Usability Assessment of Pacemaker Programmers
Bibliographic record
Abstract
There is a perception among clinicians of usability differences in the user interface of pacemaker programmers, but there is an absence of literature in this area. The purpose of this study was to describe usability differences in pacemaker programmers. Forty-two programmer users completed self-administered questionnaires and two usability experts independently performed heuristic evaluation to identify features that violated general usability principles. Programmers from seven manufacturers (coded A-G) were evaluated. There was a balanced representation of users: nurses (58%) versus technologists (40%) who are employed in community (50%) versus academic (45%) hospitals, novice versus expert users based on the median users' programming experience of 60 months (range 1-300 months). Significant differences between programmers were found in overall user satisfaction and ease of programmer use (P < 0.0001) in the display, controls, operation, and physical dimension of the programmers (P < 0.05). Heuristic evaluations showed frequent violations of usability principles in all programmers. Problematic areas include reliance on user recall, inconsistency in operation of critical controls, poor readability, and not anticipating user wants or action. Programmer interface designs do not consistently meet user needs or general usability principles. This impacts on the safe and effective use of programmers. Guidelines in programmer design should be established, particularly with respect to labeling, location, and operation of critical controls.
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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 | 0.008 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".