The influence of manual dexterity on processing speed assessment in multiple sclerosis: A comparison of the PST and oral SDMT
Bibliographic record
Abstract
Cognitive impairment (CI) is a common symptom in persons with Multiple Sclerosis (PwMS), specifically information processing speed (IPS) impairment. The Symbol Digit Modalities Test (SDMT), which requires in-person testing, is a well-established measure for screening for IPS and CI in clinic settings. The Processing Speed Test (PST), a self-administered iPad-based tool, has been proposed as an alternative. Preliminary studies suggest that the PST can effectively differentiate PwMS from healthy controls and correlates with MRI results. This study aims to investigate if the relationship between the PST and oral SDMT is affected by manual dexterity or level of disability. A cohort of 100 PwMS completed both the PST and SDMT, as well the 9-Hole Peg Test (9HPT) and Expanded Disability Status Scale (EDSS). The strong positive correlation found between the PST and SDMT was maintained across all subgroups based on 9HPT performance and EDSS functional system scores. Our findings indicate that the PST is comparable to the SDMT for PwMS regardless of manual dexterity. This validates PST as a time-efficient, self-administered alternative that can reduce clinical burden in MS care.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".