Speed and memory in WAIS–R–NI Digit Symbol performance among healthy older adults
Bibliographic record
Abstract
Although roles have been proposed for both graphomotor speed and learning in the execution of Digit Symbol, few data have been available concerning performance across the adult lifespan on the Symbol Copy, paired associates, or free recall measures derived from Digit Symbol and recommended in the WAIS-R-NI. We report findings on 177 healthy older adults (ages 50-90), providing normative data by age group, education level, and gender. As previously reported, Digit Symbol scores decline steeply with age (r = -.64). Symbol Copy speed declines almost as steeply (r = -.58). Incidental learning, however, declines only modestly (r = -.26 on both measures). Symbol Copy is a far stronger correlate of Digit Symbol (r = .72) than are paired associates or free recall (r = .26 and r = .28, respectively). The 2 incidental learning measures do, however, offer valuable supplementary information as part of a comprehensive individual assessment. When low Digit Symbol scores are produced by slowing on Symbol Copy, further evaluation of perceptual and motor speed and dexterity are indicated. When low incidental learning scores are obtained, further evaluation of memory is warranted. Qualitative analysis of errors (e.g., rotations) made on the incidental learning procedures may also be valuable.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".