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Enregistrement W4312128846 · doi:10.1111/1460-6984.12833

Attributes of communication aids as described by those supporting children and young people with AAC

2022· article· en· W4312128846 sur OpenAlexaff
Simon Judge, Janice Murray, Yvonne Lynch, Stuart Meredith, Liz Moulam, Nicola Randall, Helen Whittle, Juliet Goldbart

Notice bibliographique

RevueInternational Journal of Language & Communication Disorders · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiqueAssistive Technology in Communication and Mobility
Établissements canadiensTrinity College
Organismes subventionnairesnon disponible
Mots-clésAugmentative and alternative communicationVocabularyPsychologyApplied psychologyConsistency (knowledge bases)Focus groupQualitative researchSymbol (formal)Developmental psychologyComputer scienceLinguisticsArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Those supporting children and young people who use augmentative and alternative communication (AAC) contribute to ongoing complex decision-making about communication aid selection and support. Little is known about how these decisions are made in practice and how attributes of the communication aid are described or considered. AIMS: To understand how communication aid attributes were described by those involved in AAC recommendations and support for children and young people, and how these attributes were described as impacting on AAC use. METHODS & PROCEDURES: A secondary qualitative analysis was completed of interview and focus group data from 91 participants involved in the support of 22 children and young people. Attributes of communication aids described by participants were extracted as themes and this paper reports a descriptive summary of the identified software (non-hardware) attributes. MAIN CONTRIBUTION: Decisions were described in terms of comparisons between commercially available pre-existing vocabulary packages. Attributes related to vocabulary, graphic representation, consistency and intuitiveness of design, and ease of editing were identified. Developmental staging of vocabularies, core and fringe vocabulary, and vocabulary personalization were attributes that were described as being explicitly considered in decisions. The potential impact of graphic symbol choice did not seem to be considered strongly. The physical and social environment was described as the predominant factor driving the choice of a number of attributes. CONCLUSIONS & IMPLICATIONS: Specific attributes that appear to be established in decision-making in these data have limited empirical research literature. Terms used in the literature to describe communication aid attributes were not observed in these data. Practice-based evidence does not appear to be supported by the available research literature and these findings highlight several areas where empirical research is needed in order to provide a robust basis for practice. WHAT THIS PAPER ADDS: What is already known on the subject Communication aid attributes are viewed as a key consideration by practitioners and family members in AAC decision-making; however, there are few empirical studies investigating language and communication attributes of communication aids. It is important to understand how those involved in AAC recommendations and support view communication aid attributes and the impact different attributes have. What this paper adds to existing knowledge This study provides a picture of how communication aids are described by practitioners and family members involved in AAC support of children and young people. A range of attributes is identified from the analysis of these qualitative data as well as information about how participants perceive these attributes as informing decisions. What are the potential or actual clinical implications of this work? This study provides a basis on which practitioners and others involved in AAC support for children and young people can review and reflect on their own practice and so improve the outcomes of AAC decisions. The study provides a list of attributes that appear to be considered in practice and so also provides a resource for researchers looking to ensure there is a strong empirical basis for AAC decisions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,136
Score d'incertitude au seuil0,644

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0020,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,020
Tête enseignante GPT0,386
Écart entre enseignants0,366 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2022
Routes d'admission1
Résumé présentoui

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