Implementation of patient education for patients with atrial fibrillation: nationwide cross-sectional survey and one-year follow-up
Bibliographic record
Abstract
AIMS: Clinical practice guidelines recommend patient education for patients with atrial fibrillation (AF) as a part of holistic care, however, clinical guidelines lack detailed specification on the content, structure, and delivery of AF education programmes. To examine the implementation of education for patients with AF in Denmark in relation to coverage, organization, and content. METHODS AND RESULTS: A cross-sectional survey was conducted from February to May 2021. The survey contained questions on the organization, delivery, and content of education for patients with AF from all 29 AF outpatient hospital sites in Denmark. The survey was conducted by email and telephone. One-year follow-up was done in May 2022 by email. Patient education was provided by healthcare professionals in 16 (55%) hospitals. Nurse workforce issues, management, non-prioritization, and lack of guidance for implementation were reasons for the absence of patient education in 13 (45%) hospitals. The structure of patient education differed in relation to group or individual teaching methods and six different education models were used. Content of the AF disease education was generally similar. At 1-year follow-up, another four hospitals reported offering patient education (69% in total). CONCLUSION: Initially, almost half of the hospitals did not provide patient education, but at 1-year follow-up, 69% of hospitals delivered patient education. Patient education was heterogeneous in relation to delivery, frequency, and duration. Future research should address individualized patient education that may demonstrate superiority in relation to quality of life, less hospital admissions, and increased longevity.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".