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Record W4386564187 · doi:10.1093/occmed/kqad084

Systematic review of hearing loss in dental professionals

2023· article· en· W4386564187 on OpenAlexaboutno aff
Joseph Hartland, G Tejada, E J Riedel, Anqi Chen, O. A. J. Mascarenhas, Jeroen Kroon

Bibliographic record

VenueOccupational Medicine · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsHearing lossAudiologyMedicineDentistry

Abstract

fetched live from OpenAlex

BACKGROUND: Hearing loss leads to increased irritability and disengagement in social activities and conversations, which may impact quality of life. Dental professionals are at risk of developing hearing loss through daily exposure to noise from a wide range of equipment that produces significantly high decibels and noise frequencies. AIMS: The aim of this systematic review was to investigate the risk of hearing loss in dental professionals, including dentists, dental specialists, dental hygienists and dental assistants. METHODS: This review was conducted following the Cochrane Handbook for Systematic Reviews. PubMed, Scopus, Embase, Cochrane, Science Direct, Google Scholar and ProQuest were searched up to March 2023. Seventeen of 416 studies met the inclusion criteria. Quality assessment was performed according to the Newcastle-Ottawa Scale for cohort and case-control studies, and a modified version of this tool for cross-sectional studies. RESULTS: The majority of included studies (82%) found a positive association with hearing loss for dentists and dental specialists, with years of clinical experience identified as a prominent risk factor. Dental hygienists and dental assistants were less commonly reported in the literature. Difference between the left and right ears was found in 71% of studies, with the left ear more affected in both dentists and dental assistants due to proximity to the noise-inducing equipment. CONCLUSIONS: Dental professionals are at risk of hearing loss in their workplace, especially linked to years of clinical experience, which highlights the need for prevention and appropriate ear-protective devices.

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.088
GPT teacher head0.403
Teacher spread0.315 · 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.

Study designSystematic review
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

Citations13
Published2023
Admission routes1
Has abstractyes

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