EXPLORING MODELS OF CARE WITH A TEXT MESSAGE-BASED INTERVENTION FOR ADOLESCENTS AND YOUNG ADULTS WITH BENIGN HEMATOLOGICAL DISEASE
Notice bibliographique
Résumé
BACKGROUND: Adolescents and young adults (AYA) with chronic diseases transitioning from pediatric care to adult care have unique needs that are often neglected. As AYA learn to manage their schedules, the most commonly reported reason for missed appointments was forgetfulness. Studies have shown using short message service (SMS) to remind patients of clinic appointments can reduce missed appointments and improve young patients’ engagement in the management of their chronic disease. OBJECTIVES: We sought to integrate mobile technology into an AYA transitional care clinic via SMS reminders to notify patients of scheduled appointments, and measure the impact of this technology on compliance and no-show rates in the clinic. A secondary objective was to identify the characteristics and needs of a cohort of AYA patients. DESIGN/METHODS: We conducted a pre- and post- intervention study to compare monthly no-show rates in 18-25 year olds at an AYA benign hematology clinic. All patients enrolled in this clinic from September 2015 to present have been eligible for this study. Patients were consented at the time of appointment booking, and received SMS reminders and a link to an online study survey 3 business days prior to their appointment. We compared monthly pre-intervention no-show rates to post-intervention rates using a Chi-square test with significant p-value of <0.05. RESULTS: We have recruited 68 AYA patients and sent out 102 SMS in the post-intervention phase to date. SMS reduced missed appointments from 31.35% (91/290) to 16.2% (15/93), however, the results were not statistically significant (p=0.808). Among patients who missed appointments, 4 patients were repeat no-shows, and 5 patients have a history of no-shows from pediatric care. Five patients rescheduled appointments, and 4 who were unable to attend for medical reasons were not counted as missed appointments. Through the survey, patients agreed SMS reminders were helpful; additional patient characteristics and related data are being analyzed. All patients consented to participate; however 4 did not provide a mobile number and were excluded from the study. Recruitment is on-going. CONCLUSION: Preliminary results show SMS reminders may be an effective intervention to improve clinic attendance at an AYA hematology clinic. The SMS reminders have been well received, and have presumably impacted care in a positive way. A future study could assess the integration of such technology at a pediatric clinic to empower teenagers (ages 13-18) to engage in the management of their own healthcare treatment.
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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 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 ».