A feasibility study of working memory training for individuals with paediatric-onset multiple sclerosis
Bibliographic record
Abstract
Objective: To investigate the feasibility and experiences of paediatric-onset multiple sclerosis (MS) patients completing a working memory training programme.Methods: Nine paediatric-onset MS patients (mean age 19.3 ± 4.1 years) identified as having attention and/or working memory difficulties underwent a five-week (five days/week) internet-based working memory training programme (Cogmed™); weekly coaching was provided. Measures of adherence and tolerance were used to establish the feasibility of implementing computerised cognitive training. Qualitative experiences reported by the patients were analysed and factors that may modulate the effects of training were explored.Results: Six of the nine enrolled patients completed the programme within the recommended time, and all individuals, with the exception of one, were considered to tolerate the training well. Eight of the nine participants acknowledged that training was helpful in one or more ways. All but one participant reported improvements in working memory, although evidence for improvement on objective neuropsychological testing was limited. Lower normalised brain volume emerged as a potentially important variable in predicting extent of improvement on the training programme.Conclusion: Selected paediatric-onset MS patients can tolerate and complete an intensive cognitive rehabilitation programme. Future investigation of moderators of training effects and the stability of the findings over time is needed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".