The Number Symbol Coding Task: A brief measure of executive function to detect dementia and cognitive impairment
Bibliographic record
Abstract
INTRODUCTION: Alzheimer's disease and related dementias (ADRD) affect over 5.7 million Americans and over 35 million people worldwide. Detection of mild cognitive impairment (MCI) and early ADRD is a challenge to clinicians and researchers. Brief assessment tools frequently emphasize memory impairment, however executive dysfunction may be one of the earliest signs of impairment. To address the need for a brief, easy-to-score, open-access test of executive function for use in clinical practice and research, we created the Number Symbol Coding Task (NSCT). METHODS: This study analyzed 320 consecutive patient-caregiver dyads who underwent a comprehensive evaluation including the Clinical Dementia Rating (CDR), patient and caregiver versions of the Quick Dementia Rating System (QDRS), caregiver ratings of behavior and function, and neuropsychological testing, with a subset undergoing volumetric magnetic resonance imaging (MRI). Estimates of cognitive reserve were calculated using education, combined indices of education and occupation, and verbal IQ. Psychometric properties of the NSCT including data quality, data distribution, floor and ceiling effects, construct and known-groups validity, discriminability, and clinical profiles were determined. RESULTS: The patients had a mean age of 75.3±9.2 years (range 38-98y) with a mean education of 15.7±2.8 years (range 6-26y) of education. The patients had a mean CDR-SB of 4.8±4.7 (range 0-18) and a mean MoCA score of 18.6±7.1 (range 1-30). The mean NSCT score was 30.1±13.8 and followed a normal distribution. All healthy controls and MCI cases were able to complete the NSCT. The NSCT showed moderate-to-strong correlations with clinical and neuropsychological measures with the strongest association (all p's < .001) for measures with executive components (e.g., Judgement and Problem Solving box of the CDR, Decision Making and Problem Solving domain of the QDRS, Trailmaking B, and Cognigram Attention and Executive Composite Scores). Women slightly outperformed men, and individuals with lower educational attainment and lower education-occupation indices had lower NSCT scores. Decreasing NSCT scores corresponded to older age, worse cognitive scores, higher CDR sum of boxes scores, worse caregiver ratings of function and behavior, worse patient and informant QDRS ratings, and smaller hippocampal volumes and hippocampal occupancy scores. The NSCT provided excellent discrimination (AUC: .866; 95% CI: .82-.91) with a cut-off score of 36 providing the best combination of sensitivity (0.880) and specificity (0.759). Combining the NSCT with patient QDRS and caregiver QDRS ratings improved discrimination (AUC: .908; 95% CI: .87-.94). DISCUSSION: The NSCT is a brief, 90-second executive task that incorporates attention, planning and set-switching that can be completed by individuals into the moderate-to-severe stages of dementia. The NSCT may be a useful tool for dementia screening, case-ascertainment in epidemiological or community-based ADRD studies, and in busy primary care settings where time is limited. Combining the NSCT with a brief structured interview tool such as the QDRS may provide excellent power to detect cognitive impairment. The NSCT performed well in comparison to standardized scales of a comprehensive cognitive neurology evaluation across a wide array of sociodemographic variables in a brief fashion that could facilitate its use in clinical care and research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".