Factor Analysis of the Community Balance and Mobility Scale in Individuals with Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The clinical assessment of balance is an important first step in characterizing the risk of falls. The Community Balance and Mobility Scale (CB&M) is a test of balance and mobility that was designed to assess performance on advanced tasks necessary for independence in the community. However, other factors that can affect balancing ability may also be present during performance of the real-world tasks on the CB&M. It is important for clinicians to understand fully what other modifiable factors the CB&M may encompass. The purpose of this study was to evaluate the underlying constructs in the CB&M in individuals with knee osteoarthritis (OA). METHODS: This was an observational study, with a single testing session. Participants with knee OA aged 50 years and older completed the CB&M, a clinical test of balance and mobility. Confirmatory factor analysis was then used to examine whether the tasks on the CB&M measure distinct factors. Three a priori theory-driven models with three (strength, balance, mobility), four (range of motion added) and six (pain and fear added) constructs were evaluated using multiple fit indices. RESULTS: ) participated. A three-factor model in which all tasks loaded on these three factors explained 65% of the variance and yielded the most optimal model, as determined using scree plots, chi-squared values and explained variance. The first factor accounted for 49% of the variance and was interpreted as lower limb muscle strength. The second and third factors were interpreted as mobility and balance, respectively. DISCUSSION: The CB&M demonstrated the measurement of three distinct factors, interpreted as lower limb strength, balance and mobility, supporting the use of the CB&M with people with knee OA for evaluation of these important factors in falls risk and functional mobility. Copyright © 2016 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".