Speech and Language Therapists’ Perspectives of Virtual Reality as a Clinical Tool for Autism: Cross-Sectional Survey
Notice bibliographique
Résumé
Background: Persistent difficulties with social skills form part of the diagnostic criteria for autism and in the past have required speech and language therapy (SLT) management. However, many speech and language therapists are moving toward neuro-affirmative practices, meaning that social skills approaches are now becoming redundant. Research demonstrates that virtual reality (VR) interventions have shown promise in overcoming challenges and promoting skill generalization for autistic children; however, the majority of these focus on social skills interventions. While VR is emerging as an SLT intervention, its application for autism remains unexamined in clinical practice. Objective: This research aimed to examine speech and language therapists' knowledge and attitudes toward immersive VR as a clinical tool for autistic children and explore the reasons for its limited integration into clinical practice. Methods: A web-based cross-sectional survey was available from April 3, 2023 to June 30, 2023. The survey, consisting of 23 questions, focused on VR knowledge, attitudes, and the support required by speech and language therapists to incorporate VR into clinical practice. Dissemination occurred through the Royal College of Speech and Language Therapists Clinical Excellence Networks to recruit speech therapists specializing in autism. Results: Analysis included a total of 53 responses from the cross-sectional survey. Approximately 92% (n=49) of speech and language therapists were aware of VR but had not used it, and 1.82% (n=1) had used VR with autistic children. Three key themes that emerged were (1) mixed general knowledge of VR, which was poor in relation to applications for autism; (2) positive and negative attitudes toward VR, with uncertainty about autism specific considerations for VR; and (3) barriers to adoption were noted and speech and language therapists required an improved neuro-affirming evidence base, guidelines, and training to adopt VR into clinical practice. Conclusions: While some speech and language therapists perceive VR as a promising intervention tool for autistic children, various barriers must be addressed before its full integration into the clinical toolkit. This study establishes a foundation for future co-design, development, and implementation of VR applications as clinical tools for autistic children., This study is the first to explore clinical implementation factors for the use of VR in SLT field, specifically with autistic children. Poor autism-specific VR knowledge, and mixed attitudes toward VR, highlight that specific barriers must be addressed before the technology can successfully integrate into the SLT clinical toolkit., Speech and language therapists require support from employers, funding, a robust neuro-affirming evidence base, and education and training to adopt VR into practice. Recommendations for a SLT VR education and training program for use with autistic children, are provided.
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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 | 0,006 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».