Glove Use and Glove Education in Workers with Hand Dermatitis
Bibliographic record
Abstract
BACKGROUND: Occupational skin diseases are common. The occurrence of occupational skin diseases represents a failure of primary prevention strategies that may include the use of personal protective equipment, most commonly gloves. OBJECTIVE: The objective of this study was to describe current glove use and education practices related to gloves in workers being assessed for possible work-related hand dermatitis. METHODS: Participants included consecutive patients being assessed for possible work-related hand dermatitis. A self-administered questionnaire obtained information on demographics, workplace characteristics and exposures, glove use, and education regarding gloves. RESULTS: Ninety percent of the 105 participants reported using gloves. Only 44% had received training related to glove use in the workplace. Major gaps in training content included skin care when using gloves, warning signs of skin problems, and glove size. If the worker indicated no glove training received, the majority reported they would have used gloves if such training was provided. CONCLUSIONS: Although the majority of workers being assessed wore gloves, the minority had received training related to glove use. Particular gaps in training content were identified. Those who had not received training noted they would likely have used gloves if training had been provided.
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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 | 0.003 |
| 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) | 0.003 | 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".