A Mobile Clinical Decision Support System for High-Risk Pregnant Women in Rural India (SMARThealth Pregnancy): Pilot Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in women in India. Early identification is crucial to reducing deaths. Hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) carry independent risks for future CVD, and antenatal care is a window to screen and counsel high-risk women. In rural India, community health workers (CHWs) deliver antenatal and postnatal care. We developed a complex intervention (SMARThealth Pregnancy) involving mobile clinical decision support for CHWs and evaluated it in a pilot cluster randomized controlled trial (cRCT). OBJECTIVE: The aim of the study is to co-design a theory-informed intervention for CHWs to screen, refer, and counsel pregnant women at high risk of future CVD in rural India and evaluate its feasibility and acceptability. METHODS: In phase 1, we used qualitative methods to explore community priorities for high-risk pregnant women in rural areas of 2 diverse states in India. In phase 2, informed by behavior change theory and human-centered design, we used these qualitative data to develop the intervention components and implementation strategies for SMARThealth Pregnancy in an iterative process with end users. In phase 3, using mixed methods, we evaluated the intervention in a cRCT with an embedded qualitative substudy across 4 primary health centres: 2 in Jhajjar district, Haryana, and 2 in Guntur district, Andhra Pradesh. RESULTS: SMARThealth Pregnancy embedded a total of 15 behavior change techniques and included (1) community awareness programs; (2) targeted training, including point-of-care blood pressure and hemoglobin measurement; and (3) mobile clinical decision support for CHWs to screen women in their homes. The intervention focused on 3 priority conditions: anemia, HDP, and GDM. The evaluation involved a total of 200 pregnant women, equally randomized to intervention or enhanced standard care (control). Recruitment was completed within 5 months, with minimal loss to follow-up (4/200, 2%) at 6 weeks postpartum. A total of 4 primary care doctors and 54 CHWs in the intervention clusters took part in the study. Fidelity to intervention practices was 100% prepandemic. Over half the study population was affected by moderate to severe anemia at baseline. The prevalence of HDP (2.5%) and GDM (2%) was low in our study population. Results suggest a possible improvement in mean hemoglobin (anemia) in the intervention group, although an adequately powered trial is needed. The model of home-based care was feasible and acceptable for pregnant or postpartum women and CHWs, who perceived improvements in quality of care, self-efficacy, and professional recognition. CONCLUSIONS: SMARThealth Pregnancy is an innovative model of home-based care for high-risk pregnant women during the transitions between antenatal and postnatal care and adult health services. The use of theory and co-design during intervention development facilitated acceptability of the intervention and implementation strategies. Our experience has informed the decision to initiate a larger-scale cRCT. TRIAL REGISTRATION: ClinicalTrials.gov NCT03968952; https://clinicaltrials.gov/ct2/show/NCT03968952. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fgwh.2021.620759.
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 | 0,004 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
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 ».