Speech Amplification Device Usage for the Management of Hypophonia: A Survey of Speech-Language Pathologists
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to survey speech-language pathologists (SLPs) who assess and treat people with Parkinson's disease (PD) to gather insights into their decision making regarding their use or potential use of speech amplification technology for the management of hypophonia. METHOD: A total of 111 SLPs who were currently practicing in the United States or Canada and had experience working with clients with PD for at least 2 years completed an anonymous Qualtrics survey. Questions were designed to probe the following areas: (a) degree of familiarity with amplification devices as a form of treatment for PD, (b) attitudes and perceptions of the implementation of these devices for PD, and (c) factors that influence the clinical decision to prescribe such devices. RESULTS: Most participants (75; 71%) reported they had considered prescribing a device to at least one client with PD. When asked at which stages of speech or voice impairment they would consider the use of an amplification device for clients with PD, the most common response was for clients with moderate or severe hypophonia who were not stimulable for louder speech. However, 36 (32%) respondents indicated they would also consider an amplification device for clients who were stimulable for louder speech with severe hypophonia. When asked to rank the most important factors they would weigh when considering the prescription of an amplification device, they ranked the client's preference and comfort level as the most important consideration. CONCLUSION: This study provides valuable clinical insights regarding how SLPs can approach utilizing speech amplification devices in the therapy environment.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".