Abstracts from the 6th international conference on prevention & infection control (ICPIC 2021)
Bibliographic record
Abstract
Introduction: With the use of elastomeric-half mask respirators in healthcare settings, it has been reported that the verbal communication is decreased or compromised when wearing the masks (Palmiero, Symons, Morgan and Schaffer, 2016).This study examines the communication effectiveness of this innovation (elastomeric reusable respirator) and others in the industry, using speech intelligibility objective scoring, and qualitative research.Objectives: This research measured the acoustical performance, speech transmission index (STI) (Palmeiro, et al., 2016) on an innovative elastomeric respirator, and others utilized in health care, according to IEC 60268-16 Objective rating of speech intelligibility standard.Methods: STI measurements were obtained in a semi-anechoic acoustic test chamber/quiet room with background noise levels of less than 15 dBA.Then higher levels of background noise (57.6 dBA and 72 dBA, Zunn and Downey, 2005) was added to the test room and additional STI tests will be conducted in the presence of these elevated background noise levels.The "voice" signal was emitted by the artificial voice of an acoustic head and torso simulator (HATS) and was one of two types of sound: the STI test waveform or the the Harvard sentences sound waveform (phonetically balanced and very clearly spoken human speech).The background noise portion, when used, was added separately by a high fidelity loudspeaker.The speech and STI waveform sounds were produced inside the test room at the sound level of 60 dBA (1 m microphone distance).Results: In an environment with no background noise, the innovation of the re-usable elastomeric respirator, yielded the highest STI rating compared to other elastomeric respirators (0.90-0.91) or excellent rating.Other elastomeric respirators tested, showing fair, to low excellent range.The re-usable elastomeric respirator innovation had a 0.03 less in speech intelligibility than, single use N95 STI rating.Conclusion: Speech intelligibility is complex, and incorporates subjective (listener) criteria, objective speech intelligibility, and background noise, as well as the environment.Additional subjective testing, with the recorded sound files, with a randomized control clinical trial would benefit this research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.186 | 0.057 |
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 source (direct Gemma or distilled Codex), 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".