Patching the robot: Perspectives about amblyopia and the feasibility of social robots supporting patching therapy
Notice bibliographique
Résumé
SIGNIFICANCE: Social robots have potential applications in eyecare, including the treatment of amblyopia. Desirable functions and features were explored with caregivers whose children were prescribed patching for amblyopia. Caregiver perspectives about the feasibility of social robots supporting amblyopia patching will inform the subsequent design of a social robot for a clinical trial with children undergoing patching therapy. PURPOSE: To explore a new strategy for addressing suboptimal amblyopia patching adherence by gathering caregiver perspectives on amblyopia and the feasibility of using a social robot to support their child's patching regime. METHODS: Caregivers of children who were prescribed patching for amblyopia completed an online survey and an online individual, semi-structured interview. Caregivers were asked about their amblyopia knowledge and experiences. They were also asked to share their views about using social robots to help them understand the condition and support their child with adherence to patching therapy. Anonymized interview transcripts were evaluated using thematic content analysis. Data saturation determined the sample size. RESULTS: Seven caregivers displayed knowledge deficits about amblyopia and a 50% average patching adherence. Prior experience with amblyopia mitigated the attitudes toward amblyopia and its management. All caregivers believed their child would benefit from interacting with a social robot during their eye examinations. They held mixed views about using the robot to enhance their knowledge about amblyopia. The perceived desirable social robot functions included regulating emotions, educating, motivating, and entertaining the child, demonstrating the child's vision, and monitoring vision progress. Desirable features regarding attributes, appearances, and actions were identified (e.g., friendly, expressive, gentle, and wearing an eye patch). CONCLUSIONS: The findings underscore a need for enhanced patching adherence and caregiver amblyopia literacy. They uniquely highlight how prior experience with amblyopia can shape caregiver attitudes towards managing amblyopia. Social robots may offer an innovative option to address these problems. These caregivers identified desirable functions (e.g., regulate, educate, motivate, entertain, and monitor) and features (e.g., wear an eye patch) of a social robot interacting with children undergoing patching therapy. These perspectives will help to inform the development of a social robot for a subsequent clinical trial with children undergoing patching for amblyopia.
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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 | 0,003 | 0,001 |
| 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 | 0,002 | 0,003 |
| 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 ».