Auditory processing and its cognitive correlates in older adults with mild cognitive impairment
Bibliographic record
Abstract
INTRODUCTION: Age-related central auditory processing disorder (CAPD) is linked to cognitive decline in older adults, potentially preceding Mild Cognitive Impairment (MCI) by several years. While studies indicate that all auditory processing domains are impacted, it remains unclear which domain most significantly correlates with cognitive functions in MCI, warranting further investigation into these relationships. The current study investigated auditory processing deficits and their relationship with cognitive performance in older adults with MCI. METHOD: The study recruited 70 participants aged 60 to 72 years, divided into two groups: MCI(n = 35) and healthy controls (n = 35) based on Montreal Cognitive Assessment scores. Comprehensive central auditory processing and cognitive assessments were done. RESULTS: The MCI group showed significant deficits across all auditory processing and cognitive domains. The enhanced right ear advantage in the dichotic test could be due to corpus callosum atrophy affecting left ear processing. Different factor structures in MCI suggest that they relied more on attentional resources for complex auditory tasks. Temporal processing tests showed high sensitivity in identifying MCI, with strong AUC and R² values, underscoring their clinical relevance. CONCLUSION: Temporal processing deficits could serve as an early screening tool for cognitive decline in older adults. Larger studies targeting individuals with age-related hearing loss (ARHL) and MCI are essential, given the prevalence of ARHL in this population. Research should also examine the impact of tailored auditory training on cognitive function in MCI to inform interventions. TRIAL REGISTRATION: The study was registered in the Clinical Trials Registry of India (CTRI/2023/06/054277) on 21/06/2023 ( http://ctri.nic.in/ ).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".