Limitations of the Paced Auditory Serial Addition Test as a measure of working memory in patients with multiple sclerosis
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Bibliographic record
Abstract
The Paced Auditory Serial Addition Test (PASAT) is a commonly used procedure that combines elements of both a working memory task and a test of information processing speed. Patients with multiple sclerosis (MS) have consistently been found to be impaired on this test and it has been recommended as a core outcome measure in clinical trials. The standard score for this task is the number of correct responses at each stimulus presentation rate but a concern has been raised that subjects may ignore some test items in order to chunk the information into manageable portions and avoid performing several cognitive tasks simultaneously. To account for this strategy, one can examine the proportion of correct responses that are consecutive (termed dyads), since such responses require that the task be performed according to the instructions. We compared a group of 35 mildly to moderately disabled MS patients and matched healthy controls on the PASAT. The MS patients made significantly fewer correct responses at the 2 slowest presentation rates (2.4, 2.0 s/digit) while their scores at faster rates (1.6, 1.2 s/digit) did not discriminate them from controls as well. Nevertheless, the MS patients' percentage of dyads was significantly lower than that of the control sample across all stimulus presentation rates. While our study supports the use of the PASAT as a test that distinguishes MS patients from healthy individuals, our results also illustrate problems that lie in the interpretation of this difference in performance. It appears that a chunking strategy may be common in the PASAT, particularly as task demands increase, and that this may mask actual performance differences. If so, the total correct response score alone is limited as a measure of working memory and information processing speed. More detailed analyses of PASAT performance, coupled with other measures of information processing, may help clarify the underlying cognitive deficits of MS patients.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it