Successful Aging Through Successful Accommodation With Assistive Devices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To provide a profile of older adults who successfully accommodate declines in capacity by using assistive devices. METHOD: Using the National Health and Aging Trends Study, we provide national estimates of prevalent, incident, and persistent successful accommodation of mobility and self-care activity limitations. For incident and persistent accommodation groups, we describe their subjective wellbeing and participation restrictions, health and functioning, demographic and socioeconomic characteristics, and acquisition of assistive devices and environmental features. We estimate regression models predicting incident and persistent successful accommodation and the extent of wellbeing and participation restrictions for incident and persistent groups (vs. those who are fully able). RESULTS: Nearly one-quarter of older adults have put in place accommodations that allow them to carry out daily activities with no assistance or difficulty. In adjusted models, incident and persistent successful accommodation is more common for those ages 80-89, those with more children, and those living in homes with environmental features already installed; wellbeing levels for these groups are similar and participation restrictions only slightly below those who are fully able. DISCUSSION: A focus on facilitating successful accommodation among those who experience declines in capacity may be an effective means of promoting participation and wellbeing in later life.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it