Do Wechsler intelligence scales predict academic achievement in children with ADHD or autism? A systematic review and meta-analysis
Bibliographic record
Abstract
Intelligence tests predict academic achievement in typically developed children, however if this is the case also in children with attention-deficit/hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) is not clear. This systematic review and meta-analysis examined if Wechsler intelligence scales predict academic achievement and/or grades in children, ages 6-16 years, with ADHD and/or ASD. We searched the databases PubMed, PsycINFO and Education Research Complete for studies published between 2000 and 2023. We used the Newcastle-Ottawa Scale to assess risk of bias. Narrative synthesis and meta-analysis were performed. Twelve studies (ADHD n = 1,834, ASD n = 176) were included in the review, and six samples (ADHD n = 1,112) of those were included in the meta-analyses. The results of the meta-analyses showed moderate overall weighted correlations between IQ and word reading, written language, and mathematics respectively. Similarly, the overall weighted correlations between processing speed and the aforementioned domains of academic achievement were moderate. Meta-analysis with additional Wechsler scales composite scores could not be conducted. In the narrative synthesis, Full Scale IQ was associated with academic achievement in both ADHD and ASD, and grades in ADHD. The limited number of ASD participants and the heterogeneity of the samples need to be considered when interpreting results. Generally, the results indicate that Wechsler scales are valuable in predicting academic achievement in children with ADHD or ASD. Motivation and other factors related with academic achievement need to be further explored in these groups.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.039 | 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".