77 Qualitative Needs Assessment of Child and Caregiver Perspectives to Inform Design of an Artificial Intelligence-enhanced Social Robot to Improve Paediatric Emergency Care
Notice bibliographique
Résumé
Abstract Background Children routinely experience under-treated pain and distress related to medical procedures, such as intravenous insertions (IVI), which can have negative consequences in both the short-term (e.g., fear, inability to complete procedure) and long-term (e.g., needle phobia, healthcare avoidance). Socially assistive robots (SARs) are a promising tool to manage pain and distress in paediatric healthcare settings. As we work towards building a more developmentally adaptive and interactive SAR, we must first understand how children and families perceive SAR to create a safe and ethical tool. Objectives The aim of this study was to understand children’s and caregivers’ perceptions of interacting with an artificial intelligence (AI)-enhanced SAR as a distraction tool in the paediatric emergency department (ED) to improve their IVI experience. Design/Methods We conducted semi-structured interviews and focus groups with children and their caregivers from two Canadian paediatric EDs between April 2021 to January 2022, with interview transcription and analysis conducted concurrently until thematic saturation was achieved. Qualitative content analysis was performed independently by two team members, who met regularly to discuss the coding scheme and key themes, and facilitate iterative adjustments to the interview script based on emerging themes. Results Nineteen children (mean age 8.42 years [SD 2.21]) and twelve caregivers were included. Three main themes were identified: (1) Overall ED experience, (2) General acceptance of a SAR, and (3) Suggested SAR features to support child engagement. Most participants were comfortable in the ED but identified long wait times and lack of technological supports (e.g., iPads) as an impediment to positive experience. Most participants expressed excitement and comfort surrounding robot technology. However, concerns were raised about photo/video capture by the SAR and the possibility of technical failure resulting in child disappointment or disengagement. Suggestions for potential robot features were unique to the phase of IVI: before IVI (developmentally appropriate procedure explanation, creation of a shared distraction plan); during IVI (variety and choice of distractions, SAR capability to stop or alter course); and after IVI (debriefing and positive reinforcement). Conclusion Overall, AI-enhanced SARs were perceived by children and caregivers as a promising tool to distract children. Insights collected will be used to inform the ethical and emotionally safe design of an AI-enhanced SAR. Next steps include development and usability testing of the SAR, subsequent evaluation in the paediatric ED via a randomized controlled trial, and clinical implementation.
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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 | 0,022 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,009 | 0,006 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».