Models and frameworks for guiding assessment for aided Augmentative and Alternative communication (AAC): a scoping review
Notice bibliographique
Résumé
Background Augmentative and Alternative Communication (AAC) supports individuals with complex communication needs. Conceptual models and frameworks exist to evaluate, implement, and assess the needs of persons with communication disabilities, however, it is unknown which models were grounded in previous evidence-based research.Objective What are the models and frameworks grounded in empirical or conceptual research that enable communication outcomes for persons who require aided AAC systems?Eligibility Criteria The study had to be the original publication of a defined model or framework that included aided AAC and the model had to be developed through research, either conceptual or empirical.Sources of Evidence Eleven databases were searched using terms associated with AAC devices, conceptual models, and assessment processes. Fifteen articles presenting 14 independent assessment models were included.Charting Methods A custom data extraction form included model development using existing models and research evidence, the model’s input parameters, and explicit outcome measures.Results Four models were specific to AAC while ten models were general evaluations for assistive technology systems. Models used a variety of descriptive traits during assessment including: person, technology, environment and context, and the activity or task. Only nine models sought to iteratively assess the client. Eleven of the models identified the inclusion of members from different disciplines in the assessment process.Conclusions There is a need to standardize descriptive traits: personal abilities, environmental characteristics, potential assistive technology, and contextual factors. Models should include teams of different disciplines to provide holistic assessments. Models should include outcomes and include iterative solutions.Implications for RehabilitationStandardizing the definitions of descriptive traits used in the assessment of the personal abilities, environmental characteristics, potential assistive technology, and contextual factors would enable better evaluation of outcomes across disciplines and abilities.By identifying what factors are instrumental in the successful recommendation of assistive technology, professionals may achieve a well-organized and efficient assessment tool.An assessment model tailored specifically to individuals who may benefit from Augmentative and Alternative Communication (AAC) should be considered that are rooted in existing theories, research evidence, and the experiences of those in the AAC community.An AAC specific model would allow for consistent outcome tracking across individuals or assessment teams and the comparison of the effectiveness of various models for research purposes.
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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 | 0,004 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».