MétaCan
Menu
← Retour à la cohorte
Enregistrement W3037683591 · doi:10.1101/2020.06.28.20141663

Improving maternal, newborn, and child health outcomes through a community-based women’s health education program ( <i>Chamas for Change</i> ): a cluster randomized controlled trial

2020· preprint· en· W3037683591 sur OpenAlexafffund
Lauren Y. Maldonado, Jeffrey N. Bone, Michael Scanlon, Gertrude Anusu, Sheilah Chelagat, Anjellah Jumah, Justus E. Ikemeri, Julia Songok, Astrid Christoffersen‐Deb, Laura J. Ruhl

Notice bibliographique

RevuemedRxiv · 2020
Typepreprint
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensUniversity of TorontoUniversity of British Columbia
Organismes subventionnairesUniversity of Toronto
Mots-clésRandomized controlled trialMedicineCluster randomised controlled trialHealth facilityCommunity healthCluster (spacecraft)Intervention (counseling)Logistic regressionPregnancyFamily medicineDemographyPopulationPediatricsEnvironmental healthPublic healthNursingHealth services

Résumé

récupéré en direct d'OpenAlex

ABSTRACT Introduction Community-based women’s health education groups may improve maternal, newborn, and child health (MNCH); however, evidence from sub-Saharan Africa is lacking. Chamas for Change (Chamas) is a community health volunteer (CHV)-led health education program for pregnant and postpartum women in western Kenya. We evaluated Chamas ’ effect on facility-based deliveries and other MNCH outcomes. Methods We conducted a cluster randomized controlled trial involving 74 communities in Trans Nzoia County. We included pregnant women who presented to health facilities for their first antenatal care visits by 32 weeks gestation. We randomized community clusters 1:1 without stratification or matching; we masked data collectors, investigators, and analysts to allocation. Intervention clusters were invited to bimonthly, group-based, CHV-led health lessons ( Chamas ); control clusters had monthly CHV home-visits (standard of care). The primary outcome was facility-based delivery at 12-months follow-up. We conducted an intention-to-treat approach with multilevel logistic regression models using individual-level data. We prospectively registered this trial with ClinicalTrials.gov ( NCT03187873 ). Results Between November 27, 2017 and March 8, 2018, we enrolled 1920 participants from 37 intervention and 37 control clusters. A total of 1550 (80.7%) participants completed the study with 822 (82.5%) and 728 (78.8%) in the intervention and control arms, respectively. Facility-based deliveries improved in the intervention arm (80.9% vs 73.0%; Risk Difference (RD) 7.4%, 95% CI 3.0-12.5, OR=1.58, 95% CI 0.97-2.55, p=0.057). Chamas participants also demonstrated higher rates of 48-hour postpartum visits (RD 15.3%, 95% CI 12.0-19.6), exclusive breastfeeding (RD 11.9%, 95% CI 7.2-16.9), contraceptive adoption (RD 7.2%, 95% CI 2.6-12.9), and infant immunization completion (RD 15.6%, 95% CI 11.5-20.9). Conclusion Chamas participation was associated with significantly improved MNCH outcomes compared with the standard of care. This trial contributes robust data from sub-Saharan Africa to support community-based, women’s health education groups for MNCH in resource-limited settings. KEY QUESTIONS What is already known? Globally, maternal and infant deaths have declined over the last three decades; however, low and middle-income countries (LMICs), including Kenya, still disproportionately incur the highest morbidity and mortality. The World Health Organization recommends leveraging lay health workers (LHWs), including community health volunteers (CHVs), to promote maternal, newborn, and child health (MNCH) in resource-limited settings. Prior research suggests coupling strategies that promote community-based approaches (i.e. integrating LHWs) and women’s health education and support groups during pregnancy and postpartum may improve MNCH; however, robust evidence from sub-Saharan Africa is lacking. What are the new findings? Using a cluster randomized controlled trial design, we found that participation in Chamas for Change (Chamas) – a group-based women’s health education program led by CHVs – was associated with significantly improved MNCH outcomes, including facility-based deliveries, compared with the standard of care (i.e. monthly home-visits) in rural Kenya. This trial also demonstrated significant associations between program participation and receiving 48 hour postpartum home-visits, breastfeeding exclusively, adopting a contraceptive method postpartum, and immunizing infants fully by 12 months of life as compared to the standard of care. These findings support pilot data from a preceding evaluation of the Chamas program as well as the current literature on community-based interventions delivered by LHWs to promote MNCH in other resource-limited settings. What do the new findings imply? Effective community-based strategies that build upon existing infrastructure to promote MNCH are needed to continue to improve the health and well-being of women and infants in rural sub-Saharan Africa and other LMICs. Chamas offers an innovative approach to improve MNCH in resource-limited settings with significant health policy implications; collective evidence from this trial and preceding studies support community-based women’s health education groups as an effective strategy for improving uptake of facility-based deliveries and other life-saving MNCH practices.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,025

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,005
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0020,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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.

Tête enseignante Opus0,043
Tête enseignante GPT0,359
Écart entre enseignants0,316 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revuemedRxiv→Même sujetGlobal Maternal and Child Health→Travaux en français237 207→