The DizzyQuest: relation between self-reported hearing loss, tinnitus and objective hearing thresholds in patients with Meniere’s disease
Bibliographic record
Abstract
BACKGROUND: Combining a mobile application-based vestibular diary called the DizzyQuest and an iPad-based hearing test enables evaluation of the relationship between experienced neuro-otological symptoms and hearing thresholds in daily life setting. The aim was to investigate the relationship between self-reported hearing symptoms and hearing thresholds in patients with Meniere's disease (MD), using the DizzyQuest and the iPad-based hearing test simultaneously. METHODS: The DizzyQuest was administered for 3 weeks in 21 patients. Using the experience-sampling-method (ESM), it assessed hearing loss and tinnitus severity for both ears separately. Each day after the DizzyQuest, an iPad-based hearing test was used to measure hearing thresholds. A mixed model regression analysis was performed to investigate relationships between hearing thresholds and self-reported hearing loss and tinnitus severity. RESULTS: Fifteen patients were included. Overall, pure-tone averages (PTAs) were not correlated with self-reported hearing loss severity and tinnitus. Individual differences in PTA results between both ears did not significantly influence the difference in self-reported hearing loss severity between both ears. Self-reported hearing loss and tinnitus scores were significantly higher in ears that corresponded with audiometric criteria of MD (p < 0.001). Self-reported tinnitus severity significantly increased with self-reported hearing loss severity in affected (p = 0.011) and unaffected ears (p < 0.001). CONCLUSION: Combining the DizzyQuest and iPad-based hearing test, facilitated assessment of self-reported hearing loss and tinnitus severity and their relationship with hearing thresholds, in a daily life setting. This study illustrated the importance of investigating neuro-otological symptoms at an individual level, using multiple measurements. ESM strategies like the DizzyQuest should therefore be considered in neuro-otological research.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".