Quality of Life of Patients with Allergic Contact Dermatitis: An Exploratory Analysis by Gender, Ethnicity, Age, and Occupation
Bibliographic record
Abstract
BACKGROUND: Little has been published regarding the impact of gender, ethnicity, age, and occupation on the quality of life (QoL) of patients with allergic contact dermatitis (ACD). OBJECTIVES: This study investigated the relationship between QoL scores for patients with ACD and variables such as gender, ethnicity, age, and occupation. METHODS: Four hundred twenty-eight patients with ACD were mailed a QoL questionnaire modified from Skindex-16 to include an additional five items pertaining to occupational impact. The QoL scores were analyzed to ascertain factors that affect QoL in patients with ACD. RESULTS: The response rate was 35%. Non-Caucasians reported lower QoL scores than did Caucasians within the functioning scale. There were no statistically significant gender-related differences in QoL scores although females reported a higher degree of emotional distress. Younger subjects were more likely to have lower QoL scores within the functioning and occupational scales. Industrial workers reported the worst occupational QoL, followed by office workers. Occupation was the variable that significantly affected the greatest number of survey subjects, followed by age, ethnicity, and gender. CONCLUSIONS: Three of the four variables examined had a significant association with QoL. Non-Caucasians, younger subjects, and industrial workers reported a significantly worse QoL due to ACD. There were no statistically significant gender-related differences in QoL scores.
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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 | 0.001 |
| 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) | 0.002 | 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".