Validity of a Computerized Cognitive Battery in Children and Adolescents with Neurological Diagnoses
Bibliographic record
Abstract
OBJECTIVE: Little is known about the validity of computerized cognitive batteries, such as CNS Vital Signs (CNSVS), in pediatric patients. The purpose of this study was to examine convergent and divergent validity of the CNSVS in a clinical pediatric sample with neurological diagnoses. METHOD: Participants included 123 pediatric patients assessed in a tertiary care setting as part of clinical care. CNSVS (Memory, Psychomotor Speed, Reaction Time, Complex Attention, and Cognitive Flexibility domains, and a Neurocognition Index) and paper-and-pencil neuropsychological measures assessing learning, memory, processing speed, reaction time, attention, and executive functioning were administered. RESULTS: Most correlations between CNSVS domain scores and neuropsychological measures assessing similar constructs were medium in strength. With the exception of stronger correlations between psychomotor speed tests, correlations between tests of similar constructs were not significantly higher than those between dissimilar constructs. CONCLUSIONS: These results provide support for validity of the CNSVS battery, but also caution that many abilities are inter-correlated.
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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 | 0.004 | 0.023 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".