Near‐transfer effects following working memory intervention (Cogmed) in children with symptomatic epilepsy: An open randomized clinical trial
Bibliographic record
Abstract
OBJECTIVE: Limited research exists regarding the effectiveness of educational and psychological interventions for improving commonly presenting cognitive impairments experienced by children with epilepsy. We evaluated the efficacy of a commercially available, computerized, working memory (WM) program (Cogmed) using a well-defined population of children with epilepsy. METHODS: In this controlled trial, 77 children with symptomatic epilepsy (ages 6.5-15.5 years; 100% taking medication) with estimated intellectual ability greater than the 2nd percentile were randomly assigned to an intervention (n = 42) or waitlist-control (n = 35) group. Standardized assessments of attention and WM were administered pre- and posttraining or waitlist interval, 7 weeks apart. RESULTS: Without intervention, participants displayed significant weaknesses in intelligence, attention, and WM compared to normative samples. After controlling for preintervention scores and intelligence, we found that significant treatment effects for the intervention group were evident for visual attention span, auditory WM, and visual-verbal WM. Intention-to-treat analyses (all participants) and sensitivity analyses (n = 37 and n = 21 for the intervention and waitlist-control groups, respectively) were highly similar, providing confidence to the results. Effect sizes for significant outcomes were large (greater than or equal to two thirds of the standard deviation of the normative-data). The clinical/demographic and functional factors studied did not elucidate who most benefits from training. SIGNIFICANCE: This is the first study to evaluate the effectiveness of intervention to ameliorate WM deficits commonly experienced by children with symptomatic epilepsy. Results support group improvement on some untrained tasks immediately postintervention, demonstrating preliminary usefulness of Cogmed as a treatment option.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".