Improving Self-management of Type 2 Diabetes in Latinx Patients: Protocol for a Sequential Multiple Assignment Randomized Trial Involving Community Health Workers, Registered Nurses, and Family Members
Notice bibliographique
Résumé
BACKGROUND: The rate of Type 2 diabetes mellitus (T2DM) among Mexican American individuals is 16.3%, about twice that of non-Hispanic White individuals. While a number of education approaches have been developed and shown to improve diabetes self-management behaviors and glycemic control for Spanish-speaking Latinx patients with T2DM, there is little research to guide health practitioners regarding which interventions to apply and when so that resources are used efficiently, and treatment outcomes are maximized. OBJECTIVE: This study aimed to describe an adaptive intervention that integrates community mental health workers, diabetes nurse educators, family members, and patients as partners in care while promoting diabetes self-management for Mexican American individuals with T2DM. The project incorporates four evidence-based, culturally tailored treatments to determine what sequence of intervention strategies work most efficiently and for whom. Given the increasing prevalence of T2DM, achieving better control of diabetes and lowering the associated medical complications experienced disproportionally by Mexican American individuals is a public health priority. METHODS: Funded by the National Institute of Nursing Research (National Institutes of Health grant R01 NR015809), this project used a sequential multiple assignment randomized trial and included 330 Spanish-speaking Latinx patients with T2DM. In the first phase of the study, subjects were randomly assigned to an evidence-based diabetes self-management educational program called Tomando Control delivered in a group format for 6, biweekly 1.5-hour sessions, led either by a community health worker or a diabetes nurse educator. In the second phase of the study, those subjects who did not improve their diabetes self-management behaviors were rerandomized to receive either an augmented version of Tomando Control or a multifamily group treatment focused on problem-solving. The primary outcome measure was the "Summary of Diabetes Self-Care Activities." Evaluations were made at baseline and at 3, 6, and 12 months. RESULTS: This study was funded in June 2016 for a period of 5 years. Institutional review board approval was obtained in November 2016. Between March 2017 and September 2020, a total of 330 patients were recruited from the outpatient primary care clinics of Olive View-UCLA Medical Center, with a brief hiatus between May 2020 and July 2020 due to COVID-19 restrictions. The study interventions were completed in December 2020. Data collection began in March 2017 and was completed in December 2021. Data analysis is expected to be completed in Spring 2023, and results will be published in Fall 2023. CONCLUSIONS: The results of this trial should help practitioners in selecting the optimal approach for improving diabetes self-management in Spanish-speaking, Latinx patients with T2DM. TRIAL REGISTRATION: ClinicalTrials.gov NCT03092063; https://clinicaltrials.gov/ct2/show/NCT03092063. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44793.
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 | 0,020 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,004 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,051 | 0,008 |
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 ».