Clinical balance assessment: perceptions of commonly-used standardized measures and current practices among physiotherapists in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Balance impairment is common in multiple clinical populations, and comprehensive assessment is important for identifying impairments, planning individualized treatment programs, and evaluating change over time. However, little information is available regarding whether clinicians who treat balance are satisfied with existing assessment tools. In 2010 we conducted a cross-sectional survey of balance assessment practices among physiotherapists in Ontario, Canada, and reported on the use of standardized balance measures (Sibley et al. 2011 Physical Therapy; 91: 1583-91). The purpose of this study was to analyse additional survey data and i) evaluate satisfaction with current balance assessment practices and standardized measures among physiotherapists who treat adult or geriatric populations with balance impairment, and ii) identify factors associated with satisfaction. METHODS: The questionnaire was distributed to 1000 practicing physiotherapists. This analysis focuses on questions in which respondents were asked to rate their general perceptions about balance assessment, the perceived utility of individual standardized balance measures, whether they wanted to improve balance assessment practices, and why. Data were summarized with descriptive statistics and utility of individual measures was compared across clinical practice areas (orthopaedic, neurological, geriatric or general rehabilitation). RESULTS: The questionnaire was completed by 369 respondents, of which 43.4% of respondents agreed that existing standardized measures of balance meet their needs. In ratings of individual measures, the Single Leg Stance test and Berg Balance Scale were perceived as useful for clinical decision-making and evaluating change over time by over 70% of respondents, and the Timed Up-and-Go test was perceived as useful for decision-making by 56.9% of respondents and useful for evaluating change over time by 62.9% of respondents, but there were significant differences across practice groups. Seventy-nine percent of respondents wanted to improve their assessments, identifying individual, environmental and measure-specific barriers. The most common barriers were lack of time and knowledge. CONCLUSIONS: This study offers new information on issues affecting the evaluation of balance in clinical settings from a broad sample of physiotherapists. Continued work to address barriers by specific practice area will be critical for the success of any intervention attempting to implement optimal balance assessment practices in the clinical setting.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| 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".