Stressors at the onset of adult epilepsy: implications for practice
Bibliographic record
Abstract
The association between major life events and seizure frequency in patients with chronic epilepsy has previously been suggested in the literature. However, significant life events as precipitating factors for the occurrence of the first seizure have been considered but not documented. Recognition of such triggers may lead to a better understanding of the cause and mechanism of the epilepsy. Using a phenomenological approach, 19 participants were interviewed and recalled the occurrence of significant life events in the year prior to a diagnosis of generalized or focal epilepsy. There were gender and age-related differences in the types of triggering events, e.g. men tended to specify work related stressors while women generally cited relationship issues. None of the participants reported constraining beliefs about the cause of their epilepsy. Most respondents incorporated their knowledge of seizure triggers into strategies to achieve control of their epilepsy. This study highlights the potential value of questioning possible life stressors as triggers for the onset of epilepsy. Early awareness of high risk factors for seizures may lead to strategies of seizure self control by avoiding situations associated with high risks, improving lives disrupted by the uncertainty of epilepsy.
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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 | 0.015 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".