Perceptions on the Psychological Impact of Facial Erythema Associated with Rosacea: Results of International Survey
Bibliographic record
Abstract
INTRODUCTION: Rosacea (including facial erythema) has a negative impact on psychological and emotional health. This survey aimed to assess the impact of facial erythema on subconscious perceptions and the initial reactions of others and how this affects attitudes in different settings. The survey also measured the impact of facial erythema on a person's emotional and psychological wellbeing. METHODS: A total of 6831 participants from eight countries completed online computer-assisted web interviewing psychological assessments based on the implicit association test. Traditional questionnaires provided data on the impact of facial erythema and perceptions of people with rosacea from other participants. RESULTS: Facial erythema was strongly associated with poor health and negative personality traits with participants reporting negative impacts of rosacea emotionally, socially and in the workplace. Nearly 80% reported difficulty in controlling facial erythema but those with physician-diagnosed rosacea had significantly improved control versus those with undiagnosed rosacea (39% vs 20%, p < 0.05). CONCLUSIONS: People with facial erythema have to manage their own psychological barriers to cope with the disease and deal with the prejudice and negative first impressions of others. Formal diagnosis, advice and treatment from a healthcare professional improve rosacea control. FUNDING: Galderma.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".