Preference Differences between Insulin Glargine and MK-1293 Pens among Patients with Diabetes and Certified Diabetes Educators
Bibliographic record
Abstract
This study sought to develop and implement a usability/preference survey to compare the pen devices used with innovator insulin glargine and MK-1293 (Pen X). Type 1 and type 2 diabetes patients and certified diabetes educators (CDEs) in the U.S., Canada, and the UK were recruited from commercial panels. Several rounds of qualitative research with both groups were conducted to develop and refine the survey. Respondents were asked to perform two mock injections (into a cushion pad) for each of the two insulin pens. Pen order was randomized and after each set of injections, respondents completed the survey. Non-inferiority analyses were conducted to compare ratings of the pens as the primary analysis; two-tailed tests were also conducted. 296 respondents completed the study (177 patients and 119 CDEs). The mean age was 53.2 years for patients and 49.4 years for CDEs; 55.9% and 1.7% were male, respectively; 27.1% of patients were type 1 and 72.9% were type 2. Both patients (66.7%) and CDEs (58.0%) preferred Pen X overall. Individual ratings are reported in Table. The qualitative research results indicated our measure had appropriate content validity for assessing pen preferences. The main results suggested that the appearance and function of Pen X is non-inferior to the insulin glargine pen from the perspective of both patients and CDEs and, in many cases, superior.Table. Patients (N=177)CDEs (N=119)Rated insulin glargine pen higherRated both pens identicallyRated Pen X higherRated insulin glargine pen higherRated both pens identicallyRated Pen X higherOverall, this pen would be "easy to teach" my patients to use (CDEs only)------8.4%71.4%20.2%†Overall, this pen was “easy to learn” to use6.8%70.1%23.2%*12.6%67.2%20.2%†Selecting the correct dose each time with this pen was…(1=Difficult, 6=Easy)4.5%74.6%20.9%*8.4%69.7%21.8%*Pushing down the injection button/knob was…(1=Difficult, 6=Easy)8.5%57.6%33.9%*22.7%38.7%38.7%†The injection was smooth.13.6%57.6%28.8%*28.6%37.0%34.5%The instruction booklet is ‘user friendly’.4.0%34.5%61.6%*4.2%17.6%78.2%*Which pen would you prefer?21.5%11.9%66.7%*23.5%18.5%58.0%**p<.in non-inferiority and superiority analysis; †p<.only in non-inferiority analysis Disclosure B. Alemayehu: Employee; Self; Merck & Co., Inc. M. DiBonaventura: Employee; Self; Pfizer Inc.. Consultant; Self; Merck & Co., Inc. A.M. Nguyen: Employee; Self; Merck & Co., Inc. M. Crutchlow: Employee; Self; Merck & Co., Inc.. Consultant; Spouse/Partner; Novo Nordisk Inc., Zealand Pharma A/S, XOMA Corporation.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".