Validation of a cognitive screening tool for hearing impaired older adults
Bibliographic record
Abstract
Dementia usually starts in individuals aged over 65, and one-third of people in this age group have disabling hearing impairment. Moreover, older adults with hearing impairment are nearly 2 times more likely to develop dementia compared with their normal-hearing peers. This makes early and accurate screening for mild cognitive impairment (MCI) among this population even more important. The Montreal cognitive assessment (MoCA) is a commonly used cognitive screening tool to early identify the individuals at risk of MCI. However, the tool relies on verbal administration of the instructions and target words/sentences which as shown in a previous meta-analysis could be a disadvantage for the hearing-impaired population, making the screening inaccurate. The MoCA for hearing-aid users (MoCA-HA) was developed and validated. The development phase was done with feedback from professionals and the older adult hearing-aid users, the tool’s final target population. The appropriate cut-point score of below 26 out of 30 is proposed for an onward cognitive assessment referral which yields a similarly high sensitivity to the traditional MoCA. It had an excellent discrimination property and correlated well with other existing cognitive measures. The MoCA-HA is suitable to be used in hearing aid centres for early screening for potential mild cognitive impairment. Despite measuring with the visually presented tool such as MoCA-HA, the information encoding ability was slightly reduced in the hearing-impaired cohort. The information retrieval ability was well preserved among the hearing-impaired population but was reduced when they had additional mild cognitive impairment. This also affected their performance and reliability of the self-reported hearing difficulty questionnaires. The visuospatial ability of the hearing-impaired population was better than the norms. With additional MCI, the ability was decreased but still comparable to the norms. These considerations could formulate better and holistic care plans for the hearing-impaired population with potential cognitive impairment.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".