Pharmacists’ role in diabetes management for persons with lived experience of homelessness in Canada: A qualitative study
Bibliographic record
Abstract
Introduction: Persons with lived experience of homelessness face many challenges in managing diabetes, including purchasing and storing medications, procuring healthy food and accessing healthcare services. Prior studies have found that pharmacy-led interventions for diabetes improved A1C, and lowered blood pressure and cholesterol in general populations. This study evaluated how select pharmacists in Canada have tailored their practices to serve persons with lived experiences of homelessness with diabetes. Methods: We conducted a qualitative descriptive study using open-ended interviews with inner-city pharmacists in select Canadian municipalities (Calgary, Edmonton, Vancouver, and Ottawa). We used NVivo qualitative data analysis software to facilitate thematic analysis of the data, focusing on how pharmacists contributed to diabetes care for persons with lived experience of homelessness. Results: These pharmacists developed diabetes programs after discovering an unmet need in the population. Pharmacists have the unique ability to see patients frequently, allowing tailored education and hands-on assistance with diabetes management. These pharmacists provided extra-ordinary care like financial and housing resources and many of them were uniquely embedded within other services for persons with lived experience of homelessness (i.e. housing and social work supports). Pharmacists reported struggling with balancing optimal medical care for individuals with the financial constraints of running a business. Conclusion: Pharmacists are vital members of the diabetes care team for persons with lived experience of homelessness. Government policies should support and encourage unique models of care provided by pharmacists to improve diabetes management for 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".