Classifying child and adolescent psychiatric disorder by problem checklists and standardized interviews
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper discusses the need for research on the psychometric adequacy of self-completed problem checklists to classify child and adolescent psychiatric disorder based on proxy assessments by parents and self-assessments by adolescents. We put forward six theoretical arguments for expecting checklists to achieve comparable levels of reliability and validity with standardized diagnostic interviews for identifying child psychiatric disorder in epidemiological studies and clinical research. Empirically, the modest levels of test-retest reliability exhibited by standardized diagnostic interviews - 0.40 to 0.60 based on kappa - should be achievable by checklists when thresholds or cut-points are applied to scale scores to identify a child with disorder. The few studies to conduct head-to-head comparisons of checklists and interviews in the 1990s concurred that no construct validity differences existed between checklist and interview classifications of disorder, even though the classifications of youth with psychiatric disorder only partially overlapped across instruments. Demonstrating that self-completed problem checklists can classify disorder with similar reliability and validity as standardized diagnostic interviews would provide a simple, brief, flexible way to measuring psychiatric disorder as both a categorical or dimensional phenomenon as well as dramatically lowering the burden and cost of assessments in epidemiological studies and clinical research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it