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Record W4200259476 · doi:10.1093/geroni/igab046.327

Caring for Persons With Dementia in Audiology

2021· article· en· W4200259476 on OpenAlexaff
Marilyn Reed

Bibliographic record

VenueInnovation in Aging · 2021
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsBaycrest Hospital
Fundersnot available
KeywordsDementiaHearing lossMedicineAudiologyRehabilitationQuality of life (healthcare)Presentation (obstetrics)Cognitive impairmentHearing aidCognitionPsychologyPsychiatryPhysical therapyNursingDisease

Abstract

fetched live from OpenAlex

Abstract While hearing loss is highly prevalent among patients with dementia, it frequently goes unidentified and unmanaged. It has been a commonly-held belief that older adults with dementia are unable to benefit from hearing rehabilitation, but recent evidence shows that many individuals with dementia can successfully use amplification, helping to improve communication, social interaction and quality of life for these individuals and their caregivers. This presentation will describe how modifications to practice led to successful outcomes for the majority of patients of a geriatric audiology clinic with co-morbid hearing loss and cognitive impairment. In a study of hearing aid use in 67 patients with these comorbidities, over 90% used hearing aids successfully with measurable benefit for both patients and caregivers. Furthermore, we will discuss approaches to improving communication for LTC residents with dementia and hearing loss through the support of audiologists during remote visits with physicians and families during the pandemic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.048
GPT teacher head0.369
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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