Exploring the Psychological Risk Factors in Children with Epilepsy
Bibliographic record
Abstract
There are many factors that aggravate the clinical picture of children diagnosed with epilepsy. Through this study we will explore risk factors related to disease characteristics, cognitive impairments, intelligence and behavioral problems in children with epilepsy. Methods: Based on the medical data of children diagnosed with epilepsy being treated at the Pediatric Neurology Unit, University Hospital of Pristina, and the “Hope” Psychological Outpatient Center in Kosovo, about 100 epileptic children, 55 female and 45 male, aged between 6 and 11 years of school age were administered the Montreal Cognitive Assessment scale (MoCA), Raven’s Standard Progressive Matrices (IQ), and Child Behavior Checklist (CBCL) tests. Results: Children participating in the study reveals a predomination of the generalized epilepsy, which continue to be treated with anti-epileptics for more than 3 years. From them 67% did not show the presence of another co-neurological deficit. Neurological tests show evidences of moderate EEG changes in some children and MRI registrations in 65% of children are unchanged and continue to be treated with 1 or 2 antiepileptic drugs for being under control. Intelligence, cognitive and behavioral problems in cases where they were associated with a number of neuropsychological characteristics increase the risk of a disease aggravation and compromise their overall development. Discussion: We can imply that based on the severity of these concomitant factors of the epileptic conditions, they will constitute a high-risk factor for cognitive problems, low intelligence and the emergence of a number of internalizing and externalizing problems of the child with epilepsy. Conclusions: As a risk factor that increases the level of difficulty of epileptic children in some contexts, including general functioning, school, family and social context, the presence of neurobiological and neuropsychological factors such as issues in internalizing and externalizing behaviors, problems in the cognitive field and the IQ are seen, which is also expected to affect the overall development of children’s quality of life.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".