Engagement, Retention, and Acceptability in a Digital Health Program for Atopic Dermatitis: Prospective Interventional Study
Notice bibliographique
Résumé
BACKGROUND: Patients with atopic dermatitis can experience chronic eczema with pruritus, skin pain, sleep problems, anxiety, and other problems that reduce their quality of life (QoL). Current treatments aim to improve these symptoms and reduce inflammation, but poor treatment adherence and disease understanding are key concerns in the long-term management of atopic dermatitis. Digital therapeutics can help with these and support patients toward a healthier lifestyle to improve their overall QoL. OBJECTIVE: The aim of the study is to test the feasibility of a digital health program tailored for atopic dermatitis through program engagement, retention, and acceptability. METHODS: Adults with atopic dermatitis were recruited in Iceland for a 6-week digital health program delivered through a smartphone app. Key components of the digital program were disease and trigger education; medication reminders; patient-reported outcomes (PROs) on energy levels, stress levels, and quality of sleep (referred to as QoL PROs); atopic dermatitis symptom PROs; guided meditation; and healthy lifestyle coaching. The primary outcome was program feasibility, as assessed by in-app retention and engagement. User satisfaction was assessed by the mHealth (ie, mobile health) App Usability Questionnaire (MAUQ). RESULTS: A total of 21 patients were recruited (17 female, mean age 31 years), 20 (95%) completed the program. On average, users were active in the app 6.5 days per week and completed 8.2 missions per day. The education content, medication reminders, and PROs had high user engagement and retention; all users who were exposed to the QoL PROs (n=17) interacted with these, and 20/21 (95%) users were continuously engaged with the education missions, medication missions, and symptom PROs. Continued engagement with the step counter and mind missions among exposed users was lower (17/21 and 13/20 participants, respectively). Medication reminder and education task completion remained high over time (at least 18/20, 90%), but weekly interactions declined. All assigned users completed atopic dermatitis symptom PROs on weeks 1-5 and only one did not do so on week 6; the reported number and total severity of atopic dermatitis symptoms reduced during the program. Regarding the QoL PROs, 16/17 (94%) and 14/17 (82%) users interacted with these at least 3 times in the first and last week of the program, respectively, and all reported improvements over time. User satisfaction was high with a total score of 6.2/7. CONCLUSIONS: We found high overall engagement and retention in a targeted digital health program among patients with atopic dermatitis, as well as high compliance with missions relating to medication reminders, patient education, and PROs. Symptom number and severity were reduced, and QoL PROs improved over time. We conclude that a digital health program is feasible and may provide added benefits for patients with atopic dermatitis, including the tracking and improvement of atopic dermatitis symptoms.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,000 |
| 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
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