Alzheimer’s Disease Assessment Scale - Cognitive Subscale (ADAS-Cog): Normative Data for the Portuguese Population
Bibliographic record
Abstract
Introduction: The Alzheimer’s Disease Assessment Scale – Cognitive Subscale is a brief battery developed to assess cognitive functioning in Alzheimer’s disease that encompasses the core characteristics of cognitive decline (e.g. memory, language, praxis, constructive ability and orientation). The early detection, as well as the monitoring of cognitive decline along disease progression, is extremely important in clinical care and interventional research. The main goals of the present study were to analyze the psychometric properties of the Portuguese version of the Alzheimer’s Disease Assessment Scale – Cognitive Subscale, and to establish normative values for the Portuguese population.Material and Methods: The Portuguese version of Alzheimer’s Disease Assessment Scale – Cognitive Subscale was administered to 223 cognitively healthy participants according to a standard assessment protocol consisting of the Mini-Mental State Examination, the Montreal Cognitive Assessment and the Adults and Older Adults Functional Assessment Inventory. Normal performance on the assessment protocol was the inclusion criteria for the study.Results: The Alzheimer’s Disease Assessment Scale – Cognitive Subscale revealed good psychometric properties when used in the Portuguese population. Age was the main predictor of the Alzheimer’s Disease Assessment Scale – Cognitive Subscale total score (R2 = 0.123), whereas the influence of education level was lower (R2 = 0.027). These two variables explained 14.4% of the variance on the Alzheimer’s Disease Assessment Scale – Cognitive Subscale scores and were used to stratify the normative values for the Portuguese population presented here.Conclusion: On the total sample, the average total score in the Alzheimer’s Disease Assessment Scale – Cognitive Subscale was 6 points. The normative data were determined according to age and educational level as these were the sociodemographic variables that significantly contributed to the prediction of the Alzheimer’s Disease Assessment Scale – Cognitive Subscale total scores, explaining 14.4% of their variance. The normative data are of the utmost importance to ensure proper use of this battery in Portugal.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".