A-236 Concurrent Validity of the Paper-Match in a Diverse Population
Bibliographic record
Abstract
Abstract Introduction Symbol and digit substitution tasks are key instruments in the evaluation of attention, speed of processing, executive functioning, and cognitive dysfunction. The Match is an electronic (app-based) substitution task developed as part of the University of California San Francisco Brain Health Assessment that has been used to demonstrate cognitive impairment. We describe the paper-based oral symbol/number substitution task (Paper-Match), which was developed as part of the 5-Cog battery to assess for cognitive impairment including dementia and demonstrate it’s use in an urban, multi-ethnic, socioeconomically disadvantaged primary care population in Bronx NY. Method 109 participants, mean age 72.61 SD 6.42 and education 11.70 SD 3.82 years, 81% female, 48.6% Hispanic/Latino and 47.7% African American seen as part of 5-Cog. Participants (36.7% tested in Spanish) completed the Paper-Match (scored based on the number of correct matches in 90 seconds) and a comprehensive neuropsychological battery. Descriptive and correlational analysis were conducted. Results Mean Paper-Match score was 38.24 SD 11.83 items correct (range 4–51). Paper-Match performance was highly correlated with performance on the Symbol Digit Modalities Test (r = .819, p < .001) and moderately correlated with performance on the Montreal Cognitive Assessment (MOCA; r = .604, p < .001). Years of education and primary language impacted performances. Conclusion The results of this study provide the initial description and validation of the Paper-Match an oral symbol digit substitution task and its use in a diverse population of older primary care patients. Further research on the psychometric properties and construct validity of the Paper-Match are needed.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 0.002 |
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".