How Should Disability Be Measured in Older Adults? An Analysis from the Boston Rehabilitative Impairment Study of the Elderly
Bibliographic record
Abstract
OBJECTIVES: To determine and compare the predictive validity and responsiveness of the Late-Life Function and Disability Instrument (LLFDI) frequency and limitation dimensions in assessing two critical dimensions of disability: frequency of and limitations in performance of major life roles. DESIGN: Secondary analysis of 2-year follow-up data from the Boston Rehabilitative Impairment Study of the Elderly. SETTING: Primary care. PARTICIPANTS: Community-dwelling older adults (≥65) (n = 430) at risk of mobility decline. MEASUREMENTS: The LLFDI frequency and limitation dimensions, self-rated health, hospitalizations, and emergency department (ED) visits over 2 years. Responsiveness measures included effect size (ES) estimates and minimal detectable change (MDC) scores. RESULTS: The LLFDI frequency dimension predicted low self-rated health (odds ratio (OR) = 0.51, P < .001), hospitalizations (OR = 0.68, P < .001), and ED visits (OR = 0.73, P = .003) over 2 years, whereas the limitation dimension did not. The absolute ES was 0.63 for the frequency dimension and 0.81 for the limitation dimension. The proportion of subjects with a decline greater than or equal to the MDC was 10.6% for the frequency dimension and 14.2% for the limitation dimension. For participants who improved greater than or equal to the MDC, the proportion was 1.7% for the frequency dimension and 15.3% for the limitation dimension. CONCLUSION: Frequency of participation in major life roles was a better predictor of adverse outcomes than perceived limitations, although limitations appeared to be more responsive to meaningful change. These results can be used to guide the selection of the most appropriate metric for measuring disability in geriatric research.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| 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".