A Mobile App to Enhance Awareness of Vaccination in Adults With Psoriasis and Atopic Dermatitis: Development and Preliminary Evaluation Study
Bibliographic record
Abstract
BACKGROUND: Patients with psoriasis and atopic dermatitis are at increased risk of several vaccine-preventable diseases. Despite this increased susceptibility to infections, vaccination uptake in adults with psoriasis and atopic dermatitis, especially if treated with biologics and other systemic immunomodulators, is insufficient. As mobile health technologies may support behavior change, a mobile app called DermatoVax was developed to raise awareness of immunization in adult patients with psoriasis and atopic dermatitis. OBJECTIVE: This paper aims to describe the processes of development of the DermatoVax app and its initial evaluation in terms of technical verification and physicians' quality rating. METHODS: The app was conceived in a user-centered fashion. Its core component was the vaccine checker, which allows the app to produce a sharable list of recommended vaccines, immunization timings, and eventual precautions from a short set of input data. App prototypes were extensively piloted, and feedback from potential end users was obtained to refine the app content. The readability of the textual narratives was measured using the Italian-specific Gulpease index, which ranges from 0 to 100, where 100 indicates the best readability. The quality of the final version was evaluated by 46 medical doctors (n=29, 63% dermatologists and n=17, 37% public health physicians) using a validated Italian user version of the Mobile App Rating Scale (uMARS). RESULTS: Iterative steps during the app development process allowed us to increase its user-friendliness and comprehensibility. Proper functioning of the checker was confirmed through the correct and complete generation of recommended vaccine lists for 50 mock patients with psoriasis and atopic dermatitis. An overall Gulpease index of 41.0 was observed for the final textual narratives, suggesting acceptable readability properties for patients with a high school diploma. Of a maximum of 5 points, the average uMARS score was 4.22 (SD 0.49). Ratings provided by dermatologists (mean 4.28, SD 0.48) were similar (P=.33) to those provided by public health physicians (mean 4.12, SD 0.51). However, the mean uMARS scores for the quality dimensions of aesthetics (3.88, SD 0.78) and engagement (3.89, SD 0.68) were lower than those for information (4.64, SD 0.42) and functionality (4.47, SD 0.46), suggesting margins for improvement. The app's perceived impact was notably high, with over 80% of physicians agreeing that its use would significantly improve patient awareness (39/46, 85%) and knowledge (41/46, 89%) of vaccination, leading to increased vaccination uptake (37/46, 80%). CONCLUSIONS: DermatoVax is a promising tool to raise awareness of immunization in adult patients with psoriasis and atopic dermatitis. Further assessment of the app, such as its effectiveness in increasing vaccination uptake, is warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".