Caregivers’ Perceptions, Needs, and Data Sharing Concerns in mHealth Research on Pediatric Asthma: Cross-Sectional Survey Study
Notice bibliographique
Résumé
Background: Pediatric asthma is the most common chronic respiratory disease of childhood. Caregivers often report lacking knowledge in several aspects of asthma management at home. Although the use of mobile health (mHealth) tools, such as mobile apps, could facilitate asthma self-management and, simultaneously, the collection of data for research, few studies have explored the features that caregivers would like to see in such a tool and their perceptions on data sharing. Objective: This study evaluates caregivers' perceived knowledge gaps in asthma management; their perceptions of certain features and resources that should be included in a potential mobile app; and any concerns that they may have regarding data sharing for research, including privacy and security concerns. Methods: In this cross-sectional study, we surveyed 200 caregivers of children (aged 1-13 y) with asthma who were followed at a pediatric tertiary care center in Montreal, Canada. Anonymous data were collected through the institutional web-based survey platform. We collected the participants' answers by using a 5-category Likert scale ("completely agree," "agree," "neither agree nor disagree," "disagree," and "completely disagree"), multiple-choice questions, and free-text questions on the abovementioned topics. Descriptive statistics were performed, and answers were compared between caregivers of preschool-aged children and caregivers of school-aged children. Results: Participating children's mean age was 5.9 (SD 3.4) years, with 54% (108/200) aged ≤5 years and 46% (92/200) aged >6 years. Overall, caregivers reported having adequate knowledge about asthma and asthma self-management. Nonetheless, they identified several desirable features for a mobile app focused on asthma self-management. The most frequently identified features included receiving alerts about environmental triggers of asthma (153/199, 76.9%), having videos that demonstrate symptoms of asthma (133/199, 66.8%), and being able to log children's asthma action plans in the app (133/199, 66.8%). Interestingly, more caregivers of preschool-aged children preferred textual information when compared to caregivers of school-aged children (textual information for explaining asthma: P=.008; textual information for the symptoms of asthma: P=.005). Caregivers were generally highly in favor of sharing data collected through a mobile app for research. Conclusions: Caregivers of children with asthma in our study identified several desirable educational and interactive features that they wanted to have in a mobile app for asthma self-management. These findings provide a foundation for designing and developing mHealth tools that are relevant to caregivers of children with asthma.
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 | 0,005 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».