Health Care Professionals’ Clinical Perspectives on Glycemic Control and Satisfaction With a New Blood Glucose Meter With a Color Range Indicator: Online Evaluation in India, Russia, China, and the United States
Bibliographic record
Abstract
BACKGROUND: We previously demonstrated in patients with diabetes that displaying blood glucose results in association with color improved their ability to interpret glucose results. OBJECTIVE: The objective of this study was to investigate the perceptions of health care professionals (HCPs) in specific countries about the value of color on a new glucose meter and to determine if HCP perspectives among countries differ on the value of this approach in clinical practice. METHODS: A total of 180 HCPs, including 105 endocrinologists, 34 primary care physicians, 25 diabetes educators, and 16 pharmacists, were recruited from India (n=50), Russia (n=50), China (n=50), and the United States (n=30). These HCPs experienced the OneTouch Select Plus Simple glucose meter online from their own office computer using interactive demonstrations (webpages, meter simulator, and video clips). After providing demographic and current clinical practice insights, HCPs responded to questions about the utility of the color-enhanced glucose meter. RESULTS: Mean age and years in their current professional role for the 180 HCPs was 41.3 (SD 8.1) and 13.3 (SD 6.8) years for endocrinologists, 41.3 (SD 8.3) and 14.1 (SD 6.8) years for primary care physicians, 37.5 (SD 8.7) and 12.7 (SD 6.8) years for diabetes educators, and 35.9 (SD 5.3) and 9.5 (SD 5.2) years for pharmacists. In all, 88% (44/50) of Russian and 83% (25/30) of American HCPs said their patients find it easy to recognize low, in-range, or high blood glucose results compared to 56% (28/50) of HCPs in China and 42% (21/50) in India. Regardless of country, HCPs had less confidence that their patients act on blood glucose results with 52% (26/50) in Russia, 63% (19/30) in the United States, 60% (30/50) in China, and 40% (20/50) in India responding positively. During the interactive online meter experience, HCPs from all countries responded positively to questions about a meter with color features. After reflecting on the value of this meter, most HCPs strongly agreed or agreed their patients would be more inclined to act on results using a meter with color features (Russia: 92%, 46/50; United States: 70%, 21/30; China: 98%, 49/50; India: 94%, 47/50). They also said that color was particularly useful for patients with lower numeracy or education who may struggle with interpreting results (Russia: 98%, 49/50; United States: 77%, 23/30; China: 100%, 50/50; India: 82%, 41/50). CONCLUSIONS: This multicountry online study provides evidence that HCPs had high overall satisfaction with the OneTouch Select Plus glucose meter, which uses color-coded information to assist patients with interpreting blood glucose results. This may be especially helpful in patient populations with low numeracy or literacy and limited access to health care and direct interaction with HCPs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".