Development and Systematic Evaluation of a Progressive Web Application for Women With Cardiac Pain: Usability Study
Notice bibliographique
Résumé
BACKGROUND: Cardiac pain has been widely considered to be the primary indicator of coronary artery disease. The presentation of cardiac pain and associated symptoms vary in women, making it challenging to interpret as cardiac, possibly cardiac, or noncardiac. Women prefer to consult with family and friends instead of seeking immediate medical care. OBJECTIVE: This study aimed to assess the user performance (ie, ease of use, efficiency, and errors) and user satisfaction (System Usability Scale; SUS) of a progressive web application for women with cardiac pain. METHODS: Following ethics approval, a purposive sample of women aged >18 years with cardiac pain or associated symptoms lasting >3 months and able to speak and read English was recruited to participate in 2 iterative usability testing cycles. The first cycle assessed the performance of and satisfaction with at heart using a web application, and the second cycle assessed the performance of and satisfaction with at heart across various Android and iOS devices. In total, 2 investigators recorded user comments and documented problems. At the end of the testing session, the participants completed the SUS and 4 semistructured interview questions. RESULTS: In total, 10 eligible women participated in usability testing from March 31, 2020, to April 17, 2020 (cycle 1), and from November 17, 2020, to November 30, 2020 (cycle 2). Women across usability testing cycles had a mean age of 55.6 (SD 7.3) years, and most (9/10, 90%) were well educated. In total, 50% (5/10) were employed full or part time, and 60% (6/10) earned >CAD $70,000 (US $48,881.80) annually. Participants across 2 testing cycles reported the overall usability of the at heart progressive web application as highly acceptable (mean SUS score 81.75, SD 10.41). In total, 90% (9/10) of participants rated the user-friendliness of at heart as good or excellent. All participants (10/10, 100%) thought at heart was easy to use and efficient. Only 2 testing errors were noted as high priority; these were low contrast or small font and clarification that the chatbot was not a real person. User satisfaction was assessed using themes that emerged from the debrief and 4 semistructured interview questions; at heart was engaging, comprehensive, understandable, credible, relevant, affirming, personalized, and innovative. CONCLUSIONS: This study provides initial support for the at heart progressive web application for women living with cardiac pain and symptoms. Ongoing evaluations in phases 3 and 4 should aim to examine the feasibility and acceptability of and the extent of engagement with the at heart core feature set: Heart Check, Wellness Check, and the library. In addition to assessing effectiveness in the phase-4 effectiveness-implementation hybrid trial (type I), describing and better understanding the context for implementation (eg, race and ethnicity and geography) will be necessary. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-033092.
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 | 0,085 | 0,147 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| 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 ».