Atopic Dermatitis and Emotional and Behavioral Outcomes in Urban U.S. Children: A Birth Cohort Study
Bibliographic record
Abstract
Abstract: Background: Numerous studies suggest that childhood atopic dermatitis (AD) is associated with problems with internalizing behaviors. However, results for other behavioral domains, such as externalizing behaviors, attention problems, and social competence, have been mixed. Objective: To determine whether AD is associated with emotional/behavioral problems in a racially and ethnically diverse urban birth cohort of children of mostly unwed mothers. Methods: A total of 4898 mothers were recruited in maternity wards and followed longitudinally, completing questionnaires on AD and behavior at ages 5, 9, and 15. Logistic regression models compared the odds of emotional/behavioral problems in children with and without AD. Results: Adjusted analyses indicated children with AD were more likely to have internalizing (adjusted odds ratio [aOR] = 1.42; 95% confidence interval [CI]: 1.11–1.82) and externalizing (aOR = 1.48; 95% CI: 1.16–1.89) emotional/behavioral problems. Conclusions: Our findings underscore the importance of clinicians treating children with AD to specifically ask about emotional and behavioral problems, both at baseline and follow-up visits during AD treatment. This is crucial for early identification of behavioral problems and for monitoring responses to treatment. These assessments are also clinically significant in determining whether behavioral issues during AD treatment are preexisting or newly developed and avoiding AD treatments being incorrectly blamed for behavioral problems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".