Development of a new patient‐reported outcome measure to evaluate treatments for acne and acne scarring: the <scp>ACNE</scp> ‐Q
Bibliographic record
Abstract
BACKGROUND: Psychosocial concerns represent important outcomes in studies of treatments for acne and acne scarring. Also important, but largely overlooked, is the concept of appearance. OBJECTIVES: To design an acne-specific patient-reported outcome measure for acne and acne scarring. METHODS: We used a mixed-methods approach. Phase I involved 21 patient interviews that were audio-recorded, transcribed and coded. Concepts were identified and developed into scales that were refined through 10 cognitive interviews and input from 16 clinical experts. Phase II involved data collection at hospital and community-based dermatology clinics in Canada and the U.S.A. Eligible participants were aged 12 years and older with acne and/or acne scars on the face, chest and/or back. Rasch Measurement Theory (RMT) analyses were performed to examine psychometric properties. RESULTS: Phase I led to the development of seven scales that measure appearance of facial skin, acne (face, chest and back) and acne scars, acne-specific symptoms and appearance-related distress. In phase II, 256 patients completed the ACNE-Q. RMT analysis provided evidence that the items of each scale worked together conceptually and statistically. Most participants scored within the range of measurement for each scale (81·9-93·1%). Reliability was high, with person separation index values and Cronbach alpha values > 0·90 for the appearance scales, ≥ 0·87 for appearance-related distress and ≥ 0·75 for symptoms. Worse scores on appearance scales correlated with worse symptom scores and more appearance-related distress. CONCLUSIONS: The ACNE-Q is a rigorously developed instrument that can be used to measure appearance and other patient-centred concerns. What's already known about this topic? Acne is a common dermatological condition that can have an important impact on psychosocial function. Current patient-reported outcome measures specific to acne focus mostly on measuring psychological and social impact. What does this study add? The ACNE-Q provides a set of independently functioning scales that measure appearance of facial, back and chest acne, acne scarring and facial skin. Additional scales measure appearance-related distress and acne symptoms. What are the clinical implications of this work? ACNE-Q provides the dermatology community with a rigorously developed patient-reported measure for acne that can be applied in clinical trials, research and patient care. The measurement of appearance by ACNE-Q scales is more comprehensive than in other instruments providing important information on appearance of their acne and/or acne scars from the patient perspective.
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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 | 0.023 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".