Implementation Strategies for a Scottish National Epilepsy Guideline in Primary Care: Results of the Tayside Implementation of Guidelines in Epilepsy Randomized (TIGER) Trial
Bibliographic record
Abstract
PURPOSE: To determine the effectiveness of two dissemination and implementation strategies to implement a national guideline for epilepsy management in primary care settings. METHODS: Three-arm cluster-randomized controlled trial. The participants were general practitioners from 68 practices in Tayside, Scotland, and 1,133 of their patients with self-reported epilepsy treated with antiepileptic medications (AEDs). Practices were randomized blind to a control, intermediate, or intensive intervention. CONTROL: Postal dissemination of a nationally developed clinical guideline. Intermediate intervention: Postal dissemination of the guideline supported by interactive, accredited workshops, and dedicated, structured protocol documents. Intensive intervention: Intermediate intervention plus a nurse specialist who supported and educated practices in the establishment of epilepsy review clinics. The primary outcome was the SF-36 health-related quality-of-life instrument. Secondary measures were a battery of prevalidated epilepsy-specific quality-of-life instruments. These were administered at baseline and after the intervention phase. Process of care was assessed by case-note review on number of review meetings and counseling sessions for epilepsy before and after the interventions. RESULTS: None of the intervention groups showed any change in the primary or secondary outcome measures or process-of-care measures. CONCLUSIONS: None of the intervention strategies led to improvements in patient quality of life or quality of epilepsy care. Further research is needed to discover why the interventions failed, to identify barriers to adoption of guidelines, and to develop strategies that might improve implementation and uptake in the future.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".