Effects of Auditory Training on Cognition in Hearing Loss: A Systematic Review and Meta-analyses
Bibliographic record
Abstract
Purpose: The aim of this study was to examine the efficacy of auditory training to improve cognitive function in patients with age-related hearing loss (ARHL). Research Design: This is a systematic review and meta-analysis. Study Sample: Seven studies involving 443 participants met the inclusion criteria. Participants were typically older adults (mean age = 67.23 years, standard deviation = 7.14) with mild to severe hearing loss. Intervention: Auditory training includes speech perception training, phoneme discrimination training, and so on. Data Collection and Analysis: A literature search of academic databases (Cochrane Library, PubMed, Web of Science, Embase, Wanfang, Weipu, and China National Knowledge Infrastructure) identified relevant articles published up to December 2023. This review includes only randomized controlled trials. The primary outcome is cognition function, measured by Montreal Cognitive Assessment, Mini-Mental State Examination, and other cognition-related subtest indicators. Results: The overall effect of auditory training on overall cognition and executive function in ARHL is statistically significant (overall cognition: g = 0.79, 95 percent confidence interval [CI]: 0.57, 1.01; executive function: g = 3.84, 95 percent CI: 1.49, 6.19), but executive function domain has high heterogeneity (I2 = 100 percent). The effect of auditory training on attention/processing speed and working memory is small and not significant (attention/processing speed: g = 1.47, 95 percent CI: −0.48, 3.42; working memory: g = 0.68, 95 percent CI: −2.22, 3.58), but both attention/processing speed (I2 = 96 percent) and working memory domain (I2 = 98 percent) have high heterogeneity. Conclusions: The overall impact of auditory training on overall cognition and executive function seems to be significant, but because of the low quality of the literature and certain biases, it is impossible to conclude that auditory training can improve the cognitive function of ARHL; therefore, more high-quality evidence is needed.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".