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Record 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 on OpenAlexaff
Simon Judge, Janice Murray, Yvonne Lynch, Stuart Meredith, Liz Moulam, Nicola Randall, Helen Whittle, Juliet Goldbart

Bibliographic record

VenueInternational Journal of Language & Communication Disorders · 2022
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsTrinity College
Fundersnot available
KeywordsAugmentative and alternative communicationVocabularyPsychologyApplied psychologyConsistency (knowledge bases)Focus groupQualitative researchSymbol (formal)Developmental psychologyComputer scienceLinguisticsArtificial intelligence

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.386
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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