Review: the whispered voice test is accurate for detecting hearing impairment in children and adults
Bibliographic record
Abstract
Pirozzo S, Papinczak T, Glasziou P. Whispered voice test for screening for hearing impairment in adults and children: systematic review. BMJ 2003;327:967.[OpenUrl][1][Abstract/FREE Full Text][2] Q Is the whispered voice test accurate for detecting hearing impairment in children and adults? ### ![Graphic][3] Data sources: Medline, EMBASE/Excerpta Medica, and Science Citation Index (to June 2002); the web (for unpublished theses); reference lists; and authors. ### ![Graphic][4] Study selection and assessment: 2 reviewers independently selected cross sectional studies in any language if they evaluated the whispered voice test; the reference test, audiometry, was given to ⩾80% of participants; and sensitivity and specificity were reported (or calculable). ### ![Graphic][5] Outcomes: sensitivity and specificity. 8 English language studies were included. 4 studies included 256 adults (age range 17–96 y). The prevalence of … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft.stitle%253DBMJ%26rft.aulast%253DPirozzo%26rft.auinit1%253DS.%26rft.volume%253D327%26rft.issue%253D7421%26rft.spage%253D967%26rft.atitle%253DWhispered%2Bvoice%2Btest%2Bfor%2Bscreening%2Bfor%2Bhearing%2Bimpairment%2Bin%2Badults%2Band%2Bchildren%253A%2Bsystematic%2Breview%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.327.7421.967%26rft_id%253Dinfo%253Apmid%252F14576249%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=327/7421/967&atom=%2Febnurs%2F7%2F2%2F56.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif
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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 | 0.007 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".