Baseline Quality of Life As Measured by Skindex-16+5 in Patients Presenting to a Referral Center for Patch Testing
Bibliographic record
Abstract
BACKGROUND: The impact of skin disease on heath-related quality of life (QoL) is often underrecognized, and there is little research about health-related QoL in patch-tested populations. OBJECTIVE: A pilot study to assess baseline QoL in dermatitis patients referred to a specialized center for patch testing. METHODS: A convenience sample of patients presenting for patch testing (n = 107) completed a survey, Skindex-16+5, which measures QoL in four domains: symptoms, emotions, functioning, and occupational. RESULTS: Responses were indexed from 0 (never bothered) to 100 (always bothered). Emotions (mean, 67; SD +/- 27) and symptoms (mean, 60; SD +/- 27) demonstrated the lowest QoL. Patients with hand involvement had a worse QoL in all areas, including the occupational domain, compared to patients without hand involvement. Limitations of the study included the referral clinic population and convenience sample. Survey questions added to Skindex-16 regarding the occupational domain have not been validated. CONCLUSIONS: Patients referred for patch testing endorse a highly negative impact of the disease on their emotional QoL and are also greatly bothered by symptoms. Patch-tested patients with hand dermatitis had a significantly lower QoL across all areas as compared to tested patients without hand involvement. Facial involvement, duration of skin problem, atopic history, occupation relationship, or positive patch-test results were not correlated with QoL.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".