Exploring the Perceptions of Voice-Assisted Technology as a Tool for Speech and Voice Difficulties: Focus Group Study Among People With Parkinson Disease and Their Carers
Notice bibliographique
Résumé
BACKGROUND: People with Parkinson disease (PD) often report low volume and reduced intelligibility of speech. Common household devices that use voice-assisted technology (VAT) require users to speak slowly, clearly, and loudly for the technology to function. For people with PD, this can be challenging, but this also suggests that VAT may have potential as a therapeutic tool. While VAT is an emerging health care technology, it is important to better understand the thoughts and experiences of people with PD who are already using it despite having speech and voice difficulties. OBJECTIVE: This study aimed to explore experiences of using VAT to address hypokinetic dysarthria secondary to PD, based on the perspectives of people with PD and family carers. METHODS: People with PD experiencing mild to moderate speech changes who were smart speaker users, and their carers, were invited to participate in 1 of 4 in-person focus groups. Between September and December 2024, focus groups were audiovisually recorded. A semistructured topic guide informed by published evidence was used to guide discussions. Results were transcribed and analyzed through a framework analysis approach (managed using NVivo software). RESULTS: A total of 15 participants, including 8 (53%) people with PD and 7 (47%) carers, participated in 4 in-person focus groups. Findings revealed shared experiences with VAT that were marked by its therapeutic potential and practical challenges. Five main themes were identified: (1) therapeutic potential for speech and voice, with subthemes of changes in volume, intelligibility, and clarity of speech; the role of VAT feedback; and VAT as an everyday device; (2) distrust of technology, with concerns surrounding data privacy, the listening nature of devices, and measures users take to protect themselves; (3) frustrations with devices, including devices not understanding, devices timing out, and the lack of conversation; (4) support needs, including the impact of a lack of knowledge and the need for education and guidance; and (5) design considerations for a future VAT tool in speech and language therapy (SLT). CONCLUSIONS: This study extends on previous research findings, demonstrating that VAT may be acceptable to people with PD to create changes in volume, clarity, and intelligibility. However, attention must be given to users' privacy concerns and frustrations with devices before VAT can used as a tool in SLT. Future research should design solutions to address current usability challenges with people with PD and professionals in three ways: (1) co-designing education and guidelines for people with PD, describing the use of VAT for speech and voice difficulties; (2) refining commercial VAT for use in SLT; and (3) establishing the feasibility of a therapeutic VAT intervention for people with PD with speech and voice difficulties.
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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 | 0,001 |
| 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 | 0,000 | 0,001 |
| 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 ».