Why patients say no: Patient barriers to epilepsy surgery among patients with drug‐resistant epilepsy in Singapore
Bibliographic record
Abstract
OBJECTIVE: Epilepsy surgery is globally underutilized due to disease-, system-, and patient-related barriers. These barriers are suboptimally understood in Asia. Patient-related barriers are of particular interest because they are culture-specific and may present a significant obstacle regardless of resource availability. This study aims to identify patient-related barriers in Singapore, an ethnically heterogeneous Asian country. METHODS: We conducted a cross-sectional survey of focal drug-resistant epilepsy (DRE) patients attending the neurology specialist outpatient clinic of a major tertiary hospital in Singapore. The survey contained 28 items assessing patient perceptions of epilepsy and its treatment, and 7 items on the patient's socioeconomic status. It was adapted with permission from a previous Canadian study. RESULTS: A total of 66 patients completed the survey. Most patients (74.2%) were aware of surgery as an option for the treatment of epilepsy, and patients with university degrees were more likely to be aware (p = 0.007). Most (69.7%) viewed surgery as a "last resort," and 83.3% overestimated the risks of surgery. Even when hypothetically offered guarantees of surgical success, only 57.6% of patients responded favorably to surgery, with those acknowledging their seizures as disabling being more likely to respond favorably (p = 0.027). Financial considerations did not significantly influence reactions to hypothetically successful surgery (p = 1.000). SIGNIFICANCE: There are major patient-related barriers to epilepsy surgery among DRE patients in Singapore, contributed by an overestimation of surgical risks and an indifference to seizure-related disability in some patients. Based on our findings, financial subsidies alone may not suffice in addressing patient-related barriers; accompanying patient education efforts may be important. PLAIN LANGUAGE SUMMARY: A survey of patients with refractory epilepsy in Singapore revealed that patients are relatively averse to undergoing pre-surgical evaluation and surgical treatment for epilepsy, despite scientific evidence of effectiveness. Some of the major barriers include patients overestimating the risks of epilepsy surgery and perceiving seizures to be non-disabling. Our findings suggest that financial subsidies for surgery alone may not overcome patients' aversion to surgery, and that patient education is also required.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".