Using a Commercially Available App for the Self-Management of Hypertension: Acceptance and Usability Study in Saudi Arabia
Notice bibliographique
Résumé
BACKGROUND: The use of smartphone apps to assist in the self-management of hypertension is becoming increasingly common, but few commercially available apps have the potential to be effective along with adequate security and privacy measures in place. In a previous study, we identified 5 apps that are potentially effective and safe, and based on the preferences of doctors and patients, one (Cora Health) was selected as the most suitable app for use in a Saudi context. However, there is currently no evidence of its usability and acceptance among potential users. Indeed, there has been little research into the usability and acceptance of hypertension apps in general, and less research considers this in the Gulf Region. OBJECTIVE: This study aims to evaluate the acceptance and usability of the selected app in the Saudi context. METHODS: This study used a mixed methods approach with 2 studies: a usability test involving patients in a controlled setting performing predefined tasks and a real-world usability study where patients used the app for 4 weeks. In the usability test, participants were asked to think aloud while performing the tasks, and an observer recorded the number of tasks they completed. At the end of the real-world pilot study, participants were interviewed, and the mHealth App Usability Questionnaire was completed. Descriptive statistics were used to analyze quantitative data, and thematic analysis was used to analyze qualitative data. RESULTS: In total, 10 patients completed study 1. The study found that app usability was moderate and that participants needed some familiarization time before they could use the app proficiently. Some usability issues were revealed, related to app accessibility and navigation, and a few tasks remained uncompleted by most people. A total of 20 patients completed study 2, with a mean age of 51.6 (SD 11.7) years. Study 2 found that the app was generally acceptable and easy to use, with some similar usability issues identified. Participants stressed the importance of practice and training to use it more easily and proficiently. Participants had a good engagement level with 48% retention at the end of study 2, with most participants' engagement being classed as meaningful. The most recorded data were blood pressure, followed by stress and medication, and the most accessed feature was viewing graphs of data trends. CONCLUSIONS: This study shows that a commercially available app can be usable and acceptable in the self-management of hypertension but also found a considerable number of possibilities for improvement, which needs to be considered in future app development. The results show that there is potential for a commercially available app to be used in large-scale studies of hypertension self-management if suggestions for improvements are addressed.
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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 | 0,005 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».