Identifying the Impacts of Acne: A Delphi Survey of Patients and Clinicians
Bibliographic record
Abstract
BACKGROUND: Acne can adversely impact those affected in multiple dimensions. The purpose of this study was to determine the most prominent impacts identified by acne patients and by clinicians. METHODS: Independent Delphi surveys for acne patients and clinicians were conducted to achieve consensus regarding acne impacts within each group. Acne patients were recruited from outpatient clinics of authors (AL, JT, and DT). The first phase involved qualitative responses, where emergent themes were identified and used to generate items for 2 subsequent phases. RESULTS: The qualitative phase generated 64 items in 3 themes: psychological, sociological, and treatment related. These items were independently ranked in importance by patients and by clinicians. Consensus for importance was achieved for 34 items by patients and 43 by clinicians. Patient-identified highest ranked items were being self-conscious, feeling unattractive, feeling uncomfortable in own skin, unattractive to others, would not want pictures taken, envious of people with clear skin, and time/effort spent concealing scarring; while clinicians identified feeling unattractive. CONCLUSIONS: We identify acne impacts within psychological, sociological, and treatment-related domains by acne patients and clinicians. Further,
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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 | 0.032 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".