Development and Psychometric Evaluation of the FACE-Q Aging Appraisal Scale and Patient-Perceived Age Visual Analog Scale
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The primary outcome measures for patients who undergo aesthetic facial procedures are quality of life and satisfaction with appearance. The FACE-Q, a new patient-reported outcome (PRO) instrument composed of independently functioning scales, is designed to measure a broad range of important outcomes in patients who undergo cosmetic surgical and/or nonsurgical facial procedures. OBJECTIVES: The authors describe the development and psychometric evaluation of the FACE-Q Aging Appraisal Scale and the FACE-Q Patient-Perceived Age Visual Analog Scale (VAS). METHODS: International guidelines for creating PRO instruments were strictly observed throughout development of the FACE-Q scales. Qualitative methods were used to identify the concepts most important to patients who received aesthetic facial procedures. These were turned into "items"-and the resultant FACE-Q Aging Appraisal Scale was field tested, along with the Patient-Perceived Age VAS, in 288 patients who underwent cosmetic surgical and/or nonsurgical facial procedures. RESULTS: Rasch measurement theory and traditional psychometric methods confirmed the reliability and validity of the scales. CONCLUSIONS: The FACE-Q Aging Appraisal Scale and Patient-Perceived Age VAS are psychometrically sound, condition-specific PRO instruments with excellent reliability and validity. They enable accurate outcome assessments in patients who undergo aesthetic facial procedures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it