The Development of a Hypertension Prevention and Financial-Incentive mHealth Program Using a “No-Code” Mobile App Builder: Development and Usability Study
Notice bibliographique
Résumé
BACKGROUND: Regular physical activity (PA) is a key lifestyle component for hypertension prevention. Previous studies have shown that mobile health (mHealth) apps can be an effective tool for improving PA behaviors. However, adherence to and poor engagement with these apps is a challenge. A potential solution to overcome this challenge may be to combine financial incentives with innovative behavior theory, such as the Multiprocess Action Control (M-PAC) framework. Currently, there is a lack of PA financial incentive-driven M-PAC mHealth programs aimed at hypertension prevention. OBJECTIVE: We aimed to describe the process of developing an 8-week mHealth PA and financial-incentive hypertension education program (Healthy Hearts) and to evaluate usability of the Healthy Hearts program. METHODS: The first 2 stages of the Integrate, Design, Assess, and Share framework were used to guide the development of the Healthy Hearts program. The development process consisted of 2 phases. In phase 1, the research team met to discuss implementing the M-PAC framework to adopt an existing web-based hypertension prevention program to a mobile app. The app was developed using a no-code app development platform, Pathverse (Pathverse Inc), to help decrease overall development time. In phase 2, we created a prototype and conducted usability testing to evaluate lesson 1 of the Healthy Hearts program to further enhance the user experience. We used semistructured interviews and the mHealth App Usability Questionnaire to evaluate program acceptability and usability. RESULTS: Intervention development among the research team successfully created an 8-week financial-incentive hypertension education program for adults aged 40-65 years who did not currently meet the Canadian Physical Activity Guidelines (<150 minutes of moderate to vigorous PA per week). This program lasted 8 weeks and comprised 25 lessons guided by the M-PAC framework. The program used various behavior change techniques to further support PA adherence. Usability testing of the first lesson was successful, with 6 participants recruited for 2 rounds of testing. Feedback was gathered to enhance the content, layout, and design of the Healthy Hearts program to prepare the mHealth program for feasibility testing. Results of round 1 of usability testing suggested that the content delivered in the lessons was long. Therefore, the content was divided into multiple lessons before round 2 of usability testing, where feedback was only on design preferences. A minimum viable product was created with these results. CONCLUSIONS: The iterative development process and the usability assessments suggested by the Integrate, Design, Assess, and Share framework enabled participants to provide valuable feedback on the content, design, and layout of the program before advancing to feasibility testing. Furthermore, the use of the "no-code" app development tool enabled our team to rapidly make changes to the app based on user feedback during the iterative design process.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».