Psychological Screening Measures for Cosmetic Plastic Surgery Patients: A Systematic Review
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
With the increasing popularity of cosmetic surgery procedures, preoperative psychological assessment of cosmetic surgery patients may improve outcomes by highlighting patient expectations and motivations, as well as by identifying those who may require psychological referral. In this article, the authors describe a systematic literature review to identify and evaluate current self-report tools used in the psychological screening of cosmetic surgery patients prior to surgery. Articles related to the preoperative mental health assessment of cosmetic surgery patients were identified by searching MEDLINE, EMBASE, HAPI, CINAHL, PsycINFO, and the Cochrane Central Register of Controlled Trials through November 2010. The full text of potentially relevant articles was examined by 2 reviewers, and articles that met the inclusion criteria were reported. Close reading of 100 full-text articles showed that although a variety of instruments are currently being used as preoperative assessment tools, there are limitations to their validity and usefulness in the screening of cosmetic surgery patients. To properly assess cosmetic surgery patients, a scientifically sound and clinically useful instrument is needed.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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