Examining the criterion-related validity of the Pervasive Developmental Disorder Behavior Inventory
Bibliographic record
Abstract
The Pervasive Developmental Disorder Behavior Inventory is a questionnaire designed to aid in the diagnosis of pervasive developmental disorders or autism spectrum disorders. The Pervasive Developmental Disorder Behavior Inventory assesses adaptive and maladaptive behaviors associated with pervasive developmental disorders and provides an age-standardized Autism Composite score. In previous research, the Pervasive Developmental Disorder Behavior Inventory has demonstrated moderate to strong reliability and validity. This study aimed to replicate and extend previous research by investigating the criterion-related validity of the Pervasive Developmental Disorder Behavior Inventory. Data from 40 children were analyzed in relation to other measures. The Pervasive Developmental Disorder Behavior Inventory adaptive scores were moderately correlated with cognitive and adaptive behavior scores as expected. However, no significant correlations were found between the maladaptive and Autism Composite scores of the Pervasive Developmental Disorder Behavior Inventory and the Childhood Autism Rating Scale. Results lead to concerns regarding the validity of some scores of the Pervasive Developmental Disorder Behavior Inventory.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".