Age Scale for Assessing Activities of Daily Living
Bibliographic record
Abstract
The purpose of this study was to develop an age scale for assessing activities of daily living (ADL) among community-dwelling adults aged 75 years or older. Participants were 1006 older Japanese: 312 men (79.6 ± 4.3 years) and 694 women, (79.9 ± 5.5 years). Participants completed a battery of 8 performance tests related to ADL and the Barthel index (BI) questionnaire. Spearman rank-order correlation analysis was applied to obtain the correlation of the 8 ADL performance tests with the total BI score. Three variables were high rank-order correlated with BI, secondly those items were subjected to the principal component analysis. The weighted combination of the principal component scores was summed. Resulting in an ADL score (ADLS), women = 0.075 X1 – 0.082 X2 – 0.063 X3 + 0.124, men = 0.051 X1 – 0.105 X2 – 0.099 X3 + 0.249, where X1 = hand-grip strength, X2 = timed up and go, X3 = five-chair sit to stand. Individual ADLS was transformed to an ADL age scale (ADLA). The estimation was – 5.493 ADLS + 79.90 for women, and – 4.272 ADLS + 79.57 for men. Due to the distortion at the regression edges, the equation was corrected as suggested by Dubina et al. ADLA women after correction was = 0.447 (chronological age: CA) – 5.49ADLS + 44.17, men = 0.519CA – 4.27ADLS + 38.26. ADLA can be used to identify or monitor the characteristics of the ADL levels of physical abilities in older Japanese aged 75 years or older.
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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".