A critical review of the literature on comfort of hearing protection devices: analysis of the comfort measurement variability
Bibliographic record
Abstract
Objective. This article proposes a comprehensive literature review of past works addressing hearing protection device (HPD) comfort with the aim of identifying the main sources of variability in comfort evaluation. Methods. A literature review of study samples was performed: documents were hand searched and Internet searched using PubMed, Web of Science, Google Scholar, ProQuest Dissertations and Theses Professional, Scopus or Google search engines. While comfort constructs and measurement methods are reviewed for both earplugs and earmuff HPD types, results and analyses are provided for earplugs only. Results. The literature shows that the multiple sources of the perceived comfort measurement variability are related to the complexity of the concept of comfort and to the various physical and psychosocial characteristics of the triad ‘environment/person/earplug’, which differ from one study to the other. Conclusions. Considering the current state of knowledge and in order to decrease comfort measurements variability, it is advised to: (a) use a multidimensional construct of comfort and derive a comfort index for each comfort dimension;, (b) use exhaustive and valid questionnaires; (c) quantify as many triad characteristics as possible and use them as independent or control variables; (d) assess the quality of the earplug fitting and the attenuation efficiency.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".