Working Memory Training in Post-Secondary Students with ADHD: A Randomized Controlled Study
Bibliographic record
Abstract
OBJECTIVES: To determine whether standard-length computerized training enhances working memory (WM), transfers to other cognitive domains and shows sustained effects, when controlling for motivation, engagement, and expectancy. METHODS: 97 post-secondary students (59.8% female) aged 18-35 years with Attention-Deficit/Hyperactivity Disorder, were randomized into standard-length adaptive Cogmed WM training (CWMT; 45-min/session), a shortened-length adaptive version of CWMT (15 min/session) that controlled for motivation, engagement and expectancy of change, or into a no training group (waitlist-control group). All three groups received weekly telephone calls from trained coaches, who supervised the CWMT and were independent from the research team. All were evaluated before and 3 weeks post-training; those in the two CWMT groups were also assessed 3 months post-training. Untrained outcome measures of WM included the WAIS-IV Digit Span (auditory-verbal WM), CANTAB Spatial Span (visual-spatial WM) and WRAML Finger Windows (visual-spatial WM). Transfer-of-training effects included measures of short-term memory, cognitive speed, math and reading fluency, complex reasoning, and ADHD symptoms. RESULTS: Performance on 5/7 criterion measures indicated that shortened-length CWMT conferred as much benefit on WM performance as did standard-length training, with both CWMT groups improving more than the waitlist-control group. Only 2 of these findings remained robust after correcting for multiple comparisons. Follow-up analyses revealed that post-training improvements on WM performance were maintained for at least three months. There was no evidence of any transfer effects but the standard-length group showed improvement in task-specific strategy use. CONCLUSIONS: This study failed to find robust evidence of benefits of standard-length CWMT for improving WM in college students with ADHD and the overall pattern of findings raise questions about the specificity of training effects. TRIAL REGISTRATION: ClinicalTrials.gov NCT01657721.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".