Heterogeneity of Irritability: Psychometrics of The Irritability and Dysregulation of Emotion Scale (TIDES-13)
Bibliographic record
Abstract
ABSTRACT Objective We designed The Irritability and Dysregulation of Emotion Scale (TIDES-13) to test whether irritability consisted of several sub-dimensions that would correlate differentially with internalizing/externalizing psychopathology, age, and gender. Method Parent-report (n = 3935, mean age = 8.9) and youth self-report (n = 579, mean age = 15.1) versions of TIDES-13 were administered to a population-based sample. Exploratory and confirmatory factor analyses were conducted on separate sub-samples. We fit multivariable regression models between TIDES-13 sub-dimensions and age, gender, anxiety, depression, ODD and ADHD trait levels. Results A higher order model with a global irritability dimension and Proneness to Anger, Internalized Negative Emotional Reactivity, Externalized Negative Emotional Reactivity and Reactive Aggression sub-dimensions showed good to excellent fit in both parent-report and self-report. The global irritability dimension had a strong influence on all item variance (ω Hierarchical; parent report = .0.94, ω Hierarchical; self report = .90). Proneness to Anger, Externalized Negative Emotional Reactivity and Reactive Aggression decreased with age in males, whereas Internal Negative Emotional Reactivity increased with age in females. Internalized Negative Emotional Reactivity was associated with internalizing traits, over and above global irritability. ODD and ADHD were predicted primarily by the global irritability. Conclusion Although irritability can be estimated as an essentially unidimensional construct, differential associations of Internalized Negative Emotional Reactivity with gender and age, and internalizing psychopathology warrant examination in clinical populations. These results support TIDES-13 as a reliable and valid multidimensional measure of irritability and thus may be useful for research and clinical purposes.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".