Vocabulary knowledge as a reliable proxy of cognitive reserve in multiple sclerosis: a validation study
Bibliographic record
Abstract
INTRODUCTION: The present study aimed to explore the suitability of the vocabulary knowledge (VOC) test as an accurate and reliable proxy of cognitive reserve (CR) by evaluating its psychometric properties and discrimination accuracy compared with other CR measures in multiple sclerosis (MS). METHODS: Sixty-eight consecutive people with multiple sclerosis (pwMS), followed at our MS outpatient clinic, completed a clinical evaluation and neuropsychological assessment including: VOC, Brief Repeatable Battery of Neuropsychological Tests (BRB-N), Cognitive Reserve Index Questionnaire (CRIq), Beck Depression Inventory-II, and State-Trait Anxiety Inventory. Reliability, convergent and divergent validity, and discrimination accuracy of the VOC were assessed using educational level as reference standard. The possible effects of sociodemographic and clinical factors on VOC and their role in predicting global cognitive status were also explored. RESULTS: VOC demonstrated good internal consistency (Cronbach's α = 0.894) and adequate construct validity. It showed an acceptable level of discrimination between pwMS with high and low CR, comparable to the CRIq score. Education strongly affected VOC scores, which in turn were independent of MS features. VOC emerged as an independent predictor of global cognitive status together with MS-related disability. CONCLUSION: We demonstrated the validity of VOC as a reliable CR measure in pwMS. Thus, CR may also be estimated using fixed objective measures, independent of brain pathology and clinical features. Early CR estimation may help clinicians identify pwMS at a higher risk of cognitive decline and plan strict neuropsychological monitoring and cognitive interventions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".