Assessing self-reported measures of voice disability in tracheoesophageal speakers.
Bibliographic record
Abstract
OBJECTIVE: current instruments for evaluating quality of life in individuals treated for head and neck cancer often contain a speech-related item; however, none provide a dedicated measure of self-perceived voice-related quality of life. Therefore, this study sought to assess the utility of the Voice-Related Quality of Life (V-RQOL) instrument in a group of individuals who use tracheoesophageal (TE) speech following total laryngectomy for laryngeal cancer. DESIGN: this exploratory, retrospective study accessed individuals who used TE speech as their primary mode of communication. SETTING: Data were collected at a university centre. METHODS: fifteen male and 15 female TE speakers were age matched (± 3 years) and their V-RQOL scores were evaluated. MAIN OUTCOME MEASURES: the self-report V-RQOL was employed to evaluate participants' perceptions of their voice-related quality of life. The V-RQOL yields two subscales, social-emotional functioning and physical functioning, as well as a total score. RESULTS: analyses revealed no statistically significant differences across gender, thus permitting descriptive evaluation of group data. Data suggest that varied degrees of voice-related disability exist for both physical and social-emotional functioning, with participants generally reporting better social-emotional scores. CONCLUSIONS: based on these preliminary data, the V-RQOL may offer an easy and time-efficient clinical measure of postlaryngectomy voice disability for alaryngeal speakers. These findings suggest that the V-RQOL may be used with this clinical population and may serve to identify voice-related deficits that can be targeted for intervention as part of a patient's postlaryngectomy rehabilitation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".