Brief memory assessment in children: can the ChAMP Screening Index detect memory impairment?
Bibliographic record
Abstract
Abbreviated memory batteries play a role in some clinical and research assessments, but their validity and accuracy need to be well supported. The purpose of this study was to examine the accuracy of the ChAMP Screening Index for detecting memory impairment. The sample included N = 804 youths (ages 5–21 years) with medical and neurological diagnoses who were presented for a clinical neuropsychological assessment. All completed the full Child and Adolescent Memory Profile and had valid data. The ChAMP Screening Index contains the first two subtests of the battery (Lists and Objects) and takes about 10 min to administer (full ChAMP is about 35 min). Analyses to examine the accuracy of the ChAMP Screening Index with both the Total Memory Index and Delayed Memory Index included Intraclass correlations, Cohen’s Kappa coefficients, receiver operating characteristics, and classification metrics (e.g., sensitivity, specificity, positive predictive values [PPV], and negative predictive values [NPV]). Very strong correlations, minimal mean difference scores, substantial agreement on kappa coefficients, and outstanding receiver operating characteristics all support the Screening Index accuracy. A cutoff score on the Screening Index of 70 provides a good balance between a high PPV (.91) and a high NPV (.96) for the Total Memory Index. When detecting impairment on the Delayed Memory Index, a Screening Index cutoff score of 65 provides a balance between a high PPV (.92) and a high NPV (.94). This study supports the accuracy, validity, and utility of the 10-min ChAMP Screening Index in those clinical and research situations where a brief evaluation of memory is desired.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".