to establish reliability. The Kappa score was used to measure reliability, while sensitivity, specificity, and positive predictive values were used to measure validity. Inter-observer agreement between the two sets of data in both sites was good; most indicators measured slight agreement. However, some indicators demonstrated greater discrepancies between the two data sets (e.g. measles immunization). Specificity measures were more stable in Butere (rural), which had more than 90% in all the indicators tested, compared to Nyalenda (peri-urban), which fluctuated between 50% and 90%. There were variable reliability results in the peri-urban site for the indicators measured, while the rural site presented more stable results. This is also depicted in the validity measures in both sites. The paper concludes that there are convincing results that CHWs can accurately and reliably collect certain types of community data which has cost-saving implications, especially for resource poor settings.
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 | 0,027 | 0,065 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».