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Usability Assessment of Pacemaker Programmers

2004· article· en· W2006119558 on OpenAlexaff
Christine Chiu, Kim J. Vicente, ILAN BUFFO‐SEQUEIRA, R. M. Hamilton, Brian W. McCrindle

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsUsabilityProgrammerReadabilityHeuristic evaluationComputer scienceHuman–computer interactionWeb usabilityUsability inspectionPluralistic walkthroughUsability labUsability goalsUser interfaceUsability engineeringProgramming language

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.416
Teacher spread0.386 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2004
Admission routes1
Has abstractyes

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