Score Distributions of the Balance Outcome Measure for Elder Rehabilitation (BOOMER) in Community-Dwelling Older Adults With Vertebral Fracture
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We sought to evaluate the Balance Outcome Measure for Elder Rehabilitation (BOOMER) in community-dwelling women 65 years and older with vertebral fracture and to describe score distributions and potential ceiling and floor effects. METHODS: This was a secondary data analysis of baseline data from the Build Better Bones with Exercise randomized controlled trial using the BOOMER. A total of 141 women with osteoporosis and radiographically confirmed vertebral fracture were included. Concurrent validity and internal consistency were assessed in comparison to the Short Physical Performance Battery (SPPB). Normality and ceiling/floor effects of total BOOMER scores and component test items were also assessed. Exploratory analyses of assistive aid use and falls history were performed. RESULTS AND DISCUSSION: Tests for concurrent validity demonstrated moderate correlation between total BOOMER and SPPB scores. The BOOMER component tests showed modest internal consistency. Substantial ceiling effect and nonnormal score distributions were present among overall sample and those not using assistive aids for total BOOMER scores, although scores were normally distributed for those using assistive aids. The static standing with eyes closed test demonstrated the greatest ceiling effects of the component tests, with 92% of participants achieving a maximal score. CONCLUSIONS: While the BOOMER compares well with the SPPB in community-dwelling women with vertebral fractures, researchers or clinicians considering using the BOOMER in similar or higher-functioning populations should be aware of the potential for ceiling effects.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".