Observational measures of early irritability predict children's psychopathology risk
Bibliographic record
Abstract
Irritability is a transdiagnostic feature of diverse forms of psychopathology and a rapidly growing literature implicates the construct in child maladaptation. However, most irritability measures currently used are drawn from parent-report questionnaires not designed to measure irritability per se; furthermore, parent report methods have several important limitations. We therefore examined the utility of observational ratings of children's irritability in predicting later psychopathology symptoms. Four-hundred and nine 3-year-old children (208 girls) completed observational tasks tapping temperamental emotionality and parents completed questionnaires assessing child irritability and anger. Parent-reported child psychopathology symptoms were assessed concurrently to the irritability assessment and when children were 5 and 8 years old. Children's irritability observed during tasks that did not typically elicit anger predicted their later depressive and hyperactivity symptoms, above and beyond parent-reported irritability and context-appropriate observed anger. Our findings support the use of observational indices of irritability and have implications for the development of observational paradigms designed to assess this construct in childhood.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".