Virtual Diabetes Prevention Program Tailored to Increase Participation of Black and Latino Men: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Black and Latino men are at increased risk for poor diabetes health outcomes but are underrepresented in lifestyle interventions for weight loss and diabetes prevention. Although relatively few men participate in the National Diabetes Prevention Program (NDPP), it remains the most widely available evidence-based approach to type 2 diabetes prevention in the United States. Thus, an NDPP tailored to Black and Latino men has the potential to address prior limitations of NDPP implementation and reduce gender, racial, and ethnic diabetes disparities. It also provides an opportunity to define a population for targeted outreach and evaluate the reach of our recruitment methods and interventions. OBJECTIVE: We tailored the US Centers for Disease Control and Prevention Prevent T2 curriculum for the NDPP for Black and Latino men, called Power-Up, and will evaluate its effects in comparison to standard mixed-gender NDPP groups via virtual delivery. The primary aim of the project is to assess the effect of Power-Up versus NDPP on weight loss among men with prediabetes. The secondary aim is to compare the engagement and retention of men with prediabetes in Power-Up versus NDPP. We will also examine the reach of our recruitment methods and engagement in our screening, consenting, and assessment procedures prior to the point of randomization. We hypothesized that men randomized to Power-Up would achieve greater percent weight loss from baseline at 16 weeks (end of Core sessions) and 1 year (end of Maintenance sessions) than men randomized to standard, mixed-gender NDPP. Power-Up is also expected to have better engagement and retention. METHODS: Using the electronic health record (EHR) systems of a large academic medical center and a network of small to medium independent primary care practices throughout New York City, we identified Black and Latino men who met eligibility criteria for NDPP and enrolled them in a randomized controlled trial in which they were assigned 1:1 to receive Power-Up or the standard, mixed-gender NDPP over 1 year via online videoconferencing. Coaches delivering these interventions were trained according to the standards for the NDPP. Power-Up will be delivered by men coaches. Weight will be collected with home-based electronic scales for primary outcome analyses. Engagement will be assessed by session attendance logs. RESULTS: We identified 11,052 men for outreach based on EHR data, successfully screened 26% of them, consented and enrolled 22% of these, and randomly assigned 48% of consented participants. Primary and secondary outcome analyses will be assessed among randomized men. CONCLUSIONS: This study highlights the effort required to reach and engage Black and Latino men for virtually delivered diabetes prevention programs. Forthcoming trial results for weight loss and engagement will further inform efforts to address disparities in diabetes prevention through tailored programming for Black and Latino men. TRIAL REGISTRATION: ClinicalTrials.gov NCT04104243; https://clinicaltrials.gov/study/NCT04104243. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64405.
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 | 0,030 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,004 |
| Méta-épidémiologie (sens large) | 0,012 | 0,006 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,101 | 0,014 |
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 ».