Recommended Measures for the Assessment of Cognitive and Physical Performance in Older Patients with Dementia: A Systematic Review
Bibliographic record
Abstract
UNLABELLED: AIM/GOAL: To recommend a set of neuropsychological and physical exercise tests for researchers to assess cognition and physical fitness in clinical trials with older patients with dementia; to create consensus, decrease heterogeneity, and improve research quality. METHODS: A literature search (2005-2011) yielded 89 randomized controlled trials. To provide information on test recommendations the frequency of test use, effect size of the test outcome, study quality, and psychometric properties of tests were analyzed. RESULTS: Fifty-nine neuropsychological tests (cognitive domains: global cognition, executive functioning, memory, and attention) and 10 exercise tests (physical domains: endurance capacity, muscle strength, balance, and mobility) were found. CONCLUSION: The Severe Impairment Battery, Mini Mental State Examination, and Alzheimer Disease Assessment Scale - cognitive subscale were recommended to measure global cognition. The Verbal Fluency Test Category/Letters, Clock Drawing Test, and Trail Making Test-B were recommended to measure executive functioning. No specific memory test could be recommended. The Digit Span Forward, Digit Span Backward, and Trail Making Test-A were recommended to measure attention. As physical exercise tests, the Timed Up and Go and Six Meter Walk for mobility, the Six Minute Walk Distance for endurance capacity, and the Tinetti Balance Scale were recommended.
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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 | 0.016 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".