Impact of mHealth-Augmented Social Support on Health Care Use Among Patients With Diabetes: Secondary Analysis of the TExT-MED+FANS Trial
Notice bibliographique
Résumé
Background: The rising cost of unscheduled acute health care, particularly for emergency department (ED) visits, poses significant financial burdens. In 2021, aggregate costs for treat-and-release ED visits in the United States accounted for an estimated US $80 billion, while the total annual cost of diabetes was US $412.9 billion in 2022-representing about 1 in every 4 health care dollars, 61% of which are directly linked to diabetes. Objective: This study explores the impact of a mobile health (mHealth) intervention with augmented social support delivered via guided SMS text messaging on health care use among patients with diabetes through a secondary analysis of the TExT-MED+FANS (Trial to Examine Text-Messaging in Emergency Patients With Diabetes + Family and Friends Network Support) randomized controlled trial. Methods: The trial involved 173 participants randomized into either a FANS mHealth-augmented social support or an active control group that received the same support curriculum via mailed pamphlet; "augmented" social support refers to recruiting both individuals with diabetes and a designated family member or friend ("supporter") to participate. Supporters in the FANS arm received structured SMS guidance on how to assist the participant with diabetes in managing their condition. Health care use outcomes, including ED visits, hospitalizations, and clinic visits, were compared between groups during and after the intervention period using linear regression models on change in health care visits in the last year, with subgroup analysis by participant sex and supporter relationship. Results: Results showed significant reductions in acute unscheduled care visits for both groups during and after the intervention, with the FANS group experiencing a reduction of 1.04 visits during the intervention and 1.10 visits after the intervention, while the mailed pamphlet group had reductions of 1.47 and 1.53 visits, respectively (both P<.001). Clinic visits increased by 1.78 during the intervention phase (P=.01) but were not sustained postintervention. Hospitalizations modestly decreased in both groups, but the decrease was statistically significant only for the mailed pamphlet group (P=.002). Sex and supporter relationship differences were observed, with females supported by spouses in the active control group showing the largest decrease in unscheduled care visits. Conclusions: The findings suggest that mHealth interventions combined with structured social support can improve diabetes management and reduce health care costs. Although these conclusions are specific to this study, they align with prior research demonstrating the benefits of social support and mHealth interventions. These findings may inform future programs, including the design of low-cost, scalable interventions in resource-limited settings.
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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 | 0,005 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,007 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
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 ».