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Record W4383482296 · doi:10.1097/aud.0000000000001396

Association Between Adult-Onset Hearing Loss and Income: A Systematic Review

2023· review· en· W4383482296 on OpenAlexaboutno aff
Audrey Mossman, Virgil K DeMario, Carrie Price, Stella Seal, Amber Willink, Nicholas S. Reed, Carrie L. Nieman

Bibliographic record

VenueEar and Hearing · 2023
Typereview
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsHearing lossPopulationSocioeconomic statusMedicinePsychologyDemographyGerontologyAudiologyEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Hearing loss has been shown to be associated with both negative health outcomes and low socioeconomic position, including lower income. Despite this, a thorough review of the existing literature on this relationship has not yet been performed. OBJECTIVES: To evaluate available literature on the possible association between income and adult-onset hearing loss. DESIGN: A search was conducted in eight databases for all relevant literature using terms focused on hearing loss and income. Studies reporting the presence or absence of an association between income and hearing loss, full-text English-language access, and a predominantly adult population (≥18 years old) were eligible. The Newcastle-Ottawa Quality Assessment Scale was used to assess risk of bias. RESULTS: The initial literature search yielded 2994 references with three additional sources added through citation searching. After duplicate removal, 2355 articles underwent title and abstract screening. This yielded 161 articles eligible for full-text review resulting in 46 articles that were included in qualitative synthesis. Of the included studies, 41 of 46 articles found an association between income and adult-onset hearing loss. Due to heterogeneity among study designs, a meta-analysis was not performed. CONCLUSIONS: The available literature consistently supports an association between income and adult-onset hearing loss but is limited entirely to cross-sectional studies with the directionality remaining unknown. An aging population and the negative health outcomes associated with hearing loss, emphasize the importance of understanding and addressing the role of social determinants of health in the prevention and management of hearing loss.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.102
GPT teacher head0.372
Teacher spread0.270 · 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 designSystematic review
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

Citations10
Published2023
Admission routes1
Has abstractyes

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