Facilitators and barriers to implementing Hearing Conservation Programmes in industrial workplaces: a systematic review
Bibliographic record
Abstract
Noise-induced hearing loss (NIHL) remains a serious occupational risk in industrial settings with constant high noise exposure. Although Hearing Conservation Programmes (HCPs) are widely implemented, their effectiveness is limited by funding shortages, poor training and low compliance. This systematic review examines factors that facilitate or hinder HCP implementation, variations in program outcomes and the influence of employee attitudes, behavior and regulatory compliance. Methodological quality was assessed using the Effective Public Health Practices Project (EPHPP) tool, and risk of bias in non-randomized studies was evaluated with Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I).We searched PubMed, Web of Science, Scopus and Cochrane for English-language studies on industrial HCPs published between 2000 and 2024. Eligible designs included randomised or non-randomised trials, observational studies and mixed methods. Data extraction was guided by a standardised form capturing programme components such as training, monitoring, compliance strategies, participant characteristics and outcome indicators, which included hearing protection device usage, NIHL incidence and compliance.Nine studies from various industries met the criteria. Key facilitators included management commitment, worker involvement and tailored interventions that improved compliance and reduced NIHL. Common barriers were inconsistent training, discomfort with protective equipment and gaps between programme goals and workplace conditions. The findings also highlighted that consistent regulatory compliance and a supportive organisational culture play a critical role in the successful implementation of HCPs.Effective HCPs require context-specific designs addressing workplace barriers and enhancing facilitators. Future research should prioritise longitudinal studies to evaluate long-term sustainability and impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".