A Multimodal Investigation of Listening Effort in Single-Sided Deafness
Bibliographic record
Abstract
PURPOSE: For patients with single-sided deafness (SSD), choosing between bone conduction devices (BCDs) and contralateral routing of signal hearing aids (CROS) is challenging due to mixed evidence on their benefits. The lack of clear guidelines complicates clinical decision making. This study explores whether realistic spatial listening measures can reveal a clinically valid benefit and if the optimal choice varies among patients. By assessing listening effort through objective and subjective measures, this research evaluates the efficacy of BCD and CROS, seeking to provide evidence-based recommendation anchored in the effectiveness of these devices in real-world scenarios. METHOD: Thirteen participants with SSD performed the Hearing-in-Noise Test while using a BCD, CROS hearing aids, and no hearing device (unaided). Subjective listening effort was assessed using the National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire after each testing block. An objective measurement of listening effort was obtained by measuring the peak pupil dilation (PPD) during the task using eye tracking glasses. RESULTS: No significant difference of either PPD or NASA-TLX scores was observed between the three device conditions (BCD, CROS, and unaided). However, a trend is noted toward reduced PPD in the BCD and CROS conditions. The lack of significance in pupillometry results does not stem from technical issues, as the study's findings confirm its effectiveness in measuring task difficulty, and validate its use for assessing listening effort. CONCLUSIONS: Although the results from the present study cannot significantly differentiate the hearing devices, we observe a trend that points toward reduced listening effort when using hearing devices. Future investigations should aim to optimize metrics of listening effort, perhaps making them clinically useful on an individual level.
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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".