Effects of Wearing Hearing Aids on Gait and Cognition: A Pilot Study
Bibliographic record
Abstract
INTRODUCTION: Positive effects of hearing aids (HA) have been suggested. However, their impact on gait performance, which is closely associated with hearing loss and cognition, remains unclear. This pilot study assessed the impact of wearing HA on gait performance among patients with age-related hearing loss (ARHL). METHODS: This single-arm trial compared gait performance of patients with ARHL before and after wearing HA. Participants diagnosed with ARHL and prescribed HA by an audiologist wore the HA gradually over 1 week. They then underwent a baseline assessment before wearing HA consistently. After wearing the HA for 1 year, participants underwent a follow-up assessment that included evaluations of gait and cognitive performance, fear of falling, incidental falls, and well-being using WHO-5. RESULTS: Of the 10 participants included, one withdrew during the follow-up period. Intention-to-treat analyses showed improvements in gait step time at both usual and maximum paces due to HA use. Cognitive function, including Montreal Cognitive Assessment scores and delayed verbal recall on the logical memory test, also significantly improved at follow-up. Furthermore, reduced fear of falling and increased WHO-5 scores was observed after 1 year of HA use. Conversely, the rate of incidental falls did not decrease. CONCLUSION: HA use may contribute to improved gait performance and reduced anxiety related to physical function, in addition to cognitive function and well-being. Although the results should be interpreted with caution due to the non-randomized controlled trial design and small sample size, the findings suggest that improving hearing acuity among older adults may enhance overall health status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".