Development of a Comprehensive Quality-of-Life Measure for Facial and Torso Acne
Bibliographic record
Abstract
Background Acne is a chronic skin disorder which generally presents in adolescence but continues into adulthood, and negatively affects both physical and psychosocial well-being. Presently, there are no validated acne-specific quality-of-life (QoL) measures that include dimensions for both facial and torso acne. OBJECTIVE: The objective of this study was to develop a QoL instrument for both facial and torso acne (CompAQ) in accordance with recommended standards. METHODS: A literature review and Delphi survey of patients and clinicians were used to develop the conceptual framework for outcomes perceived important to acne patients. An initial version of the measure was developed, CompAQ-v1, and pilot tested with patients via cognitive interviews. RESULTS: The Delphi survey generated 4 domains (physical, psychological, sociological, and treatment) and 54 items. These, along with a literature review and input from clinical experts, informed the development of the CompAQ-v1. Eleven cognitive interviews were conducted, resulting in the second version of the measure, CompAQ-v2. Psychometric validation resulted in the final 20-item CompAQ measure comprising 5 domains. An abbreviated 5-item measure was also developed (CompAQ-SF). CONCLUSION: CompAQ and CompAQ-SF are instruments intended to evaluate QoL in patients with acne on their face or torso. The former is a 21-item QoL intended for research, while the latter is intended for clinical practice.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".