The Toronto Outcome Measure for Craniofacial Prosthetics: Reliability and Validity of a Condition-Specific Quality-of-Life Instrument
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to refine the Toronto Outcome Measure for Craniofacial Prosthetics (TOMCP), present evidence for its reliability and validity, and use the instrument to explore differences in quality of life between prostheses made with chlorinated polyethylene (CPE) (experimental) and silicone (control). MATERIALS AND METHODS: As part of a multicenter prospective controlled randomized double-blind single-crossover clinical trial of the two materials, the TOMCP was administered at the start and end of two 4-month study arms, during which 42 patients wore prostheses made from one material then the other. Reliability was assessed at the crossover. To determine validity of the TOMCP, the Linear Analogue Self-Assessment (LASA-12) and the Short-Form 8 (SF-8) were also administered with the TOMCP. The TOMCP was reduced by removing items that were unreliable, had poorly distributed answers, showed increased internal consistency after their removal, or were too highly correlated with more than one other item. The tests of reliability and validity were then repeated. Finally, the reduced instrument was used to test for differences in quality of life between prostheses made of the two materials. RESULTS: The item reduction tactics pared the 52-item instrument down to 27 items. The correlations of both TOMCP versions with the LASA-12 and the SF-8 were found to be statistically significant, providing evidence of the validity of the TOMCP. The instrument revealed significantly better quality of life with silicone rather than CPE prostheses. CONCLUSIONS: Both versions of the TOMCP were found to be reliable and valid. The instrument was able to show differences in quality of life between two materials.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".