Further psychometric evaluation of the WOUND‐Q: A responsiveness study
Bibliographic record
Abstract
The WOUND-Q is a modular patient-reported outcome measure (PROM) with 13 scales measuring constructs across 4 domains (i.e., wound characteristics, health related quality of life, experience of care and wound treatment). The psychometrics of the WOUND-Q were previously assessed and the 13 scales evidenced good validity and reliability. However, the responsiveness (i.e., ability to detect clinical change) of the WOUND-Q has yet to be assessed. The objective of this study was to evaluate responsiveness for 9 WOUND-Q scales that assess outcomes, in a sample of people 18 years of age or older with chronic wounds that were present for at least 3 months. This study conducted a 4 month follow-up of 421 participants who completed the WOUND-Q as part of a previous psychometric study. Participants completed an online survey answering questions about their current wound state (e.g., number, type, size, smell, drainage), anchor questions about change, as well as the WOUND-Q scales that they had completed in their initial assessment. Pre-defined hypotheses were tested with a 75% acceptance threshold indicating sufficient evidence of responsiveness. Minimally important differences (MIDs) were also calculated using both anchor-based and distribution-based methods. Of 390 invited participants, 320 provided responses, ranging in age from 19 to 84 years. Acceptance of hypotheses ranged from 60% to 100%, with only the Symptom scale not meeting the 75% threshold. The findings of this study provide evidence that the WOUND-Q can validly measure clinical change in patients with chronic wounds.
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 | 0.069 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".