Potential Effect of Vouchers on the Completion of Self-management Education Among Patients With Diabetes
Bibliographic record
Abstract
Diabetes is a significant public health problem in eastern North Carolina, and completion of formal diabetes self-management education (DSME) is low. To seek methods to increase DSME completion, patients with diabetes in an eastern North Carolina regional health care system who had not completed DSME (n = 58) were surveyed during wellness visits to examine attitudes toward the use of vouchers (eg, coupons that purchase healthy food, exercise classes, gym memberships). There was an extremely low awareness (19%) of and referral (5%) to DSME. Most respondents (77%) said they would or might be more likely to complete DSME if they received a voucher at the end. Vouchers for healthy food venues such as farmers' markets were most preferred, and 6 months or less was found to be an acceptable time frame to use the voucher. This study offers some evidence for DSME providers to explore vouchers as one approach to increase program completion.
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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 | 0.004 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".