Mobility predicts change in older adults’ health-related quality of life: evidence from a Vancouver falls prevention prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Older adults with mobility impairments are prone to reduced health related quality of life (HRQoL) is highly associated with mobility impairments. The consequences of falls have detrimental impact on mobility. Hence, ascertaining factors explaining variation among individuals' quality of life is critical for promoting healthy ageing, particularly among older fallers. Hence, the primary objective of our study was to identify key factors that explain variation in HRQoL among community dwelling older adults at risk of falls. METHODS: We conducted a longitudinal analysis of a 12-month prospective cohort study at the Vancouver Falls Prevention Clinic (n = 148 to 286 depending on the analysis). We constructed linear mixed models where assessment month (0, 6, 12) was entered as a within-subjects repeated measure, the intercept was specified as a random effect, and predictors and covariates were entered as between-subjects fixed effects. We also included the predictors by sex and predictor by sex by time interaction terms in order to investigate sex differences in the relations between the predictor variable and the outcome variable, the EQ-5D. RESULTS: Our primary analysis demonstrated a significant mobility (assessed using the Short Performance Physical Battery and the Timed Up and Go) by time interaction (p < 0.05) and mobility by time by sex interaction (p < 0.05). The sensitivity analyses demonstrated some heterogeneity of these findings using an imputed and a complete case analysis. CONCLUSIONS: Mobility may be an important predictor of changes in HRQoL over time. As such, mobility is a critical factor to target for future intervention strategies aimed at maintaining or improving HRQoL in late life.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".