A Mobile App to Enhance Awareness of Vaccination in Adults With Psoriasis and Atopic Dermatitis: Development and Preliminary Evaluation Study
Notice bibliographique
Résumé
BACKGROUND: Patients with psoriasis and atopic dermatitis are at increased risk of several vaccine-preventable diseases. Despite this increased susceptibility to infections, vaccination uptake in adults with psoriasis and atopic dermatitis, especially if treated with biologics and other systemic immunomodulators, is insufficient. As mobile health technologies may support behavior change, a mobile app called DermatoVax was developed to raise awareness of immunization in adult patients with psoriasis and atopic dermatitis. OBJECTIVE: This paper aims to describe the processes of development of the DermatoVax app and its initial evaluation in terms of technical verification and physicians' quality rating. METHODS: The app was conceived in a user-centered fashion. Its core component was the vaccine checker, which allows the app to produce a sharable list of recommended vaccines, immunization timings, and eventual precautions from a short set of input data. App prototypes were extensively piloted, and feedback from potential end users was obtained to refine the app content. The readability of the textual narratives was measured using the Italian-specific Gulpease index, which ranges from 0 to 100, where 100 indicates the best readability. The quality of the final version was evaluated by 46 medical doctors (n=29, 63% dermatologists and n=17, 37% public health physicians) using a validated Italian user version of the Mobile App Rating Scale (uMARS). RESULTS: Iterative steps during the app development process allowed us to increase its user-friendliness and comprehensibility. Proper functioning of the checker was confirmed through the correct and complete generation of recommended vaccine lists for 50 mock patients with psoriasis and atopic dermatitis. An overall Gulpease index of 41.0 was observed for the final textual narratives, suggesting acceptable readability properties for patients with a high school diploma. Of a maximum of 5 points, the average uMARS score was 4.22 (SD 0.49). Ratings provided by dermatologists (mean 4.28, SD 0.48) were similar (P=.33) to those provided by public health physicians (mean 4.12, SD 0.51). However, the mean uMARS scores for the quality dimensions of aesthetics (3.88, SD 0.78) and engagement (3.89, SD 0.68) were lower than those for information (4.64, SD 0.42) and functionality (4.47, SD 0.46), suggesting margins for improvement. The app's perceived impact was notably high, with over 80% of physicians agreeing that its use would significantly improve patient awareness (39/46, 85%) and knowledge (41/46, 89%) of vaccination, leading to increased vaccination uptake (37/46, 80%). CONCLUSIONS: DermatoVax is a promising tool to raise awareness of immunization in adult patients with psoriasis and atopic dermatitis. Further assessment of the app, such as its effectiveness in increasing vaccination uptake, is warranted.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».