Patient and Healthcare Professional Satisfaction with the OneTouch VerioReflect® Blood Glucose Monitoring System in the UAE
Bibliographic record
Abstract
Aims: The goal of this study was to collect the opinions of patients and HCPs who used OneTouch Verio Reflect® in the United Arab Emirates (UAE). Background: Blood glucose monitoring devices are essential tools that aid healthcare professionals (HCPs) in improving outcomes in people with diabetes. Objectives: To assess the satisfaction of patients and HCPs with the new functionalities of the OneTouch Verio Reflect® Blood Glucose Meter (BGM). Method: We conducted a multicenter cross-sectional study that recruited eight HCPs and 100 patients with diabetes who had used OneTouch Verio Reflect® with OneTouch Verio® test strips for four weeks in four hospitals in the UAE. Result: Around 98% of patients and HCPs declared their satisfaction with the new features in the OneTouch Verio Reflect® BGM. Participants’ responses were not associated with the duration of diabetes (p-values >0.05) except for the Results Log feature (p-value=0.016). Patients rated Blood Sugar Mentor® messages, which include mentor tips, pattern messages, and awards, as the most important features, while HCPs rated ColorSure® Dynamic Range Indicator as the most helpful feature. Patients and HCPs stated that the “pattern found (high glucose),” which was the most frequently seen message, was the most useful message. All HCPs strongly agreed that the ColorSure® Dynamic Range Indicator helped them understand results and 98% of patients agreed that automated meter messages helped them to be more confident in following HCP recommendations. Conclusion: Patients and HCPs indicated high levels of satisfaction with the features within the OneTouch Verio Reflect® meter.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".