The Influence of Hearing Aids on Balance Control: A Systematic Review
Bibliographic record
Abstract
AIM: To assess the current opinion on the effects of hearing loss treatment by hearing aids (HAs) and the benefits of HA use on imbalance. METHODS: PRISMA-compliant systematic review was done, including observational studies in patients affected by mild to severe sensorineural hearing loss with HAs, investigating the benefits of HAs on balance. Electronic searches were performed through Medline, Cochrane, Embase, Web of Science, and Scopus. RESULTS: A total of 200 patients in 8 studies were included in this systematic review. Four studies were cross-sectional, 3 cross-sectional controlled and 1 prospective nonrandomized study. Static and dynamic balance in the aided condition improved in patients assessed using clinical investigations including Romberg test and Functional Ambulation Performance/mini-BESTest, respectively. Variable outcomes were found measuring static and dynamic balance during the aided condition with objective tests (computerized posturography, Mobility Lab device). Improved quality of life outcomes and self-confidence were noted, while subjective measurements of balance had conflicting results. CONCLUSION: Although an improvement in balance in patients with HAs has been shown in certain conditions, the overall benefit is still unclear and it is only possible to speculate that HAs may also improve static, dynamic, or subjective perception of balance function in adults affected by hearing loss.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".