Problem checklists and standardized diagnostic interviews: evidence of psychometric equivalence for classifying psychiatric disorder among children and youth in epidemiological studies
Bibliographic record
Abstract
BACKGROUND: The standard approach for classifying child/youth psychiatric disorder as present or absent in epidemiological studies is lay-administered structured, standardized diagnostic interviews (interviews) based on categorical taxonomies such as the DSM and ICD. Converting problem checklist scale scores (checklists) to binary classifications provides a simple, inexpensive alternative. METHODS: Using assessments obtained from 737 parents, we determine if child/youth behavioral, attentional, and emotional disorder classifications based on checklists are equivalent psychometrically to interview classifications. We test this hypothesis by (1) comparing their test-retest reliabilities based on kappa (κ), (2) estimating their observed agreement at times 1 and 2, and (3) in structural equation models, comparing their strength of association with clinical status and reported use of prescription medication to treat disorder. A confidence interval approach is used to determine if parameter differences lie within the smallest effect size of interest set at ±0.125. RESULTS: The test-retest reliabilities (κ) for interviews compared with checklists met criteria for statistical equivalence: behavioral, .67 and .70; attentional, .64 and .66; and emotional, .61 and .65. Observed agreement between the checklist and interviews on classifications of disorder at times 1 and 2 was, on average, κ = .61. On average, the β coefficients estimating associations with clinical status were .59 (interviews) and .63 (checklists); and with prescription medication use, .69 (interviews) and .71 (checklists). Behavioral and attentional disorders met criteria for statistical equivalence. Emotional disorder did not, although the coefficients were stronger numerically for the checklist. CONCLUSIONS: Classifications of child/youth psychiatric disorder from parent-reported checklists and interviews are equivalent psychometrically. The practical advantages of checklists over interviews for classifying disorder (lower administration cost and respondent burden) are enhanced by their ability to measure disorder dimensionally. Checklists provide an option to interviews in epidemiological studies of common child/youth psychiatric disorders.
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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 | 0.138 | 0.297 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".