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Record W4391136254 · doi:10.1080/14992027.2024.2305279

Perceptions of older and younger adults who wear hearing aids

2024· article· en· W4391136254 on OpenAlexafffund
Julie Beadle, Lorienne M. Jenstad, Diana Cochrane, Jeff Small

Bibliographic record

VenueInternational Journal of Audiology · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of British Columbia
FundersFaculty of Medicine, University of British Columbia
KeywordsAudiologyPerceptionMedicineHearing lossYoung adultGerontologyPsychology

Abstract

fetched live from OpenAlex

Objective: To investigate older and younger adults' perceptions of older and younger adults who wear hearing aids.Design: Participants completed two Implicit Association Tests: One with images of older adults (OA-IAT) and one with images of younger adults (YA-IAT), either wearing or not wearing hearing aids.Participants also rated age, attractiveness, and intelligence of younger and older adults pictured with or without a hearing aid.Study sample: Thirty older adults (M age 70 years, SD 4.38) and 30 younger adults (M age 23 years, SD 3.01) who reported not having hearing aids or a diagnosed hearing impairment.Results: For both IATs, older and younger participants responded faster and more accurately when images of individuals wearing hearing aids were paired with negative words in comparison to positive words.Photo ratings did not vary in relation to the presence or absence of hearing aids for either age group. Conclusion:Although the photo rating tasks indicate neutral explicit attitudes towards individuals who wear hearing aids, our interpretation of the IAT results indicates that younger and older adults may hold negative implicit attitudes towards both older and younger hearing aid users.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.158

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.018
GPT teacher head0.319
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2024
Admission routes2
Has abstractyes

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