Quality of Life and Contact Dermatitis: A Disease-Specific Questionnaire
Bibliographic record
Abstract
BACKGROUND: Contact dermatitis (CD) is a chronic disease with a significant impact on quality of life (QoL). There have been relatively few reports in the literature on specific QoL outcomes for patients suffering from CD. OBJECTIVES: To develop a new instrument specifically designed to measure QoL in CD and to investigate which disease features could strongly influence QoL. METHODS: Three hundred seventy-two patients affected by CD were administered a 20-item questionnaire, which comprised some questions taken and modified from the Dermatology Life Quality Index and the Skindex 16. Six more items were added. Univariate analysis and a chi-square test were performed. RESULTS: Females reported lower QoL scores than males. Three aspects (itching, discomfort, and difficulty in daily activities) were strongly associated with a poor QoL; even if patients who experienced difficulty in using their hands at work had a poor QoL, the statistical significance was very low. CONCLUSION: A CD-specific questionnaire can be used to understand a priori the impact on psychological behaviour of the patient and can lead to specific choices, such as the appropriate therapy to be used, the evaluation of treatment efficacy, the choice of preventive devices, and the comparison with QoL of other dermatoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".