A Digital Self-help Intervention for Atopic Dermatitis: Analysis of Secondary Outcomes From a Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) is a common inflammatory skin disease characterized by dry skin, eczematous lesions, and an often severe pruritus. The disease may have a negative effect on quality of life and is also associated with symptoms of anxiety and depression. Few individuals with AD receive any form of behavioral intervention. Behavioral interventions for AD are potentially efficacious but need to be constructed so that they are safe, credible, and user-friendly. We have previously reported on a feasibility study that demonstrated that a self-management version of a digital intervention based on cognitive behavioral therapy (CBT) for AD can potentially be effective in reducing AD symptoms. The aim of this secondary report was to further examine treatment feasibility and preliminary effects on dermatological quality of life, itching sensations, depressive symptoms, and perceived stress. OBJECTIVE: This is a secondary report on intervention credibility, usability, adverse events, and preliminary effects on secondary measures of a self-management digital intervention for atopic dermatitis. METHODS: In total, 21 adults with AD, recruited nationwide in Sweden, were assessed by telephone, and used the digital intervention for 8 weeks. Participants were also assessed directly afterward and 3 months after the end of the intervention. There was no therapist guidance. Feasibility indicators included intervention credibility, usability, and possible adverse effects. Other measures included preliminary effects on dermatological quality of life, itching sensations, depressive symptoms, and perceived stress. RESULTS: The intervention was regarded as credible and no serious adverse events were reported. System usability was, however, found to be below the predetermined cutoff for acceptable usability. Preliminary effects at 3-month follow-up were in the moderate to large range for dermatological quality of life (Cohen d=0.89, 95% CI 0.18-1.56), itching sensations (Cohen d=0.85, 95% CI 0.15-1.52), depressive symptoms (Cohen d=0.78, 95% CI 0.1-1.45), and perceived stress (Cohen d=0.75, 95% CI 0.01-1.36). CONCLUSIONS: This 8-week self-management digital CBT-based intervention was, together with telephone calls before and after, a feasible intervention for participants with AD. Preliminary effects were promising and should be explored further in a randomized controlled trial. Intervention usability was, however, rated below cutoff scores. Efforts should be made to improve written material to increase usability.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".