Patients with Tinnitus: Their Perspective on Sound Generators
Bibliographic record
Abstract
OBJECTIVE: Sound therapy (ST) is a well-known treatment option for tinnitus patients. However, patient perspectives on this option remain scarce. This study investigated the perspectives of first-time sound generator users on ST for chronic tinnitus, focusing on their perceptions of the sound generators and the effects on tinnitus. METHODS: The subjects were 29 adult patients with chronic tinnitus who received ST using sound generators for the first time. In the 3-week ST trial, In the 3-week ST trial, hearing aids with built-in sound generators built idelivered broadband noise at a low and individualized sound level. Semistructured interviews were conducted 1 month after the ST trial. Using an interpretive description approach, themes were captured qualitatively to describe patients' subjective experience of the ST. RESULTS: After performing inductive coding on the dataset, five main themes emerged: (1) effects while wearing the generators; (2) effects after removing the generators; (3) perception of the generated noise; (4) untargeted effects; and (5) purchasing sound generators. Each theme was further subdivided into one to three subthemes. CONCLUSIONS: The study highlighted uncertainties regarding the overall perceived benefits of short-term ST, with results influenced by initial noise hypersensitivity, hearing loss, and noise appreciation. Future research should examine the benefits of ST after controlling for these variables and compare the effects of different types of tailored sound on each dimension of tinnitus. Understanding how noise physiologically modulates tinnitus both during and after exposure is crucial to better counsel patients on what to expect.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".