Quality of life, alexithymia, anxiety and depression symptoms among mothers of children with atopic dermatitis
Bibliographic record
Abstract
Objective: The mothers of children diagnosed with atopic dermatitis (AD) may be impacted in many different ways. Aim of the present study was to compare quality of life, anxiety, depression, and alexithymia symptoms between mothers of children diagnosed with AD and mothers of healthy children. Method: The study included 34 mothers of children who were diagnosed with AD between June 2012 and July 2013 and 35 mothers of healthy children. In the study, Short Form 36 (SF-36) Health Survey was used to evaluate quality of life, while the Toronto Alexithymia Scale (TAS) was used to evaluate alexithymia level, the State-Trait Anxiety Inventory (STAI) was used to evaluate anxiety symptoms, and the Beck Depression Scale (BDS) was used to evaluate depression symptoms. Results: There was no statistically significant difference between the mothers of AD patients and control subjects in terms of quality of life, anxiety, depression, and alexithymia. In addition, there was no significant difference in disease severity or symptoms scale scores between the two groups. Conclusion: These results may suggest that mothers’ mental health is not affected in the early stage of the disease. In later stages of the disease, mothers of children with AD may become psychologically affected. Long-term follow up studies are required to clarify this distinction.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".