“Internet+Nursing Service” Mobile Apps in China App Stores: Functionality and Quality Assessment Study
Notice bibliographique
Résumé
Background: As the Chinese society ages and the concern for health and quality of life grows, the demand for care services in China is increasing. The widespread use of internet technology has greatly improved the convenience and efficiency of web-based services. As a result, the Chinese government has been implementing "Internet+Nursing Services" since 2019, with mobile apps being the primary tools for users to access these services. The quality of these apps is closely related to user experience and the smooth use of services. Objective: This study aims to evaluate the functionality, services, and quality of "Internet+Nursing Service" apps; identify weaknesses; and provide suggestions for improving service programs and the research, development, improvement, and maintenance of similar apps. Methods: In December 2022, two researchers searched for "Internet+Nursing Service" apps by applying the search criteria on the Kuchuan mobile app monitoring platform. After identifying the apps to be included based on ranking criteria, they collected information such as the app developer, app size, version number, number of downloads, user ratings, and number and names of services. Afterward, 5 trained researchers independently evaluated the quality of the apps by using the Chinese version of the user version of the Mobile App Rating Scale (uMARS-C). The total uMARS-C score was based on the average of the five evaluators' ratings. Results: A total of 17 "Internet+Nursing Service" apps were included. Among these, 12 (71%) had been downloaded more than 10,000 times, 11 (65%) had user ratings of 4 or higher, the median app size was 62.67 (range 22.71-103; IQR 37.51-73.47) MB, 16 (94%) apps provided surgical wound dressing change services, 4 (24%) covered first-tier cities, and only 1 (6%) covered fourth-tier cities. The median total uMARS-C score was 3.88 (range 1.92-4.92; IQR 3.71-4.05), which did not correlate with app store user ratings (r=0.003; P=.99). The quality of most apps (11/17, 65%) was average. Most apps (12/17, 71%) were rated as "good" or above (≥4 points) in terms of information quality, layout, graphics, performance, and ease of use; however, the vast majority of apps were rated as "fair" or even "poor" (<4 points) in terms of credibility (14/17, 82%) and demand (16/17, 94%). Conclusions: "Internet+Nursing Service" apps need to broaden their service coverage, increase service variety, and further optimize their service structure. The overall quality of these apps is generally poor. App developers should collaborate with medical professionals and communicate with target users before launching their products to ensure accurate content, complete functionality, and good operation that meets user needs.
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 | 0,007 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| 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 ».