L’entraînement de la mémoire de travail par le programme Cogmed et le TDAH
Bibliographic record
Abstract
L’entraînement de la mémoire de travail par le logiciel Cogmed est souvent proposé dans le contexte d’un TDAH, ce trouble étant associé à un déficit de la mémoire de travail. L’objectif de cette recension des écrits est d’examiner les effets de cette intervention à partir de l’ensemble des études existantes comprenant un groupe témoin (n = 8), auprès d’enfants et d’adolescents présentant un TDAH. Les résultats indiquent une amélioration des composantes de la mémoire de travail principalement ciblées par le programme soient le calepin visuospatial et la boucle phonologique, décrits par le modèle de Baddeley (1986, 2007). Toutefois, les effets ne sont pas démontrés sur l’inhibition, le raisonnement non verbal, les capacités attentionnelles, les symptômes liés au TDAH et les performances scolaires. Modifier les exercices du programme afin d’entraîner des composantes plus complexes de la mémoire de travail tels que : l’administrateur central ou la mémoire secondaire pourrait favoriser la généralisation des effets. Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Inattention, hyperactivity, and impulsivity are key symptoms of ADHD. It is typically associated with working memory deficits at the cognitive level. For this reason, interventions have been designed to train working memory in ADHD. Currently, Cogmed Working Memory Training program is the most commonly used and studied program in clinical practice and research. This program is proposed as an intervention for ADHD that targets working memory deficits with specific exercises through intensive training sessions. The goal of this literature review is to examine the effects of the Cogmed program in children and adolescents with ADHD on working memory, inhibition, non-verbal reasoning, attention functioning, ADHD symptoms and academic achievement. All existing studies on the subject that included a control group (n = 8) are reviewed. It is clear from most studies that Cogmed training program increases and verbal and visuospatial working memory (or the phonological loop and visuospatial sketchpad in Baddeley's model (1986, 2007), among ADHD participants. However, transfer of learning is not demonstrated on other components of working memory that are not directly targeted by the program such as the central executive described in Baddeley's model or the secondary memory defined by Unsworth & Engle (2007). With regards to far transfer measures, results are controversial for inhibition, non-verbal reasoning, ADHD symptoms reported by parents, and reading abilities. No improvement is demonstrated for attentional capacities, ADHD symptoms reported by teachers and mathematic reasoning. Cogmed training improves verbal and visuospatial working memory, two cognitive functions that play an important role in ADHD. However, Cogmed's exercises need to be modified in order to train more complex working memory components such as the central executive (Baddeley, 1986, 2007) and the secondary memory (Unsworth & Engle, 2007), which are more impaired in ADHD than the phonological loop and visuospatial sketchpad. Another approach would be to design programs that can tackle a larger range of cognitive functions that are impaired in ADHD (e.g., inhibition). In future, studies evaluating such modified programs, direct observation instruments that are more sensitive to short-term changes need to be included. Follow-up measures should also be systematically included.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".