Psychometric evaluation of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID).
Bibliographic record
Abstract
The goals of the study were to examine test-retest reliability, informant agreement and convergent and discriminant validity of nine DSM-IV-TR psychiatric disorders classified by parent and youth versions of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID). Using samples drawn from the general population and child mental health outpatient clinics, 283 youth aged 9 to 18 years and their parents separately completed the MINI-KID with trained lay interviewers on two occasions 7 to 14 days apart. Test-retest reliability estimates based on kappa (κ) went from 0.33 to 0.79 across disorders, samples and informants. Parent-youth agreement on disorders was low (average κ = 0.20). Confirmatory factor analysis provided evidence supporting convergent and discriminant validity. The MINI-KID disorder classifications yielded estimates of test-retest reliability and validity comparable to other standardized diagnostic interviews in both general population and clinic samples. These findings, in addition to the brevity and low administration cost, make the MINI-KID a good candidate for use in epidemiological research and clinical practice. (PsycINFO Database Record
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".