Measuring the Impact of Surgical and Non-surgical Facial Cosmetic Interventions Using FACE-Q Aesthetic Module Scales: A Systematic Review and Meta-Analysis
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Bibliographic record
Abstract
Background: The FACE-Q Aesthetic module measures patient-important outcomes following surgical and non-surgical facial cosmetic procedures. Objective: The primary aim of this systematic review was to summarize the pre- to post-intervention mean differences of facial aesthetic interventions that evaluate outcomes using the FACE-Q Face Overall, Psychological, and Social scales. Methods: Ovid Medline, Embase, Cochrane, and Web of Science databases were searched on December 20, 2022 with the assistance of a health-research librarian (CRD42023404238). Studies that examined any surgical or non-surgical facial aesthetic intervention in adult patients and used FACE-Q Aesthetics Face Overall, Psychological, and/or Social scales to measure participants before and after treatment were included for analysis. Results: Of 914 potential articles screened, 35 studies met the inclusion criteria. Most studies evaluated surgical (n = 22, 62.9%) versus non-surgical facial cosmetic interventions (n = 13, 37.1%). Rhinoplasty [37.0 points, 95% CI 24.7-49.3, P < 0.01] demonstrated the largest weighted increase in Face Overall scores, whereas the largest increase in Psychological [67.1 points, 95% CI 62.9–71.3, P < 0.01] and Social [63.9 points, 95% CI 53.2–74.6, P < 0.01] scores was demonstrated by a single study evaluating surgical forehead lifts, respectively. Conclusions: This meta-analysis leverages FACE-Q Aesthetic module scoring to present the expected mean differences in Face Overall, Psychological, and Social scale scores for various surgical and non-surgical facial cosmetic interventions. The findings from this review may be used to indirectly compare interventions and contribute to sample size calculations when planning future studies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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