Using Multivariate Base Rates to Interpret Low Scores on an Abbreviated Battery of the Delis–Kaplan Executive Function System
Bibliographic record
Abstract
OBJECTIVE: Executive function consists of multiple cognitive processes that operate as an interactive system to produce volitional goal-oriented behavior, governed in large part by frontal microstructural and physiological networks. Identification of deficits in executive function in those with neurological or psychiatric conditions can be difficult because the normal variation in executive function test scores, in healthy adults when multiple tests are used, is largely unknown. This study addresses that gap in the literature by examining the prevalence of low scores on a brief battery of executive function tests. METHOD: The sample consisted of 1,050 healthy individuals (ages 16-89) from the standardization sample for the Delis-Kaplan Executive Function System (D-KEFS). Seven individual test scores from the Trail Making Test, Color-Word Interference Test, and Verbal Fluency Test were analyzed. RESULTS: Low test scores, as defined by commonly used clinical cut-offs (i.e., ≤25th, 16th, 9th, 5th, and 2nd percentiles), occurred commonly among the adult portion of the D-KEFS normative sample (e.g., 62.8% of the sample had one or more scores ≤16th percentile, 36.1% had one or more scores ≤5th percentile), and the prevalence of low scores increased with lower intelligence and fewer years of education. CONCLUSIONS: The multivariate base rates (BR) in this article allow clinicians to understand the normal frequency of low scores in the general population. By use of these BRs, clinicians and researchers can improve the accuracy with which they identify executive dysfunction in clinical groups, such as those with traumatic brain injury or neurodegenerative diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".