The diagnosis of ADHD in children and adolescents with epilepsy: a scoping review
Bibliographic record
Abstract
Attention-deficit hyperactivity disorder (ADHD) is often diagnosed in children and adolescents with epilepsy, but clear clinical guidelines on how to make this diagnosis are still lacking. Without these guidelines, there is no consensus between specialists on how to proceed when assessing children with epilepsy for ADHD, which can negatively impact the quality of care being offered to this population. As a first step toward gaining more specific clinical guidelines, this scoping review was aimed at documenting the tools and procedures used to diagnose ADHD in children and adolescents with epilepsy over time and at determining whether the diagnoses were made in accordance with clinical guidelines and recommendations. The literature search was conducted using PsycINFO, PubMed, and CINAHL. Studies were included if conducted with children and adolescents aged between 4 and 18 years with epilepsy being evaluated for ADHD. Studies were clustered according to their publication date and the reported diagnostic procedures were identified. Forty-nine out of 3854 records were included. Results highlight discrepancies between how ADHD was diagnosed in reviewed studies and clinical guidelines or recommendations. Indeed, most studies did not use a multi-method and multi-informant approach when diagnosing ADHD in children with epilepsy, with no improvement over time. Future studies aimed at diagnosing ADHD in children and adolescents should ensure that they are following clinical guidelines and recommendations, in addition to adapting their diagnostic procedures to the presence of any neurological comorbidities, such as epilepsy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".