Designing an App to Facilitate Self-Management in Young Adult Survivors of Childhood Cancer: Development and Usability Study
Notice bibliographique
Résumé
BACKGROUND: Young adult survivors of childhood cancer are at risk for late and long-term effects from their treatment, and less than 1 in 5 obtain risk-based care in adulthood. Transitioning young adult survivors from pediatric, parent-driven care to adult, self-driven care is a challenging process during which young adults face multiple barriers. Intervening during this period may facilitate better transition readiness. For this purpose, we previously developed the Managing Your Health (MYH) web-based intervention, which showed initial feasibility and acceptability; however, young adult participants wanted to access the intervention through a mobile app. OBJECTIVE: We used an iterative, cocreation design process to translate, build, and evaluate the usability of the MYH web-based intervention into a mobile app to be used in a future peer-mentoring educational intervention. METHODS: In phase 1, we conducted key informant workshops with 3 stakeholder groups to understand target users' needs and expectations related to the content and design of the mobile app. In phase 2, we conducted usability testing with young adult survivors of childhood cancer to evaluate the app's usability and subjective appeal. RESULTS: Participants in the key informant workshops (n=13) agreed that the content of the proposed app matched the barriers faced by young adult survivors of childhood cancer. Participants provided suggestions about the design of the app, including content and features, although there were mixed views about the inclusion of gamification features. Usability testing participants (n=25) rated the app highly on measures of technology acceptance, usability, and aesthetic appeal. Participants' qualitative comments suggested that they found the app to be useful, easy to use, and likable or familiar relative to other existing apps. Participants suggested a variety of features to enhance the app, including adding features to enhance usability and reformatting certain aspects of the app to enhance interactivity and feedback to the user. Suggestions with uniformly positive reports were used to refine the app, while suggestions with mixed enthusiasm were not prioritized in refining the app. CONCLUSIONS: We engaged target users of an educational app in an iterative app design process to create a product that would meet the needs and expectations of those users. Results suggested that the app was generally viewed as acceptable, useful, and visually appealing. Common suggestions for improvement, such as reformatting quizzes to enhance interactivity and provide feedback regarding correct answers, were used to refine the app. The refined app will be used in the future intervention efficacy trial. TRIAL REGISTRATION: ClinicalTrials NCT06763770; https://clinicaltrials.gov/study/NCT06763770.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».