Approaches to communication assessment in adults with neurodegenerative disorders
Bibliographic record
Abstract
Abstract Neurodegenerative diseases (NDs) cause progressive communication difficulties, encompassing motor speech disorders, language impairments, and functional communication challenges, all of which impact daily activities and social participation. This chapter outlines comprehensive approaches to assess communication in adults with NDs, guided by the International Classification of Functioning, Disability, and Health model. It highlights the significance of impairment-based and activity/participation-based frameworks for evaluating motor speech abilities (e.g., dysarthria, apraxia of speech), language, and functional communication. Tools for perceptual and objective analyses, dynamic assessments, and personal and environmental factors are discussed, emphasizing person-centered, context-sensitive evaluations. Multilingual and cultural considerations in adapting assessments are also discussed. The chapter identifies critical gaps in current tools and advocates for developing and refining assessment measures tailored to the progressive nature of NDs. This work provides a foundation for accurate diagnosis as well as planning intervention, ensuring holistic, effective communication management for individuals with NDs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".