Functional Disability in Early Alzheimer’s Disease – A Validation Study of the Italian Version of the Disability Assessment for Dementia Scale
Bibliographic record
Abstract
AIM: To determine the applicability and psychometric properties of the Italian version of the Disability Assessment of Dementia scale (DAD-I) in a community-residing population with early-stage Alzheimer's disease (AD). METHODS: The DAD-I was administered to the primary caregivers of 159 patients (mean age +/- SD 77.1 +/- 5.2) with mild AD (mean Mini Mental State Examination, MMSE, +/- SD 23.1 +/- 2.2). RESULTS: The DAD-I showed excellent internal consistency reliability (Cronbach's alpha = 0.92) and good construct validity. The DAD-I score was not significantly associated with gender, education and presumed duration of the illness, and had a low negative correlation with age. The DAD-I score correlated moderately with the traditional Instrumental Activities of Daily Living and Activities of Daily Living scales, respectively, with r = 0.53 and r = 0.54 (p < 0.0001). Relatively low, but statistically significant correlations (r ranging between 0.21 and 0.31) with the MMSE were also found. CONCLUSION: The DAD-I was found to be a reliable and valid instrument to assess functional disability in community-dwelling Italian subjects with early-stage AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".