The construct validity of a new screening measure of functional cognitive ability: The menu task
Bibliographic record
Abstract
This study evaluated the construct validity of the Menu Task (MT): a new performance-based screening measure of functional cognition. We enrolled 114 community dwelling adults (55 years or older) in the study: all participants completed the MT and four other neuropsychological screening measures. Construct validity was evaluated using a three-step hierarchical regression model with the MT as the dependent variable. Demographic control variables were entered at step 1, followed by the Brief Interview of Mental Status (BIMS), and the Trail Making Test A (TMT A) at step 2, and finally TMT B and the Montreal Cognitive Assessment (MoCA) at step 3. It was hypothesised that measures sensitive to executive functioning (TMT B and MoCA) would significantly explain MT performance after controlling for demographic variables and adding measures of cognitive function to the model, providing additional evidence for construct validity of the MT. All three steps of the model were statistically significant (p < 0.01). Inclusion of measures sensitive to executive function in step 3 explained 30% of variability in MT score (adjusted R2 = 0.30). Our findings provide further empirical support for the construct validity of the MT, and offer implications for the use of the MT in acute and post-acute care settings.
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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 | 0.020 |
| 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 | 0.000 |
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".