Development and evaluation of a self-administered on-line test of memory and attention for middle-aged and older adults
Bibliographic record
Abstract
There is a need for rapid and reliable Internet-based screening tools for cognitive assessment in middle-aged and older adults. We report the psychometric properties of an on-line tool designed to screen for cognitive deficits that require further investigation. The tool is composed of measures of memory and executive attention processes known to be sensitive to brain changes associated with aging and with cognitive disorders that become more prevalent with age. Measures included a Spatial Working Memory task, Stroop Interference task, Face-Name Association task, and Number-Letter Alternation task. Normative data were collected from 361 healthy adults age 50-79 who scored in the normal range on a standardized measure of general cognitive ability. Participants took the 20-minute on-line test on their home computers, and a subset of 288 participants repeated the test 1 week later. Analyses of the individual tasks indicated adequate internal consistency, construct validity, test-retest reliability, and alternate version reliability. As expected, scores were correlated with age. The four tasks loaded on the same principle component. Demographically-corrected z-scores from the individual tasks were combined to create an overall score, which showed good reliability and classification consistency. These results indicate the tool may be useful for identifying middle-aged and older adults with lower than expected scores who may benefit from clinical evaluation of their cognition by a health care professional.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".