Design, Development, and Usability Evaluation of a Mobile Application for Monitoring Voice and Upper Airway Health
Notice bibliographique
Résumé
IntroductionAsthma and chronic obstructive pulmonary disease (COPD) are highly prevalent chronic respiratory diseases worldwide and in Canada. Despite the availability of telemonitoring methods, adequate symptom control in asthma and COPD remains a challenge due to the unpredictable nature of exacerbations and nighttime awakenings, which can lead to increased hospitalizations, healthcare costs and mortality. Mobile health (mHealth) applications (apps) provide a viable option to remotely monitor patients’ health conditions and control symptom progression. The objectives of this thesis are to design, develop, and evaluate a mHealth app, namely AIrway, to support patients with asthma and COPD in symptom monitoring and self-management. MethodsThe AIrway app was designed and developed for Android smartphone devices in accordance with Morville’s mobile app design principles and clinical guidelines, such as the Global Initiative for Asthma (GINA) and the Global Initiative for Chronic Obstructive Lung Disease (GOLD), to meet the needs of symptom monitoring. The app also complies with the Personal Information Protection and Electronic Documents Act (PIPEDA) and Quebec privacy law to ensure the protection of user information. Essential features include journaling asthma/COPD diaries, utilizing the Google Firestore cloud service for data storage, parsing local weather information, as well as sending medication reminders and action plans.We recruited 5 app developers (i.e., technical raters) who were Computer Science Ph.D. students or post-doctoral fellows who took at least one mobile app development course or had at least one year of mobile app programming experience to evaluate the AIrway app. These technical raters completed the User Version of the Mobile Application Rating Scale (uMARS) survey, provided open-ended feedback, and responded to the IQVIA items after testing the app. The uMARS survey was designed to assess the app's engagement, functionality, aesthetics, and information quality while the IQVIA items were intended to assess the app's self-management functionality.We collected, processed, and reported the uMARS and IQVIA data in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) guidelines to enhance the reliability of the findings. We also performed a literacy analysis using an open-source readability calculator to evaluate the app’s contents.Descriptive statistics of uMARS and IQVIA were computed and compared to the scores of similar self-management apps in the literature. A qualitative analysis of the open-ended feedback provided by the technical raters was also conducted to identify areas for product improvement.Results and Discussion The results indicate that the AIrway app was easily understandable to individuals with nine years of formal education. The app received a high uMARS overall mean score (3.6 out of 5.0) and an IQVIA overall median score (8 out of 11). These scores align with similar mHealth apps in the literature (MARS: 3.0-4.2 and IQVIA: 6-10). The open-ended feedback suggested incorporating more graphical icons for better user interface display and improving the input field for the password reset function.Overall, the app met the mobile app design principles and development guidelines, achieving appropriate colour contrast, readability, and layout presentations. Furthermore, asthma and COPD diaries, medication profiles, and action plans were developed based on clinically validated guidelines. These steps are essential to meet industrial standards and safeguard the app’s credibility, accessibility, and usability. Future steps include expanding the app’s compatibility to cross-platform frameworks to enhance the app’s accessibility and equity
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 | 0,006 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| 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 | 0,001 |
| 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 ».