The 25-Item Ontario Child Health Study Emotional Behavioural Scales-Brief Version (OCHS-EBS-B): Test-Retest Reliability and Construct Validity When Used as Categorical Measures
Bibliographic record
Abstract
OBJECTIVE: Child and youth mental health problems are often assessed by parent self-completed checklists that produce dimensional scale scores. When converted to binary ratings of disorder, little is known about their psychometric properties in relation to classifications based on lay-administered structured diagnostic interviews. In addition to estimating agreement, our objective is to test for statistical equivalence in the test-retest reliability and construct validity of two instruments used to classify child emotional, behavioural, and attentional disorders: the 25-item, parent completed Ontario Child Health Study Emotional Behavioural Scales-Brief Version (OCHS-EBS-B) and the Mini International Neuropsychiatric Interview for Children and Adolescents-parent version (MINI-KID-P). METHODS: = 452) and uses the confidence interval approach to test for statistical equivalence. Reliability is based on kappa (κ). Construct validity is based on standardized beta coefficients (β) estimated in structural equation models. RESULTS: The average differences between the MINI-KID-P and OCHS-EBS-B in κ and β were -0.022 and -0.020, respectively. However, in both instances, criteria for statistical equivalence were met in only 5 of 12 comparisons. Based on κ, between-instrument agreement on the classifications of disorder went from 0.481 (attentional disorder) to 0.721 (emotional disorder) but were substantially higher (0.731 to 0.895, respectively) when corrected for attenuation due to measurement error. CONCLUSIONS: Although falling short of equivalence, the results suggest on balance that the reliability and validity of the two instruments for classifying child psychiatric disorder assessed by parents are highly comparable. This conclusion is supported by the high levels of agreement between the instruments after correcting for attenuation due to measurement error.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".