An Epilepsy Questionnaire Study of Knowledge and Attitudes in Canadian College Students
Bibliographic record
Abstract
PURPOSE: Controversy exists about the relation of societal knowledge and attitudes regarding epilepsy. We conducted a survey to examine knowledge and attitudes, to note gender and occupational influences, and to examine the effect of an informational brochure. METHODS: We administered a standardized questionnaire that noted demographics and examined knowledge and attitudes regarding epilepsy and persons with epilepsy, respectively, to a wide variety of Canadian college students. In a separate class we gave every other student a brochure regarding epilepsy and then administered the questionnaire to both the naïve and brochure-exposed students. RESULTS: Knowledge was patchy and weakest for the approximate prevalence of epilepsy in the population, hereditary epilepsy and several other etiologies, recognition of nonconvulsive seizures as a type of epilepsy, and knowledge of antiepileptic drug-induced teratogenicity. In contrast, attitudes were more uniformly favorable. However, 11 and 14%, respectively, showed negative bias against persons with epilepsy having children and equal opportunity for occupational employment. Women were slightly but significantly more tolerant than men. The brochure-exposed group showed better knowledge but equivalent attitudes compared with the naïve group. CONCLUSIONS: Results compare favorably with surveys in other countries. Although knowledge was patchy, it could be easily improved on with an educational brochure. Attitudes were positive but show some discrepancies from knowledge and a gender effect.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".