Usability and Teachability of Continuous Glucose Monitoring Devices in Older Adults and Diabetes Educators: Task Analysis and Ease-of-Use Survey
Bibliographic record
Abstract
BACKGROUND: Continuous glucose monitoring (CGM) devices continuously sense and relay glucose concentration data from the interstitial fluid to a mobile phone or receiver. Older adults benefit from this continuous monitoring of glucose levels. Proper deployment of the sensing wire is facilitated by a specialized applicator. OBJECTIVE: Our aim was to assess a new seventh-generation (G7) CGM device (Dexcom, Inc) for use by adults 65 years of age or older and certified diabetes care and education specialists (CDCESs). Ease of use related to intradermal insertion and mobile app setup will be assessed and compared to the fifth- and sixth-generation systems. METHODS: Formal task analysis was conducted to enumerate the number and complexity of tasks associated with CGM deployment. We recruited 10 older adults with no prior CGM experience and 10 CDCESs to assess ease of use through hands-on insertion and initiation of a G7 system followed by a survey and, for older adults, a system usability scale survey. RESULTS: About half as many tasks are needed to deploy G7 compared to G6. Older adults and CDCESs reported overall high usability of the G7 CGM device. CDCESs noted G7's easier setup compared to previous generations. The system usability scale score for the CGM system was 92.8, which reflects excellent usability. CONCLUSIONS: For CDCESs and for older adults using the G7 CGM system, cognitive burden is relatively low and reduced compared to previous CGM systems. Easing of this burden and simplification of the glucose monitoring aspect of proper diabetes management will likely contribute to improved outcomes in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".