Clinical and Laboratory Based Proprioceptive Assessments in Older Adults and People with Multiple Sclerosis
Bibliographic record
Abstract
Proprioception is the sense of body position in space (Gilman, 2002; Goble, Coxon, et al., 2012), and can be evaluated using both clinical assessments and laboratory based tasks. To date, normal aging has been shown to lead to a decline in proprioceptive acuity as assessed via laboratory based proprioceptive matching tasks, while proprioceptive deficits have been assumed to be present in people with multiple sclerosis (PwMS) based on performance on clinical assessments. The objective of the current study was to determine if performance on clinical assessments and laboratory based proprioceptive matching tasks is similar across older adults (OA) and PwMS (Adamo et al., 2007; Goble, 2010; Herter et al., 2014; Jamali et al., 2017; Khan et al., 2018; Scherder et al., 2018). Twenty-four OA participants (70+ years old) and twenty PwMS from the Ottawa community were recruited to take part in this study. Proprioceptive sense was assessed using clinical assessments (i.e., superficial sensation, vibration sense and joint position sense) and laboratory based proprioceptive matching tasks. Analysis revealed that while OA performed better on the clinical assessments, PwMS were more accurate in the laboratory matching tasks. Furthermore, analysis of goal directed movements in the matching tasks, revealed that PwMS spent more time in the initial, planning stage of the movement compared to OA, who spent more time executing their movements. These results indicate that OA and PwMS do not demonstrate similar deficits across clinical assessments and laboratory based proprioceptive tasks, and in fact plan and execute their movements differently. Moreover, results also call into question the relationship between clinical and laboratory based assessments of proprioception.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".