Maxillary obturators: The relationship between patient satisfaction and speech outcome
Bibliographic record
Abstract
BACKGROUND: Patient satisfaction with a maxillary obturator has been studied in relation to extent of surgical defect, sociodemographic characteristics, scores on mental health inventories, and psychosocial adjustment to illness scales. However, review of the literature reveals limited study of the relationship between patient satisfaction with an obturator and clinical speech outcome measures. The purpose of this study is to relate patient satisfaction scores obtained by questionnaire with those obtained by means of clinical speech measurements. METHODS: Acoustical, aeromechanical, and perceptual measurements of speech were collected for 20 patients after receiving a definitive obturator. Patient satisfaction with their obturator was later measured with the Obturator Functioning Scale (OFS). RESULTS: Results reveal that poorer aeromechanical speech results were associated with patient-reported avoidance of social events, whereas lower speech intelligibility outcomes were related to overall poorer perception of speech function on the OFS. Several background patient characteristics were significantly related to several responses on the OFS and to the aeromechanical assessment outcomes. CONCLUSIONS: Results from instrumental assessments of speech seem to be informative regarding not only speech outcome but also a patient's satisfaction with the obturator. Consideration of background patient characteristics is important when interpreting both clinically obtained and patient-perceived outcomes.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".