Leg and Trunk Impairments Predict Participation in Life Roles in Older Adults: Results From Boston RISE
Bibliographic record
Abstract
BACKGROUND: The physical impairments that affect participation in life roles among older adults have not been identified. Using the International Classification of Functioning Disability and Health as a conceptual framework, we aimed to determine the leg and trunk impairments that predict participation over 2 years, both directly and indirectly through mediation by changes in activities. METHODS: We analyzed 2 years of data from the Boston Rehabilitative Impairment Study of the Elderly, a cohort study of 430 primary care patients with self-reported mobility limitation (mean age 77 years; 68% female; average of four chronic conditions). Frequency of and limitations in participation were examined using the Late-Life Disability Instrument. Baseline physical impairments included: leg strength, leg speed of movement, knee range of motion (ROM), ankle ROM, leg strength asymmetry, kyphosis, and trunk extensor endurance. Structural equation modeling with latent growth curve analysis was used to identify the impairments that predicted participation at year 2, mediated by changes in activities. Models were adjusted for baseline participation, age, and gender. RESULTS: Leg speed and ankle ROM directly influenced participation in life roles during follow-up (βdirect = 1.39-4.53 and 4.70, respectively). Additionally, ankle ROM and trunk extensor endurance contributed indirectly to participation score at follow-up via effects on changes in activities (βindirect = -1.06 to -4.24 and 1.01 to 4.18, respectively). CONCLUSIONS: Leg speed, ankle ROM, and trunk extensor endurance are key physical impairments predicting participation in life roles in older adults. These results have implications for the development of exercise interventions to enhance participation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".