Use of an interdisciplinary, participatory design approach to develop a usable patient self-assessment tool in atrial fibrillation
Bibliographic record
Abstract
After identifying that significant care gaps exist within the management of atrial fibrillation (AF), a patient-focused tool was developed to help patients better assess and manage their AF. This tool aims to provide education and awareness regarding the management of symptoms and stroke risk associated with AF, while engaging patients to identify if their condition is optimally managed and to become involved in their own care. An interdisciplinary group of health care providers and designers worked together in a participatory design approach to develop the tool with input from patients. Usability testing was completed with 22 patients of varying demographics to represent the characteristics of the patient population. The findings from usability testing interviews were used to further improve and develop the tool to improve ease of use. A physician-facing tool was also developed to help to explain the tool and provide a brief summary of the 2012 Canadian Cardiovascular Society atrial fibrillation guidelines. By incorporating patient input and human-centered design with the knowledge, experience, and medical expertise of health care providers, we have used an approach in developing the tool that tries to more effectively meet patients' needs.
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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 | 0.098 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".