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Record W4323294934 · doi:10.26355/eurrev_202302_31386

Extra-auditory effects of noise exposure in school workers and preventive measures: a systematic review.

2023· review· en· W4323294934 on OpenAlexaboutno aff
Simone De Sio, R Perri, F Durel Tchaptchet, G Buomprisco, N Mucci, F Cedrone, V Traversini, G Arcangeli, P Nataletti, G La Torre

Bibliographic record

VenuePubMed · 2023
Typereview
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsNoise (video)MedicineScale (ratio)PsychologySystematic reviewApplied psychologyMedical educationMEDLINEComputer sciencePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: Noise is still today one of the main causes of occupational diseases; in fact, in Italy in the three-year period 2019-2022, hearing loss represented 15% of all occupational diseases recognized by the National Institute for Insurance against Accidents at Work. The extra-auditory effects related to noise exposure also require particular attention, because they can interfere with mental activities that require concentration, memory and ability to deal with complex problems, causing sleep and learning disorders. For this reason, acoustic comfort is considered a fundamental requirement for obtaining an optimal degree of well-being in closed environments. In schools, a high degree of noise pollution not only makes it difficult for students to listen and learn, but also affects school workers. The aim of this study was to perform a systematic review of international literature and analysis of the preventive measures of extra-auditory effects among school workers. MATERIALS AND METHODS: The presentation of this systematic review is in accordance with the PRISMA statement. The methodological quality of the selected studies was assessed with specific rating tools (INSA, Newcastle Ottawa Scale, JADAD, JBI scale and AMSTAR). Only publications in English were selected. No restrictions were applied for the publication type. We excluded articles not concerned with the extra-auditory effects of noise exposure in school workers and preventive measures, findings of less academic significance, editorial articles, individual contributions, and purely descriptive studies published in scientific conferences. RESULTS: Online research indicated 4,363 references: PubMed (2,319), Scopus (1,615) and Cochrane Library (429) have been consulted; 30 studies were included in this review (5 narrative or systematic reviews and 25 original articles). Regarding the scores of narrative reviews, the INSA score showed an average and a median value of 6.5, thus indicating an intermediate/high quality of the studies. Regarding the scores of systematic reviews, the AMSTAR score showed an average of 6.7 and a median and a modal value of 6, thus indicating a high quality of the studies. The scores assigned to the original articles have an average and median value of 7 and a modal value of 6 and this demonstrates an intermediate/high quality of the studies. CONCLUSIONS: We can assume that, as it is highlighted by this study, to date these consequences are not considered at the legislative level for the protection of exposed workers. The extra-auditory effects impacting health afterward environmental noise exposure are many and widespread. Therefore, there is a need for interventions to be carried out by institutions and that the physician of the schools, during health surveillance, investigates the effects and clinical manifestations, in order to prevent disorders and deficits highlighted by our study.

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)0.006
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.069
GPT teacher head0.381
Teacher spread0.312 · 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 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

Citations3
Published2023
Admission routes1
Has abstractyes

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