Impact of a Text Messaging Intervention as an In-Between Support to Diabetes Group Visits in Federally Qualified Health Centers: Cluster Randomized Controlled Study
Notice bibliographique
Résumé
Background: In the United States, 1 in 11 people receive primary care from a federally qualified health center (FQHC). Text messaging interventions (TMIs) are accessible ways to deliver health information, engage patients, and improve health outcomes in the health center setting. Objective: We aimed to evaluate the impact of a TMI implemented with a group visit (GV) intervention among patients with type 2 diabetes mellitus (T2DM) at FQHCs on patient-reported outcomes and clinical outcomes based on patient TMI engagement. Methods: A TMI was implemented for 11 health centers participating in a cluster randomized study of diabetes GVs in Midwestern FQHCs targeting adults with T2DM. FQHC patients participated in 6 monthly GVs either in person or online and a concurrent 25-week TMI. Outcome measures included clinical markers such as glycated hemoglobin A1c and patient-reported diabetes distress, diabetes self-care, diabetes self-efficacy, diabetes care knowledge, diabetes quality of life, diabetes social support, and TMI use and satisfaction. TMI response rate was calculated as responses to an SMS text message requesting a response divided by total messages requesting a response sent. Patients were grouped as high responders if their response rate was greater than or equal to the median response rate and low responders if their response rate was below the median. We conducted linear mixed models to compare high and low responders and within a group, adjusting for age, gender, GV attendance, and depression/anxiety at baseline. Results: In total, 101 of 124 GV patients (81.5%) enrolled in the TMI. The average age of the population in the TMI was 53 years. Of the 101 respondents, 61 (60%) were racial or ethnic minorities, while 42 of 82 respondents (51%) had a high school diploma/General Education Development or less, and 56 of 80 respondents (71%) reported an annual income less than US $30,000. In addition, 70 of 81 respondents (86%) owned a smartphone and 74 of 80 respondents (93%) had an unlimited texting plan. The median response rate was 41% and the mean response rate was 41.6%. Adjusted models showed significantly improved diabetes knowledge (P<.001), foot care (P<.001), and exercise (P=.002) in high responders (n=34) compared to low responders (n=23) at 6 months. No group difference was found in glycated hemoglobin A1c. Within high responders, diabetes distress (P=.001), social support (P<.001), quality of life (P<.001), diabetes knowledge (P<.001), foot care (P<.001), and diet (P=.003) improved from baseline to 6 months. Low responders only improved in diabetes quality of life (P=.003) from baseline to 6 months. Conclusions: In a FQHC safety net population participating in a combined TMI and GV intervention, our study showed improved diabetes distress, social support, knowledge, self-care, self-efficacy, and quality of life among patients highly engaged in the SMS text messaging program.
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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 | 0,012 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 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 | 0,000 |
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.
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