Patient satisfaction with care in epilepsy: How much do we know?
Bibliographic record
Abstract
OBJECTIVE: Satisfaction with epilepsy care (SEC) encompasses care delivery, expectations, attitudes, and disease course. Through a systematic review of the evidence, we explore how and where the SEC of patients is being measured, the level of SEC overall and in specific domains, and its relationship to clinical and demographic variables. METHODS: We searched Medline, PsycINFO, CINAHL, Cochrane Register of Controlled Trials, and EMBASE using medical subject headings and keywords related to satisfaction with care and epilepsy in adults and children, in all languages. Two independent reviewers screened abstracts and full-text articles. We examined the clinical context and patient characteristics, type and content of satisfaction scales, and reported outcomes. Abstracted variables were grouped for descriptive purposes and presented as medians and proportions when the data allowed it. RESULTS: Of 25 included studies (6,336 patients), 88% were performed in the United States or the United Kingdom. Nine studies (36%) used validated instruments and 16 studies (64%) used nonvalidated instruments. For SEC domains reported in >1 study, the median proportion (interquartile range) of patients satisfied with epilepsy care was 86% (17%) for overall satisfaction with care, 85% (24%) for interpersonal skills, 78% (3%) for access to care, 67% (32%) for communication, and 65% (15%) for knowledge/technical skills. Communication and clinicians' knowledge was important in all settings. Patients seen in specialized settings and those receiving more and better information had higher SEC ratings. There was no consistent association between SEC and quality of care indicators. SIGNIFICANCE: Data on SEC have been reported infrequently. Patients are least satisfied with communication, perceived skills, and knowledge of care providers. Epilepsy-specific SEC tools have neither been validated nor do they contain many of the important domains identified by this review. The relationship between SEC and indicators of quality of care requires further study. Measures aimed at improving education and communication could improve SEC.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".