Assessing Willingness of Patients with Diabetes to Attend Pharmacist-Led Structured and Patient Specific Diabetes Self-Management Education
Bibliographic record
Abstract
Background: The American Diabetes Association recommends that people with diabetes should participate in diabetes self-management education, however data shows that many patients do not attend educational classes. Objectives: To examine the views of patients with diabetes who utilize services at an independent pharmacy in Richmond, Virginia regarding their (1) interest in attending diabetes self-management education and support (DSMES) services, (2) perceptions of a pharmacist leading DSMES services, (3) willingness to pay for DSMES services, and (4) relationship between self-reported diabetes management status with their willingness to attend DSMES services. Methods: A qualitative survey was administered over five months to patients with diabetes at an independent community pharmacy in Richmond, VA. The survey included 35 questions in a mixed format of Likert scale, dichotomous, and fill in the blank. Survey data was analyzed using univariate, bivariate, and/or multivariate analysis using SAS 9.4. Results: Twenty seven surveys were completed, 15% response rate. Patients were female (56.7%) with an average age of 69 ± 10.8 years. Caucasian race accounted for 90% of patients, 6.7% reported Black or African American, the remainder responded “other”. Patients agreed they were interested in attending individual virtual and in person DSMES sessions with a rate of 52% and 87%, respectively. When asked about the full service of 9 group sessions, 33% responded disagree and 30% reported agree. 52% of patients reported belief that pharmacists had the knowledge to lead sessions. When asked about willingness to pay, patients mostly selected the lowest cost option ($25 – $35). Conclusion: Patients with diabetes are willing to participate in DSMES services and believe pharmacists can lead the sessions. It is important to continue to advocate for DSMES services so patients can understand the full benefits of the program and receive the best possible care.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".