New Child and Adolescent Memory Profile Embedded Performance Validity Test
Bibliographic record
Abstract
OBJECTIVE: It is essential to interpret performance validity tests (PVTs) that are well-established and have strong psychometrics. This study evaluated the Child and Adolescent Memory Profile (ChAMP) Validity Indicator (VI) using a pediatric sample with traumatic brain injury (TBI). METHOD: A cross-sectional sample of N = 110 youth (mean age = 15.1 years, standard deviation [SD] = 2.4 range = 8-18) on average 32.7 weeks (SD = 40.9) post TBI (71.8% mild/concussion; 3.6% complicated mild; 24.6% moderate-to-severe) were administered the ChAMP and two stand-alone PVTs. Criterion for valid performance was scores above cutoffs on both PVTs; criterion for invalid performance was scores below cutoffs on both PVTs. Classification statistics were used to evaluate the existing ChAMP VI and establish a new VI cutoff score if needed. RESULTS: There were no significant differences in demographics or time since injury between those deemed valid (n = 96) or invalid (n = 14), but all ChAMP scores were significantly lower in those deemed invalid. The original ChAMP VI cutoff score was highly specific (no false positives) but also highly insensitive (sensitivity [SN] = .07, specificity [SP] = 1.0). Based on area under the curve (AUC) analysis (0.94), a new cutoff score was established using the sum of scaled scores (VI-SS). A ChAMP VI-SS score of 32 or lower achieved strong SN (86%) and SP (92%). Using a 15% base rate, positive predictive value was 64% and negative predictive value was 97%. CONCLUSIONS: The originally proposed ChAMP VI has insufficient SN in pediatric TBI. However, this study yields a promising new ChAMP VI-SS, with classification metrics that exceed any other current embedded PVT in pediatrics.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".