Patient-Reported Outcome Measures in Dermatology: A Systematic Review
Bibliographic record
Abstract
By relying on data from existing patient-reported outcome measures of quality of life, the true impact of skin conditions on patients' lives may be underestimated. This study systematically reviewed all dermatology-specific (used across skin conditions) patient-reported outcome measures and makes evidence-based recommendations for their use. The study protocol is registered on PROSPERO (CRD42018108829). PubMed, PsycInfo and CINAHL were searched from inception to 25 June 2018. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) criteria were used to assess the measurement properties and methodological quality of studies. A total of 12,925 abstracts were identified. Zero patient-reported outcome measures were assigned to category A (ready for use without further validation), 31 to category B (recommended for use, but only with further validation) and 5 to category C (not recommended for use). There is no gold-standard dermatology-specific patient-reported outcome measure that can be recommended or used without caution. A new measure that can comprehensively capture the impact of dermatological conditions on the patient's life is needed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".