Behavioral Management of Respiratory/Phonatory Dysfunction for Dysarthria Associated With Neurodegenerative Disease: A Systematic Review
Bibliographic record
Abstract
PURPOSE: This systematic review represents an update to previous reviews of the literature addressing behavioral management of respiratory/phonatory dysfunction in individuals with dysarthria due to neurodegenerative disease. METHOD: Multiple electronic database searches and hand searches of prominent speech-language pathology journals were conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses standards. RESULTS: The search yielded 1,525 articles, from which 88 met inclusion criteria and were reviewed by two blinded co-investigators. A large range of therapeutic approaches have been added to the evidence base since the last review, including expiratory muscle strength training, singing, and computer- and device-driven programs, as well as a variety of treatment modalities, including teletherapy. Evidence for treatment in several different population groups-including cerebellar ataxia, myotonic dystrophy, autosomal recessive spastic ataxia of Charlevoix-Saguenay, Huntington's disease, multiple system atrophy, and Lewy body dementia-were added to the current review. Synthesis of evidence quality provided strong evidence in support of only one behavioral intervention: Lee Silverman Voice Treatment Program (LSVT LOUD) in people with Parkinson's disease. No other treatment approach or population included in this review demonstrated more than limited evidence, reflecting that these approaches/populations require urgent further examination. CONCLUSION: Suggestions about where future research efforts could be significantly strengthened and how clinicians can apply research findings to their practice are provided. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24964473.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".