<scp>M</scp>easurement instruments to assess posture, gait, and balance in <scp>P</scp>arkinson's disease: Critique and recommendations
Bibliographic record
Abstract
BACKGROUND: Disorders of posture, gait, and balance in Parkinson's disease (PD) are common and debilitating. This MDS-commissioned task force assessed clinimetric properties of existing rating scales, questionnaires, and timed tests that assess these features in PD. METHODS: A literature review was conducted. Identified instruments were evaluated systematically and classified as "recommended," "suggested," or "listed." Inclusion of rating scales was restricted to those that could be used readily in clinical research and practice. RESULTS: One rating scale was classified as "recommended" (UPDRS-derived Postural Instability and Gait Difficulty score) and 2 as "suggested" (Tinetti Balance Scale, Rating Scale for Gait Evaluation). Three scales requiring equipment (Berg Balance Scale, Mini-BESTest, Dynamic Gait Index) also fulfilled criteria for "recommended" and 2 for "suggested" (FOG score, Gait and Balance Scale). Four questionnaires were "recommended" (Freezing of Gait Questionnaire, Activities-specific Balance Confidence Scale, Falls Efficacy Scale, Survey of Activities, and Fear of Falling in the Elderly-Modified). Four tests were classified as "recommended" (6-minute and 10-m walk tests, Timed Up-and-Go, Functional Reach). CONCLUSION: We identified several questionnaires that adequately assess freezing of gait and balance confidence in PD and a number of useful clinical tests. However, most clinical rating scales for gait, balance, and posture perform suboptimally or have been evaluated insufficiently. No instrument comprehensively and separately evaluates all relevant PD-specific gait characteristics with good clinimetric properties, and none provides separate balance and gait scores with adequate content validity for PD. We therefore recommend the development of such a PD-specific, easily administered, comprehensive gait and balance scale that separately assesses all relevant constructs. © 2016 International Parkinson and Movement Disorder Society.
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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 | 0.036 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".