The Use of Text Messaging to Improve the Hospital-to-Community Transition in Acute Coronary Syndrome Patients (Txt2Prevent): Intervention Development and Pilot Randomized Controlled Trial Protocol
Notice bibliographique
Résumé
BACKGROUND: Acute coronary syndrome, including acute myocardial infarction (AMI), is one of the leading causes for hospitalization, with AMI 30-day readmission rates around 20%. Supporting patient information needs and increasing adherence to recommended self-management behaviors during transition from hospital to home has the potential to improve patient outcomes. Text messages have been effective in other interventions and may be suitable to provide support to patients during this transition period. OBJECTIVE: The goal of this study is to pilot test a text messaging intervention program (Txt2Prevent) that supports acute coronary syndrome patients for 60 days postdischarge. The primary objective is to compare self-management, as measured by the Health Education Impact Questionnaire, between patients receiving only usual care versus those who receive usual care plus the Txt2Prevent intervention. The secondary objectives are to compare medication adherence, health-related quality of life, self-efficacy, health care resource use (and associated costs), all-cause and cardiovascular disease (CVD) readmission, and all-cause and CVD mortality rates between the 2 groups. The third objective is to assess acceptability of the text messaging intervention and feasibility of the study protocol. METHODS: This is a randomized controlled trial with blinding of outcome assessors. The Txt2Prevent program includes automated text messages to patients about standard follow-up care, general self-management, and healthy living. The content of the text messages was informed by and developed based on interviews with patients, discharge materials, theoretical domains of behavior, and a clinical advisory group composed of patients, clinicians, and researchers. We will recruit 76 consecutive cardiac in-patients with acute coronary syndrome who are treated with either medical management or percutaneous coronary intervention from a hospital in Vancouver, Canada. RESULTS: Assessments at baseline will include measures for demographic information, self-management, health-related quality of life, and self-efficacy. Assessments at follow-up will include medication adherence, readmissions, health care resource use, and mortality in addition to the reassessment of baseline measures. Baseline assessments are done in-person while follow-up assessments are completed through a combination of mailed packages and phone calls. Semistructured interviews with participants will also be performed to better understand participant experiences managing their condition and with the text messages. CONCLUSIONS: This study will determine preliminary efficacy, feasibility, and acceptability of the Txt2Prevent program to support acute coronary syndrome patients in the transition to home following hospital discharge. The results of this study will be used to inform a larger trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT02336919; https://clinicaltrials.gov/ct2/show/NCT02336919 (Archived by WebCite at http://www.webcitation.org/6qMjEqo6O).
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 | 0,013 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,002 |
| Méta-épidémiologie (sens large) | 0,007 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,047 | 0,006 |
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 ».