Exploring the role of psychological factors in diabetes management for people experiencing housing instability: a qualitative descriptive study of providers’ perspectives across Canada
Bibliographic record
Abstract
Psychological factors, such as mental health and cognition, are significant contributors to diabetes management, especially for those experiencing housing insecurity. Our aim was to explore the role of psychological factors in diabetes management for people experiencing housing instability from the perspective of providers. We designed a qualitative descriptive study that consisted of a secondary analysis of semi-structured interviews with a range of health and social care providers from programs that addressed the needs of people with diabetes who were also experiencing homelessness. Interviews were recorded, transcribed, and analyzed using inductive thematic analysis. Ninety-six participants completed semi-structured interviews. We identified four themes that showed (i) experiences of stigma and trauma influence clients’ relationships with providers and their diabetes care seeking behaviors, (ii) immediate psychological safety concerns are generally given priority over diabetes in the client’s care, (iii) substance use can create challenges when trying to manage diabetes and lead to diabetic emergencies, and (iv) varying cognitive abilities and social supports compromise a client’s ability to complete self-management tasks. We conclude that providers have a nuanced understanding of psychological factors and the challenges they create for clients with diabetes experiencing housing insecurity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".