Potential for misclassification of mild cognitive impairment: A study of memory scores on the Wechsler Memory Scale-III in healthy older adults
Bibliographic record
Abstract
The psychometric criterion of mild cognitive impairment (MCI) generally involves having an unusually low score on memory testing (i.e., -1.5 SDs). However, healthy older adults can obtain low scores, particularly when multiple memory measures are administered. In turn, there is a substantial risk of psychometrically misclassifying MCI in healthy older adults. This study examined the base rates of low memory scores in older adults (55-87 years; n = 550) from the Wechsler Memory Scale-Third Edition (WMS-III; Wechsler, 1997b) standardization sample. The WMS-III consists of four co-normed episodic memory tests (i.e., Logical Memory, Faces, Verbal Paired Associates, and Family Pictures) that yield eight age- and demographically-adjusted standard scores (Auditory Recognition and Working Memory tests not included). When the eight age-adjusted scores were examined simultaneously, 26% of older adults had one or more scores at or below the 5th percentile (i.e., -1.5 SDs). On the eight demographically- adjusted scores, 39% had at least one score at or below the 5th percentile. There was an inverse relationship between intellectual abilities and prevalence of low memory scores, particularly with the age-adjusted WMS-III scores. Understanding the base rates of low scores can reduce the overinterpretation of low memory scores and minimize false-positive misclassification.
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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 | 0.020 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".