Bibliographic record
Abstract
BACKGROUND: The aim of this multinational (Canada, France, Germany, United Kingdom, and United States), task and interview-based study was to compare the ease of use and performance of the ClikSTAR® (sanofi-aventis, Paris, France) insulin pen with other commonly used reusable pens based on participant and interviewer assessments. METHODS: People with diabetes (n = 654) were asked to demonstrate four pens consecutively-ClikSTAR, Lilly Luxura ® (Eli Lilly, Indianapolis, IN), and NovoPen ® 3 and 4 (Novo Nordisk, Bagsvaerd, Denmark)-according to the respective instruction manuals. The endpoint was assessed by a rating from the participants and the interviewer. While the participants focused on the pen's ease of use, the interviewer considered the participants' difficulty in preparing and delivering a 40-unit dose and their requirement for help. RESULTS: Twenty percent of U.S. participants and 24% of participants from the other countries had type 1 diabetes. Approximately 50% of participants in each group had prior insulin pen experience. A higher proportion of participants, including those with dexterity or visual impairments, reported ClikSTAR as easier to use than other pens (P < 0.05). Participants using ClikSTAR did not experience any difficulty in completing the tasks. The proportion of participants not requiring help in completing the tasks with ClikSTAR was rated as numerically higher than, or similar to, that observed with Lilly Luxura or NovoPen 3 or 4 (75%, 74%, 62%, and 65%, respectively). According to participants, ClikSTAR and NovoPen 4 emerged as the most highly rated pens. CONCLUSIONS: In comparison with other pens, ClikSTAR was significantly easier to use, which, when taken together with overall performance, meets the need of people with diabetes.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".