Usability of a Mobile App for Improving Literacy in Children With Hearing Impairment: Focus Group Study
Notice bibliographique
Résumé
BACKGROUND: Children with hearing loss, even those identified early and who use hearing aids or cochlear implants, may face challenges in developing spoken language and literacy. This can lead to academic, behavioral, and social difficulties. There are apps for healthy children to improve their spoken language and literacy and apps that focus on sign language proficiency for children with hearing loss, but these apps are limited for children with hearing loss. Therefore, we have developed an app called Hear Me Read, which uses enhanced digital stories as therapy tools for speech, language, and literacy for children with hearing loss. The platform has therapist and parent/child modes that allow (1) the selection of high-quality, illustrated digital stories by a speech-language pathologist, parent, or child; (2) the modification of digital stories for a multitude of speech and language targets; and (3) the assignment of stories by a therapist to facilitate individualized speech and language goals. In addition, Hear Me Read makes the caregiver a core partner in engagement through functionality, whereby the caregiver can record video and audio of themselves to be played back by the child. OBJECTIVE: This study aimed to evaluate the user experience of the Hear Me Read app through a focus group study with caregivers and their children. METHODS: We recruited 16 participants (8 children with and without hearing loss and 8 caregivers) to participate in 1-hour focus groups. Caregivers and children interacted with the app and discussed their experiences through a semistructured group interview. We employed thematic analysis methods and analyzed the data. We used feedback from the focus group to improve the elements of the app for a larger clinical trial assessing the impact of the app on outcomes. RESULTS: We identified three themes: default needs, specific needs, and family needs. Participants found the app to be esthetically pleasing and easy to use. The findings of this study helped us to identify usability attributes and to amend app functionalities to best fit user needs. Caregivers and children appreciated the enhancements, such as highlighting of parts of speech and caregiver reading of video playback, which were made possible by the digital format. Participants expressed that the app could be used to enhance family reading sessions and family interaction. CONCLUSIONS: The findings from this focus group study are promising for the use of educational apps designed specifically for those with hearing loss who are pursuing listening and spoken language as a communication outcome. Further investigation is needed with larger sample sizes to understand the clinical impact on relevant language and literacy outcomes in this population.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».