Evaluation of Skin Barrier Condition among Physicians and Dentists
Bibliographic record
Abstract
Abstract: Background: Physicians and dentists are at risk for chronic hand eczema, but their skin barrier condition has rarely been investigated before. Objective: To objectively assess the skin barrier condition among physicians and dentists. Methods: This cross-sectional epidemiological study included an occupational questionnaire, medical examination of hand skin, skin transepidermal water loss (TEWL), and pH measurements, analyzed in 5 groups (N = 37 in each): physicians-nonsurgeons, physicians-surgeons, dentists-nonsurgeons, dentists-surgeons, and control group (unexposed workers). Results: Critical skin condition (TEWL >30 g/[m 2 ·h]) was found in 14% of control workers, 14% physicians nonsurgeons, 22% physicians surgeons, 27% dentists nonsurgeons, and 43% dentists surgeons. The latter had the worst stratum corneum condition indicated by a TEWL median of 25.80 g/(m 2 ·h) (interquartile range [IQR] 19.24–34.31). Hand skin pH was highest among dentists with nonsurgical specializations, with a median of 5.33 (IQR 5.15–5.60), where 38% of them had pH >5.5. Male sex ( P < 0.001) and glove use for >1 h/day ( P = 0.009) were associated with elevated hand TEWL values, whereas female sex ( P < 0.001) and glove use for >4 h/day with elevated pH values ( P < 0.001). Conclusions: Prolonged glove usage and dental profession, especially surgical work, significantly affect the skin barrier condition. This study was the first to objectively determine skin barrier condition among dentists and physicians.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".