User Needs in the Development of a Health App Ecosystem for Self-Management of Cystic Fibrosis: User-Centered Development Approach
Notice bibliographique
Résumé
BACKGROUND: Digital self-management in cystic fibrosis (CF) is foreseen as a means toward better understanding of the disease and its treatment and better adherence to the treatment. Mobile apps hold the potential to provide access to information, motivate, and strengthen compliance. However, to deliver high-quality apps, the development should be based on thorough knowledge about user needs. Empirical research on the user-centered development of mobile apps for health care is, however, still limited. OBJECTIVE: The aim of this research is to develop and evaluate an app ecosystem for self-management in CF. It targets not only those directly affected by CF but also parents and health care professionals involved in the treatment. This paper covers the first step of the design process that aims to analyze the context and the user requirements. The primary research question is as follows: what digital support has the potential to usefully support persons with CF and their caregivers in the CF care? To answer this question, we address two preliminary questions: what important factors in everyday life affect the care of persons with CF? and how is the CF care delivered today and what are the limitations of CF care services? METHODS: The overall research adopts a user-centered design approach in which future users are involved in the development process from the very beginning to ensure that the apps developed best suit the potential users. The research presented in the paper follows an interpretative case study research strategy seeking to understand the concerns and needs of persons with CF and their caregivers. Data were collected through semistructured qualitative interviews involving 74 participants in seven European countries and from internet forums. RESULTS: The results of the analysis phase show a strong need for individuality of the digital support, as well as for its adaptability to different contexts. The paper presents the concerns and needs of the participants in the study and extracts a set of relevant features for a self-management app ecosystem. Education, enzyme dosage calculation, nutrition management, treatment organization, health diary, treatment follow-up, practical guidelines for treatment, communication with doctors, and communication with peers are foreseen as useful features. CONCLUSIONS: The results indicate the readiness for self-management in the CF care even in countries that provide well-functioning health care services for CF care. The large diversity of user requirements identified reflects the crucial role user integration plays in developing apps for a chronic condition such as CF. The need for personalization stemming from the individuality of the patients and the need for communication with health care professionals support the idea of an app ecosystem for the self-management of CF.
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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 | 0,029 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,007 | 0,006 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».