Youth Weigh In: Views on Advanced Neurotechnology for Drug-Resistant Epilepsy
Bibliographic record
Abstract
BACKGROUND: Epilepsy affects over 500,000 children in North America of whom 30% have drug-resistant epilepsy. Advancements with neurotechnologies show promising benefits, but the perceptions of these procedures by youth is unknown. METHODS: We conducted semistructured interviews with 10 youth in British Columbia, Canada who underwent procedures for drug-resistant epilepsy involving different forms of neurotechnology (subdural grids, vagus nerve stimulation, responsive neurostimulation). Interviews were analyzed using the constant comparative qualitative method. RESULTS: Four major thematic categories emerged from the interviews. Treatment values, impact of the disorder, personal context, and impact of neurotechnology. CONCLUSIONS: Besides the predictable goal of seizure reduction, a desire for autonomy and the importance of trust in the medical team emerged as dominant values within the 4 thematic categories that were explicit to the use of new neurotechnologies for the management of drug-resistant 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".