Speech treatment for people with hereditary ataxia – a feasibility study
Bibliographic record
Abstract
Hereditary ataxias are frequently associated with ataxic dysarthria. The characteristics of ataxic dysarthria include imprecise articulation, distorted vowels, hypophonia, reduced speech rate, flat prosody and poor respiratory support. These changes lead to reduced speech intelligibility and a reduced effectiveness of communication which can affect quality of life. Communication breakdown has been ranked amongst the top three most upsetting symptoms of their disease by people with Friedreich’s Ataxia in a recent survey by Ataxia UK. Whilst we have significantly increased our understanding of the nature of the communication problems experienced by speakers with ataxic dysarthria, there are very few intervention studies and a recent Cochrane review concluded that “there is insufficient and low or very low quality evidence from either RCTs or observational studies to determine the effectiveness of any treatment for speech disorder in any of the hereditary ataxia syndromes.” (Vogel et al. 2014, p.1). Based on the speech symptoms prevalent across the various types of hereditary ataxia, one treatment approach that has potential to increase communication efficiency is Lee Silverman Voice Treatment (LSVT). This treatment approach focuses on increasing the level of loudness in a person’s speech. The method has been shown to positively affect the wider articulatory system, such as improving breath support for speech, slowing down rate, and improving voice quality and articulation, whilst at the same being simple enough for the patient to implement in everyday communication. There are many reports , including RCTs (Baumgartner et al. 2001, Ramig et al. 2018), showing the benefits of LSVT for people with Parkinson’s Disease (PD), as well as smaller studies on other disorders such as cerebral palsy (e.g. Boliek & Fox, 2014), traumatic brain injury and stroke (Wenke et al. 2008, Mahler & Ramig 2012). In addition, a single case study on a patient with ataxic dysarthria as a result of a thiamine deficiency demonstrated improvement in overall speech intelligibility following a course of LSVT (Sapir et al., 2003), highlighting its potential as a treatment for speakers with hereditary ataxias. However, further evidence about its effectiveness across a larger number of participants and a wider range of underlying neuropathologies is necessary before LSVT can be advocated as an appropriate treatment for people with ataxic dysarthria. We report on a feasibility study that aimed to investigate the effectiveness of LSVT to improve communication efficiency, and the acceptability of the approach to people with hereditary ataxia. We recruited 20 participants with hereditary ataxia and dysarthria (17 FRDA, one SPG7, one SCA6 and one unspecified cerebellar ataxia). 19 of these concluded treatment and all assessment points. Dysarthria severity levels ranged from mild to severe. Participants were offered extended LSVT on a 2 session a week basis over 8 weeks via Skype. Assessments included 2 baseline tests, as well as immediate and 6-8 week post treatment follow-ups, also conducted via Skype. Analysis included a range of speech measures, as well as qualitative assessments of voice handicap, communication participation, and fatigue, captured by rating scales as well as interviews. The interview data indicate that 16 of the 19 participants perceived considerable improvements to their communication following LSVT intervention, whilst three reported only minor improvements or no change. Prominent themes emerging from the interviews include the ability to produce longer utterances and speak for longer periods of time, decreased hypophonia, reduced anxiety and greater confidence. A further twelve participants also reported improvements in intelligibility, clearer speech and/or a reduced need to repeat themselves. The formal rating scales corroborate these qualitative results to some degree with the majority of participants showing improved scores after treatment, although this did not reach statistical significance due to variable group performance. Perceptual evaluations of intelligibility and naturalness of a reading sample showed similar results, with some participants showing improved scores after treatment, but not to the extent expressed in the qualitative evaluation. Acoustic voice analysis demonstrated statistically significant performance improvements following treatment, with increases in prolonged vowel length and reduced voice perturbation (jitter and shimmer) values. These effects were maintained 8 weeks post-treatment. Our study provides clear support for offering speech treatment such as LSVT for people with degenerative ataxia to improve their communication and psychosocial wellbeing. This finding is corroborated by a recent pilot study into intensive home-based treatment involving seven speakers with autosomal recessive spastic ataxia Charlevoix-Saguenay (ARSACS) by Vogel et al. (2019), which identified improvements in intelligibility and naturalness post-treatment.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".