Psychosocial Impact of Epileptic Seizures in a Dutch Epilepsy Population: A Comparative Washington Psychosocial Seizure Inventory Study
Bibliographic record
Abstract
PURPOSE: The psychosocial functioning of epilepsy patients from the Netherlands was investigated and compared with results from other countries. The impact of epilepsy was also studied in two different groups of Dutch epilepsy patients, inpatients and outpatients. METHODS: The Washington Psychosocial Seizure Inventory (WPSI) was used to study the psychosocial problems of 134 Dutch outpatients and 181 Dutch inpatients. WPSI profiles were compared with those from the former German Democratic Republic (West Germany), Finland, Canada, the United States, Chile, and Japan. RESULTS: For the Dutch epilepsy patients, most of the psychosocial problems were experienced by inpatients; they had serious problems in emotional, interpersonal, and vocational adjustment, adjustment to seizures, and overall psychosocial functioning. Seizure-free outpatients, however, experienced significant problems only in the emotional adjustment area. Comparing the outcomes of various countries, Dutch outpatients and patients from West Germany and Finland experienced the least psychosocial difficulties, whereas epilepsy patients from Chile, Japan, and Canada have serious problems in most areas of psychosocial functioning. CONCLUSIONS: Patients with epilepsy experience psychosocial problems, although the amount of psychosocial difficulties depends on the seizure frequency and the culture that patients live in.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".