328 Understanding the impact of atopic dermatitis on patients: a large international, ethnically diverse survey-based qualitative study
Bibliographic record
Abstract
Abstract Atopic dermatitis (AD) is a common, chronic inflammatory skin disease often associated with a significant long-term disease burden. AD can profoundly impact a patient’s physical and mental health. Current AD management recommendations do not capture patient perspectives on their treatment needs, expectations and drivers of decision-making. Qualitative patient research is needed to support the creation of patient-centric recommendations for AD assessment and management. To study a large, international, ethnically diverse population of patients with AD that will enable the creation of patient-centric recommendations for AD management. Adult patients (≥18 years old) receiving treatment for AD were recruited from patient market research databases, clinician referrals, and local advertising. All patients were screened via a questionnaire to ensure a balanced and diverse range of ages, gender, educational levels, geographic locations, and AD severities, and to confirm that they were currently receiving treatment for AD. Patients participated in a 45-minute, 1 : 1 telephone interview conducted in their native language by the research team. These interviews explored the impact of AD on patients’ lives, patients’ most troublesome symptoms, how patients make treatment decisions and patients’ treatment expectations. Patients were also questioned on their current knowledge of AD scoring systems and what they thought was most important to include in AD scoring systems. A large ethnically diverse global patient population (N = 88; 15 countries) was included in the study. AD was reported to have a substantial, broad impact on patients’ lives, with patients being affected by AD at all times of the day and night. Itch, skin redness, dry/flaky skin and sleep disturbance were the most frequently reported signs and symptoms, with over 75% of patients experiencing them every 1–3 days. The itch was cited by 37% of patients as being the primary reason for changing AD treatments. In addition, the research revealed that mental health issues such as anxiety and depression are common in patients suffering from AD, and these features have the greatest negative impact on patients’ daily lives. Patients reported that AD impairs their quality of life, with many perceiving that clinicians underestimate this burden; this was reported more often for non-specialists compared with dermatologists. Patients also felt they were often not given enough time to express themselves in medical appointments and reported an inability to optimally communicate with their clinicians. Patients had little awareness of AD severity scoring systems, with almost no survey respondents reporting their use during previous healthcare encounters. When questioned about their preferences for different AD scoring systems, patients favoured using a combination of patient-reported outcomes to reflect disease burden and clinician-reported outcomes to ensure consistency across different physicians and patient populations. These preferences indicate that an optimal scoring system would consider a diverse range of symptoms, and the variable nature of AD, and be accessible regardless of education level. No single AD scoring system was preferred by all patients. Patients indicated that they would like AD scoring systems to be incorporated into clinical practice, to help them communicate their AD burden to clinicians, and to provide a clear framework for monitoring treatment response. This global patient study generated insights into the burden of AD on patients’ lives, their expectations of treatment, and their views on AD scoring methods. Results provided an evidence base for the development of patient-centric recommendations for AD management.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".