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Enregistrement W4417015871 · doi:10.1182/blood-2025-4366

A pilot study evaluating the feasibility and usability of an mHealth application: SCD warrior

2025· article· en· W4417015871 sur OpenAlexaff
Nancy Asomaning, Mingjie Xu, Ingrid Frey, Raquel Andres

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueHemoglobinopathies and Related Disorders
Établissements canadiensPancreas Centre (Canada)
Organismes subventionnairesnon disponible
Mots-clésmHealthUsabilityLife expectancyDiseaseDigital healthDisease managementChronic diseaseMEDLINE

Résumé

récupéré en direct d'OpenAlex

Abstract BACKGROUND Sickle cell disease (SCD) is an inherited blood disorder that affects over 7 million individuals worldwide, including an estimated 100,000 in the US. Since the late 20th century, the survival rates for patients with sickle cell disease (SCD) in high-income countries have significantly improved. Previously referred to as a “disease of childhood,” it is now estimated that 94-99% of individuals with HbSS live into adulthood although life expectancy for SCD patients remains 20-30 years shorter than that of the general population. Adults with SCD, however, continue to suffer from pain - acute and chronic – in addition to fatigue compounded by multiple organ complications. Effective self-care and self-management are essential for managing and mitigating complications in chronic conditions such as SCD. Digital health technologies, including wearables and mobile health (mHealth) applications, have gained signification attention in recent years as potential solutions to improve the management of chronic conditions such as SCD. Specifically, they have been shown to improve patient-driven disease tracking and management, thereby enhancing self-care. Here, we conducted a pilot study to evaluate the feasibility and usability of SCD Warrior, an mHealth application, in helping individuals with SCD manage their disease. METHODS Eleven SCD (HbSS, mean age 44 years [28-60 years], 7 male) patients of African descent, enrolled under the IRB-approved protocol NCT04610866 at the NIH Clinical Center, participated in the study. After obtaining informed consent, participants were trained and onboarded onto the SCD Warrior application (SWA). They were instructed to use SWA daily (Mon-Fri) for 12 weeks, to record their pain, medication usage, and other lifestyle variables of personal interest. Each participant was linked to a clinician via the provider dashboard, who reviewed participant entries and followed up if necessary. A product feedback questionnaire was administered to each participant at baseline and at the end of the 12-week period. Data was analyzed via Stata (v. 18.5) and a paired t-test and Wilcoxon signed-rank test were used for significance testing. RESULTS Nine (81.8%) of the 11 participants utilized SWA throughout the 12-week study period. The 2 remaining subjects did not submit any entries to SWA once enrolled and were considered lost to follow up. All 9 active subjects were adherent (logging medication usage or another health factor in SWA at least 4 days each week, over the study period), with a mean daily adherence rate of 89.9% (SD = 15.3%). The mean application satisfaction score rose from 7.1 (SD=2.70) to 7.7 (SD=1.49) over the study (t=0.970, p value =0.357) period. There was a significant (z=-2.041, p-value=0.0412) change in the mean number of features participants found useful in SWA, with the mean increasing from 2.8 at baseline to 4.3 at the end of the 12-week study period. At baseline, 77.8% (7/9) of participants found the application useful for tracking their medications, 55.6% (5/9) for messaging their care team, and 44.4% (4/9) for tracking their sickle cell-related pain. By the end of the 12-week study period, these percentages increased to 88.8% (8/9), 66.7% (6/9), and 66.7% (6/9), respectively. Most subjects (77.8%, 7/9) agreed that SWA was easy to integrate into their daily and weekly routine and that the logging features were quick and easy to complete. Five of the 9 (55.6%) of the participants agreed that using SWA encouraged them to take better care of their health. Suggestions for improving SWA included integrating more educational information about SCD and better guidance for self-care into the application. CONCLUSIONS SWA was well-received by study participants, achieving an 89.9% adherence rate over 12 weeks. Positive feedback on ease of use, safe-care management, and integration into daily routines indicates that SWA is feasible and useful for managing SCD. However, future improvements should include more educational content on SCD and enhanced self-care features. Overall, SWA shows potential as an effective mHealth tool for health management in individuals with SCD.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,014
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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.

Tête enseignante Opus0,054
Tête enseignante GPT0,379
Écart entre enseignants0,325 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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