Practices and perceptions of cognitive assessment for adults with age‐related hearing loss
Bibliographic record
Abstract
OBJECTIVES: To investigate the landscape of cognitive impairment (CI) screening for adults with age-related hearing loss (ARHL) among otolaryngologists and audiologists. To identify provider factors and patient characteristics that impact rates of CI screening and referral. METHODS: A 15 question online survey was sent to members of the Georgia Society of Otolaryngology (GSO), Georgia Academy of Audiology (GAA), American Otological Society and American Neurotology Society (AOS/ANS), and posted on the web forum for two hearing disorders special interest groups within the American-Speech-Language-Hearing Association (ASHA). Responses were collected anonymously. Chi-square tests were used to compare responses. RESULTS: < .001). The complaint of a neurological symptom, such as memory loss, would prompt screening or referral for only 27.3% (n = 18) and 51.52% (n = 34) of respondents, respectively. Forty-two percent (n = 28) of respondents suggested CI screening with the MMSE vs 20% (n = 13) with the Montreal Cognitive Assessment. CONCLUSIONS: Despite recommendations for cognitive assessment in high-risk populations, such as older adults with ARHL, the practice of CI screening and referral is not yet commonplace among otolaryngologists and audiologists. These providers have a unique opportunity to assess adults with ARHL for CI and ensure appropriate referral. LEVEL OF EVIDENCE: 5.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".