MétaCan
Menu
Back to cohort
Record W3046265197 · doi:10.1108/ijhg-01-2020-0004

Here's to sound action on global hearing health through public health approaches

2020· article· en· W3046265197 on OpenAlexaffabout
Farah M. Shroff, David Jung

Bibliographic record

VenueInternational Journal of Health Governance · 2020
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPublic healthRecreationHearing lossOccupational safety and healthNoise-induced hearing lossEnvironmental healthMedicinePublic relationsPolitical scienceNoise exposureAudiologyNursingPathology

Abstract

fetched live from OpenAlex

Purpose A global pandemic, non-occupational noise-induced hearing loss (NIHL) is a completely preventable public health problem, which receives limited air time. This study has dual purposes: to contribute to scholarly literature that puts non-occupational NIHL on the global priority map and to effect change in the City of Vancouver's policies toward noise. Design/methodology/approach Experts in public health and hearing health were contacted in addition to a scoping literature search on PubMed. Information pertaining to both developed and developing countries was obtained, and comparison was made to Canada where possible. The authors met with elected officials at the City of Vancouver to inform them of the win–win aspects of policies that promoted better hearing. Findings Non-occupational NIHL is an underappreciated issue in Canada and many other countries, as seen by the lack of epidemiological data and public health initiatives. Other countries, such as Australia, have more robust research and public health programs, but most of the world lags behind. Better hearing health is possible through targeted campaigns addressing root causes of non-occupational, recreational noise – positive associations with loud noise. By redefining social norms so that soft to moderate sounds are associated with positive values and loud sounds are negatively attributed, the societies will prevent leisure NIHL. The authors recommend widespread national all-age campaigns that benefit from successful public health campaigns of the past, such as smoking cessation, safety belts and others. Soft Sounds are Healthy (SSH) is a suggested name for a campaign that would take many years, ample resources and sophisticated understanding of behavior change to be effective. Research limitations/implications A gap exists in the collection of non-occupational NIHL data. Creating indicators and regularly collecting data is a high priority for most nations. Beyond data collection, prevention of non-occupational NIHL ought to be a high priority. Studies in each region would propel understanding, partly to discern the cultural factors that would predispose the general population to change favorable attitudes toward loud sounds to associations of moderate sounds with positivity. Evaluations of these campaigns would then follow. Practical implications Everyday life for many people around the world, particularly in cities, is loud. Traffic, construction, loudspeakers, music and other loud sounds abound. Many people have adapted to these loud soundscapes, and others suffer from the lack of peace and quiet. Changing cultural attitudes toward loud sound will improve human and animal health, lessen the burden on healthcare systems and positively impact the economy. Social implications Industries that create loud technologies and machinery ought to be required to find ways to soften noise. Regulatory mechanisms that are enforced by law and fines ought to be in place. When governments take up the banner of hearing health, they will help to set a new tone toward loud sounds as undesirable, and this will partially address the root causes of the problem of non-occupational NIHL. Originality/value Very little public health literature addresses NIHL. It is a relatively ignored health problem. This project aims to spurn public health campaigns, offering our own infographic with a possible title of Soft Sounds are Healthy (SSH) or Soft Sounds are Sexy (SSS). The study also aimed to influence city officials in the authors’ home, Vancouver, and they were able to do this.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.753
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.426
GPT teacher head0.499
Teacher spread0.073 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Health GovernanceSame topicNoise Effects and ManagementFrench-language works237,207