Health Care Professionals’ Clinical Perspectives & Satisfaction with a Blood Glucose Meter and Mobile App featuring a Dynamic Color Range Indicator and Blood Sugar Mentor: Online Evaluation in the United Kingdom, France, Germany, India, Algeria, Canada and the United States (Preprint)
Notice bibliographique
Résumé
BACKGROUND Despite many new therapies and technologies becoming available in the last decade, people with diabetes continue to struggle to achieve good glycemic control. Innovative and affordable solutions are needed to support healthcare professionals (HCPs) to improve patient outcomes OBJECTIVE To gather current self-management perceptions of HCPs in seven countries and investigate HCP satisfaction with a new glucose meter and mobile app featuring a dynamic color range indicator and a blood sugar mentor METHODS A total of 355 HCPs, including 142 endocrinologists, 108 primary care physicians, and 105 nurses, were recruited from the United Kingdom (n=50), France (n=50), Germany (n=50), India (n=54), Algeria (50), Canada (n=51) and the United States (n=50). HCPs experienced the OneTouch Verio Reflect glucose meter and OneTouch Reveal mobile app online from their own office computer using interactive demonstrations (via webpages and multiple animations). After providing demographic and clinical practice insights, HCPs responded to statements about the utility of the system. RESULTS Concerning current practice, 83% (295/355) of HCPs agreed poor numeracy or health literacy was a barrier for their patients. 86% (305/355) and 92% (327/355) of HCPs responded that type 2 (T2D) and type 1 (T1D) patients were aware what represented a low, in-range or high blood glucose result. Only 62% felt current glucose meters made it easy for patients to understand if results were in-range. 50% (178/355) and 78% (277/35) were confident that T2D and T1Ds took action for low or high results. 87% (309/355) agreed the ColorSure Dynamic Range Indicator could help them teach patients how to interpret results and 89% (323/355) agreed it made them more aware of hyper and hypoglycemic results so they could take action. 86% (305/355) agreed the Blood Sugar Mentor feature, gave personalized guidance, insight, and encouragement so patients could take action. 86% (305/355) also agreed the Blood Sugar Mentor provided real-time guidance to reinforce the goals HCPs had set, so patients could take steps to manage diabetes between office visits. After experiencing the full system, 86% (305/355) agreed it was beneficial for patients with lower numeracy or health literacy, 96% (341/355) that it helped patients understand when results were low, in-range or high and 91% (323/355) agreed the way it displayed diabetes information would make patients more inclined to act upon results. 89% (316/355) agreed it would be helpful for agreeing appropriate in-range goals for their patients next clinic visit. CONCLUSIONS This multi-country online study provides evidence that HCPs were highly satisfied with the OneTouch Verio Reflect meter and OneTouch Reveal mobile app, which each use color-coded information and a Blood Sugar Mentor feature to assist patients with interpreting, analyzing and acting upon their blood glucose results, which is particularly beneficial to keep patients on track between scheduled office visits CLINICALTRIAL none
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 | 0,008 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».