Newly Diagnosed Epilepsy: Can Nurse Specialists Help? A Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: To describe a group of people with newly diagnosed epilepsy and to test the effect of an epilepsy nurse specialist on patients' knowledge of epilepsy, satisfaction with the advice provided, and psychological well-being. METHODS: Neurologists in the United Kingdom (U.K.) recruited adults with newly diagnosed epilepsy. Patients were randomized to receive the offer of two appointments with an epilepsy nurse specialist or usual medical care. The main outcome measures were a questionnaire assessing patients' knowledge of epilepsy, the Hospital Anxiety and Depression Scale, and patients' reported satisfaction with the advice and explanations provided on key epilepsy-related topics. RESULTS: Ninety people with new epilepsy completed the trial. At baseline, fewer than half the patients reported having been given enough advice on epilepsy, and there were important differences in patients' knowledge of epilepsy. Lack of a U.K. school-leaving examination pass (General Certificate School Examination) was associated with lower knowledge of epilepsy (p = 0.03). At follow-up, the patients randomized to see the nurse specialist were significantly more likely to report that enough advice had been provided on most epilepsy-related topics compared with the control group. There were no significant differences in knowledge of epilepsy scores. However, there were significant differences in the group who, at baseline, had knowledge scores in the lowest quartile; those randomized to the nurse had higher knowledge scores (42.7 vs. 37.2; p < 0.01). Compared with doctors, the nurse was highly rated for providing clear explanations. CONCLUSIONS: Patients who have less general education have less knowledge of epilepsy. The introduction of a nurse specialist in epilepsy is associated with a significant increase in patient reports that enough advice has been provided. Nurse intervention appears to help those with the least knowledge of epilepsy improve their knowledge scores.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.019 | 0.002 |
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; both teacher heads agree on what is shown here.
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".