Signs of Facial Aging in Men in a Diverse, Multinational Study: Timing and Preventive Behaviors
Bibliographic record
Abstract
BACKGROUND: Men are a growing patient population in aesthetic medicine and are increasingly seeking minimally invasive cosmetic procedures. OBJECTIVE: To examine differences in the timing of facial aging and in the prevalence of preventive facial aging behaviors in men by race/ethnicity. METHODS: Men aged 18 to 75 years in the United States, Canada, United Kingdom, and Australia rated their features using photonumeric rating scales for 10 facial aging characteristics. Impact of race/ethnicity (Caucasian, black, Asian, Hispanic) on severity of each feature was assessed. Subjects also reported the frequency of dermatologic facial product use. RESULTS: The study included 819 men. Glabellar lines, crow's feet lines, and nasolabial folds showed the greatest change with age. Caucasian men reported more severe signs of aging and earlier onset, by 10 to 20 years, compared with Asian, Hispanic, and, particularly, black men. In all racial/ethnic groups, most men did not regularly engage in basic, antiaging preventive behaviors, such as use of sunscreen. CONCLUSION: Findings from this study conducted in a globally diverse sample may guide clinical discussions with men about the prevention and treatment of signs of facial aging, to help men of all races/ethnicities achieve their desired aesthetic 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".