Investigation of attention deficit and hyperactivity disorder in adult patients with atopic dermatitis
Bibliographic record
Abstract
Background. Atopic dermatitis (AD) is a common chronic inflammatory disease that is associated with significant psychosocial morbidity and a decrease in health-related quality of life. Attention deficit hyperactivity disorder may be present in atopic dermatitis patients. Objective. The present study aims to investigate the co-presence of ADHD in adult patients with AD. Material and method. The study registered 60 adult patients with AD (48 females and 12 males) and 50 non-atopic control subjects (38 females and 12 males). The AD patient group and the control group were assessed using the Turgay adult Attention-Deficit/Hyperactivity Disorder (ADD/ADHD) DSM-IV-Based Diagnostic Screening and Rating Scale (Turkish Version), which was studied by a team of psychologists and psychiatrists in Turkey for validity, reliability and norms. The scale covers three dimensions of the disease, namely inattention, hyperactivity and impulsivity, and associated features of ADHD. The groups were compared and contrasted in terms of their similarities and differences in ADD/ADHD symptoms. Results. Three sub-dimensions of ADD/ADHD scale (Attention Deficit, Hyperactivity/ Impulsivity and Problem subdivisions) in AD patients were found statistically significantly elevated relative to controls (P<0.001, P<0.001, P<0.001, respectively). Conclusions. In conclusion we established the co-presence of ADHD in AD patients in the adult age group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".