Subtypes of Psychopathology in Children Referred for Neuropsychological Assessment
Bibliographic record
Abstract
The validity of a Personality Inventory for Children-Revised edition (PIC-R) typology was examined in a sample of 323 children aged 6-16 years. These children had been referred to a children's mental health centre for neuropsychological assessment. In study 1, K-means cluster analysis (k = 12) was applied to the PIC clinical scales in an attempt to replicate the 12 clusters identified by Gdowski, Lachar, and Kline (1985). Partial cluster replication was achieved. Examination of the obtained clusters revealed significant overlap, suggesting that fewer clusters would represent an optimal solution. In study 2, a two-stage cluster analysis yielded a seven-cluster solution consistent with several key forms of psychopathology previously reported in the literature using specific neuropsychological populations. Identified subtypes included profiles characterized as: normal, cognitive deficit, cognitive deficit with internalized psychopathology, cognitive deficit with social impairment, cognitive deficit with hyperactivity, cognitive deficit with both internalized and externalized psychopathology, and combined internalized and externalized psychopathology without a cognitive deficit component.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".