Understanding Self-Monitoring of Blood Glucose Among Individuals With Type 1 and Type 2 Diabetes
Bibliographic record
Abstract
PURPOSE: To evaluate self-monitoring of blood glucose (SMBG) information deficits, motivational obstacles, and behavioral skills limitations in individuals with type 1 and type 2 diabetes, and to assess the relationship of these deficits with SMBG frequency. METHODS: Individuals with type 1 (n = 208; 103 male, 105 female) and type 2 (n = 218; 107 male, 111 female) diabetes participated in an online survey assessing SMBG information, motivation, behavioral skills, and behavior. RESULTS: A substantial proportion of participants scored as SMBG uninformed, unmotivated, and unskilled on specific assessment items. SMBG information, motivation, and behavioral skills deficits were significantly correlated with SMBG frequency, such that individuals with type 1 or type 2 diabetes, who were less informed, less motivated, and less behaviorally skilled, reported lower frequency of SMBG. CONCLUSION: Common and consequential SMBG information, motivation, and behavioral skills deficits were present, and patients with these gaps were less likely to test frequently. Clinical education focusing on relevant SMBG information, motivation to act, and behavioral skills for acting effectively may be a priority.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".