Development and psychometric validation of the interRAI ChYMH externalizing subscale
Bibliographic record
Abstract
The interRAI Child and Youth Mental Health (ChYMH) is a standardized assessment instrument utilized in over 60 mental health agencies that promotes seamless transition across public healthcare sectors. The purpose of this study was to develop and assess the reliability and validity of the externalizing subscale on the interRAI Child and Youth Mental Health (ChYMH). Part one invited a panel of experts (i.e. doctoral-level clinical psychologists) to assess content validity of the items relevant to externalizing behaviors. Items that experts deemed representative of externalizing symptoms underwent unrestricted factor analyses in a sample of children/youths 4 to 18 years of age ( N = 3,464) collected across 39 mental health agencies. The final externalizing subscale showed strong content representativeness, high internal consistency, and good structural validity for a two-dimensional model of reactive and proactive externalizing behavior. In part two, Bayesian correlations demonstrated that the interRAI ChYMH externalizing subscale showed strong associations with externalizing subscales, anger, and disruptive behavior measures from various assessment instruments (i.e. Beck Youth Inventories, Social Skills Improvement System, Child and Adolescent Functional Assessment Scale, Child Behavior Checklist, Brief Child and Family Phone Interview). Overall, the externalizing subscale demonstrated strong measurement properties for the assessment of behavioral disturbances.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".