Clinical Motor Coordination Tests in Adult Neurology: A Scoping Review
Bibliographic record
Abstract
Purpose: This scoping review aimed to identify which clinical tests are used to assess upper limb, lower limb, and trunk motor coordination, and their metric and measurement properties for adult neurological populations. Method: MEDLINE (1946–) and EMBASE (1996–) databases were searched using keywords such as movement quality, motor performance, motor coordination, assessment, and psychometrics. Data regarding the body part assessed, neurological condition, psychometric properties, and scored metrics of spatial and/or temporal coordination were independently extracted by two reviewers. Alternate versions of some tests such as the Finger-to-Nose Test were included. Results: Fifty-one included articles yielded 2 tests measuring spatial coordination, 7 tests measuring temporal coordination, and 10 tests measuring both. Scoring metrics and measurement properties differed between tests, with a majority of tests having good-to-excellent measurement properties. Conclusions: The metrics of motor coordination scored by current tests vary. Since tests do not assess functional task performance, the onus falls on clinicians to infer the connection between coordination impairments and functional deficits. Clinical practice would benefit from the development of a battery of tests that assesses the metrics of coordination related to functional performance.
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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".