A Digital Health Intervention to Lower Cardiovascular Risk
Notice bibliographique
Résumé
IMPORTANCE: South Asian individuals have a high burden of premature myocardial infarction (MI). OBJECTIVES: To test whether a digital health intervention (DHI) designed to change diet and physical activity improves MI risk among a South Asian population. DESIGN, SETTING, AND PARTICIPANTS: This single-blind, community-based, randomized clinical trial with 1-year follow-up was performed among South Asian men and women 30 years or older and living in Ontario and British Columbia who were free of cardiovascular disease. Data analysis was by intention to treat. Data were collected from June 3, 2012, to October 27, 2013. Final follow-up was completed on December 2, 2014, and data were analyzed from April 2, 2015, to February 29, 2016. INTERVENTIONS: Participants were randomized 1:1 to the DHI or control condition. The goal-setting DHI used emails or text messages and focused on improving diet and physical activity that was tailored to the participant's self-reported stage of change. MAIN OUTCOMES AND MEASURES: The change in an MI risk score from baseline to 1 year was the primary outcome. Secondary outcomes included the change in each objectively measured component of the MI risk score (ie, blood pressure, waist to hip ratio, hemoglobin A1c level, and the ratio of apolipoprotein B to apolipoprotein A). Genetic risk for MI was determined by counting the 9p21 risk alleles; results were provided to each participant at baseline. RESULTS: A total of 343 South Asian men and women (178 men [51.9%]; mean [SD] age, 50.6 [11.4] years) who were free of cardiovascular disease were randomized to the control condition (n = 174) or the DHI (n = 169). The mean (SD) MI risk score was 13.3 (6.6) at baseline. No significant difference was found in the change in MI score after 1 year between the DHI and control groups (-0.27; 95% CI, -1.12 to 0.58; P = .53) after adjusting for baseline scores, and no difference was found in the fully adjusted model (-0.39; 95% CI, -1.24 to 0.45; P = .36). No association between knowledge of the genetic risk status at baseline and the change in MI risk score was found (0.19; 95% CI, -0.40 to 0.78; P = .53). CONCLUSIONS AND RELEVANCE: Among South Asian individuals, a DHI was not associated with a reduction in MI risk score after 12 months and was not influenced by knowledge of genetic risk status. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01841398.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,005 |
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 tête enseignante, 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 ».